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This paper introduces realizations of a reconfigurable finite-impulse-response (FIR) filter for simultaneous equalization and lowpass filtering. The proposed structures employ properties of both a variable bandwidth (VBW) filter and a variable equalizer (VE) with an adjustable coefficient using the Farrow structure, therefore they consist of weighted combinations of fixed subfilters. Design procedures using minimax optimization technique are provided. The paper includes a design example and complexity comparisons between the proposed structures of the reconfigurable lowpass equalizer (RLPE) and a common approach of using a regular FIR equalization filter requiring online redesign.

Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified to stimulate the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed., Funding Agencies|National Key Research and Development Program of China [2018YFB1801101]; National Natural Science Foundation of China [61960206006, 62122020]; Key Technologies Research and Development Program of Jiangsu(Prospective and Key Technologies for Industry) [BE2022067, BE2022067-1, BE2022067-5]; EU H2020RISE TESTBED2 Project [872172]; EU H2020ARIADNE Project [871464]; EU H2020 RISE-6G Project [101017011]; U.S. National Science Foundation [CCF-1908308, CNS-2128448]; Engineering and Physical Sciences Research Council Project [EP/W016605/1, EP/X01228X/1]; European Research Councils Advanced Fellow Grant Quant Com [789028]

In this thesis, we focus on vulnerabilities and robustness of two wireless communication technologies: global navigation satellite system (GNSS), a technology that provides position-velocity-time information, and massive multiple-input-multiple-output (MIMO), a core cellular 5G technology. In particular, we investigate spoofing and jamming attacks to GNSS and massive MIMO, respectively, and the robust massive MIMO receiver against impulsive noises. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal to interference plus noise ratio (SINR) on the receiver side. The reason why we investigate impulsive noises is that the standard wireless receivers assume that the noise has Gaussian distribution. However, the impulsive noises may appear in any communication link. The difference between impulsive noises and standard Gaussian noises is that it is more likely to observe outliers in impulsive noises. Therefore, we question whether the standard Gaussian receivers are robust against impulsive noises and design robust receivers against impulsive noises. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation's cellular networks? Which jamming attack strategies are the best from the jammer's perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number of spoofers in the environment. In paper C and D, we design robust receivers for massive MIMO against impulsive noise. In paper C, w

In this thesis, we focus on vulnerabilities and robustness of two wireless communication technologies: global navigation satellite system (GNSS), a technology that provides position-velocity-time information, and massive multiple-input-multiple-output (MIMO), a core cellular 5G technology. In particular, we investigate spoofing and jamming attacks to GNSS and massive MIMO, respectively, and the robust massive MIMO receiver against impulsive noises. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal to interference plus noise ratio (SINR) on the receiver side. The reason why we investigate impulsive noises is that the standard wireless receivers assume that the noise has Gaussian distribution. However, the impulsive noises may appear in any communication link. The difference between impulsive noises and standard Gaussian noises is that it is more likely to observe outliers in impulsive noises. Therefore, we question whether the standard Gaussian receivers are robust against impulsive noises and design robust receivers against impulsive noises. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation's cellular networks? Which jamming attack strategies are the best from the jammer's perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number of spoofers in the environment. In paper C and D, we design robust receivers for massive MIMO against impulsive noise. In paper C, w

In this thesis, we focus on vulnerabilities and robustness of two wireless communication technologies: global navigation satellite system (GNSS), a technology that provides position-velocity-time information, and massive multiple-input-multiple-output (MIMO), a core cellular 5G technology. In particular, we investigate spoofing and jamming attacks to GNSS and massive MIMO, respectively, and the robust massive MIMO receiver against impulsive noises. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal to interference plus noise ratio (SINR) on the receiver side. The reason why we investigate impulsive noises is that the standard wireless receivers assume that the noise has Gaussian distribution. However, the impulsive noises may appear in any communication link. The difference between impulsive noises and standard Gaussian noises is that it is more likely to observe outliers in impulsive noises. Therefore, we question whether the standard Gaussian receivers are robust against impulsive noises and design robust receivers against impulsive noises. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation's cellular networks? Which jamming attack strategies are the best from the jammer's perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number of spoofers in the environment. In paper C and D, we design robust receivers for massive MIMO against impulsive noise. In paper C, w

In this thesis, we focus on vulnerabilities and robustness of two wireless communication technologies: global navigation satellite system (GNSS), a technology that provides position-velocity-time information, and massive multiple-input-multiple-output (MIMO), a core cellular 5G technology. In particular, we investigate spoofing and jamming attacks to GNSS and massive MIMO, respectively, and the robust massive MIMO receiver against impulsive noises. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal to interference plus noise ratio (SINR) on the receiver side. The reason why we investigate impulsive noises is that the standard wireless receivers assume that the noise has Gaussian distribution. However, the impulsive noises may appear in any communication link. The difference between impulsive noises and standard Gaussian noises is that it is more likely to observe outliers in impulsive noises. Therefore, we question whether the standard Gaussian receivers are robust against impulsive noises and design robust receivers against impulsive noises. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation's cellular networks? Which jamming attack strategies are the best from the jammer's perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number of spoofers in the environment. In paper C and D, we design robust receivers for massive MIMO against impulsive noise. In paper C, w

The knowledge of channel covariance matrices is of paramount importance to the estimation of instantaneous channels and the design of beamforming vectors in multi-antenna systems. In practice, an abrupt change in channel covariance matrices may occur due to the change in the environment and the user location. Although several works have proposed efficient algorithms to estimate the channel covariance matrices after any change occurs, how to detect such a change accurately and quickly is still an open problem in the literature. In this paper, we focus on channel covariance change detection between a multiantenna base station (BS) and a single-antenna user equipment (UE). To provide theoretical performance limit, we first propose a genie-aided change detector based on the log-likelihood ratio (LLR) test assuming the channel covariance matrix after change is known, and characterize the corresponding missed detection and false alarm probabilities. Then, this paper considers the practical case where the channel covariance matrix after change is unknown. The maximum likelihood (ML) estimation technique is used to predict the covariance matrix based on the received pilot signals over a certain number of coherence blocks, building upon which the LLR-based change detector is employed. Numerical results show that our proposed scheme can detect the change with low error probability even when the number of channel samples is small such that the estimation of the covariance matrix is not that accurate. This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.

An intelligent reflecting surface (IRS), consisting of reconfigurable metamaterials, can be used to partially control the radio environment and thereby bring new features to wireless communications. Previous works on IRS have particularly studied the range extension use case and under what circumstances the new technology can beat relays. In this paper, we study another use case that might have a larger impact on the channel capacity: rank improvement. One of the classical bottlenecks of point-to-point MIMO communications is that the capacity gains provided by spatial multiplexing are only large at high SNR, and high SNR channels are mainly appearing in line-of-sight (LoS) scenarios where the channel matrix has low rank and therefore does not support spatial multiplexing. We demonstrate how an IRS can be used and optimized in such scenarios to increase the rank of the channel matrix, leading to substantial capacity gains., The paper was supported by ELLIIT and Swedish Research Council

Backscatter communication (BSC) is a promising solution for Internet-of-Things (IoT) connections due to its lowcomplexity, low-cost, and energy-efficient solution for sensors. There are several network infrastructure setups that can be used for BSC with IoT nodes/passive devices. One of them is a bistatic setup where there is a need for high dynamic range and high-resolution analog-to-digital converters at the reader side. In this paper, we investigate a bistatic BSC setup with multiple antennas. We propose a novel algorithm to suppress direct link interference between the carrier emitter (CE) and the reader using beamforming into the nullspace of the CEreader direct link to decrease the dynamic range of the system and increase the detection performance of the backscatter device (BSD). Further, we derive a Neyman-Pearson (NP) test and an exact closed-form expression for its performance in the detection of the BSD. Finally, simulation results show that the dynamic range of the system is significantly decreased and the detection performance of the BSD is increased by the proposed algorithm compared to a system not using beamforming in the CE, which could then be used in a host of different practical fields such as agriculture, transportation, factories, hospitals, smart cities, and smart homes., Funding Agencies|European Union [101013425]; ELLIIT; KAW foundation

The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field., Funding Agencies|National Key R&D Program of China [2020YFB1807201]; National Natural Sci-ence Foundation of China [61 971 027, U1834210, 61 961 130 391]; Beijing Natural Science Foundation [L202013]; Frontiers Science Center for Smart High-speed Railway System [2020JBZD005]; Royal Society Newton Advanced Fellowship [NA191006]; Swedish Research Council [2019-05 068]

Massive multiple input multiple output (MIMO)emerged as the leading technology for supporting fifth generation(5G) and beyond 5G cellular communication systems. Due to thetremendous increase in data traffic in urban areas and to meetsuch a significant demand, most studies consider macro/micro celldeployments in urban environments. Internet service providers(ISPs) are less interested in providing communication services inrural areas considering the relatively low profits compared to thedeployment and maintenance costs. In this paper, we investigatethe massive MIMO performance in rural scenarios. In particular,we investigate different aspects to consider while designing along-range communication system. We propose to use elevatedbase station (BS) with sectorized antennas with unusually largeaperture and implement a user scheduling algorithm at theBS to provide full digital coverage. We analyze the coveragerange of a massive MIMO system to provide high-rate services.Furthermore, we also analyze the link budget requirements andthe rates users can achieve in such a SuperCell massive MIMOnetwork., Funding: ELLIIT; Swedish Research Council (VR); KAW foundation

In this paper, we consider privacy aspects of wireless federated learning (FL) with Over-the-Air (OtA) transmission of gradient updates from multiple users/agents to an edge server. OtA FL enables the users to transmit their updates simultaneously with linear processing techniques, which improves resource efficiency. However, this setting is vulnerable to privacy leakage since an adversary node can hear directly the uncoded message. Traditional perturbation-based methods provide privacy protection while sacrificing the training accuracy due to the reduced signal-to-noise ratio. In this work, we aim at minimizing privacy leakage to the adversary and the degradation of model accuracy at the edge server at the same time. More explicitly, spatially correlated perturbations are added to the gradient vectors at the users before transmission. Using the zero-sum property of the correlated perturbations, the side effect of the added perturbation on the aggregated gradients at the edge server can be minimized In the meanwhile, the added perturbation will not be canceled out at the adversary, which prevents privacy leakage. Theoretical analysis of the perturbation covariance matrix, differential privacy, and model convergence is provided, based on which an optimization problem is formulated to jointly design the covariance matrix and the power scaling factor to balance between privacy protection and convergence performance. Simulation results validate the correlated perturbation approach can provide strong defense ability while guaranteeing high learning accuracy., Funding Agencies|Security Link; ELLIIT; KAW foundation

Base stations in 5G and beyond use advanced antenna systems (AASs), where multiple passive antenna elements and radio units are integrated into a single box. A critical bottleneck of such a system is the digital fronthaul between the AAS and baseband unit (BBU), which has limited capacity. In this paper, we study an AAS used for precoded downlink transmission over a multi-user multiple-input multiple-output (MU-MIMO) channel. First, we present the baseline quantization-unaware precoding scheme created when a precoder is computed at the BBU and then quantized to be sent over the fronthaul. We propose a new precoding design that is aware of the fronthaul quantization. We formulate an optimization problem to minimize the mean squared error at the receiver side. We rewrite the problem to utilize mixed-integer programming to solve it. The numerical results manifest that our proposed precoding greatly outperforms quantization-unaware precoding in terms of sum rate., Funding Agencies|Knut and Alice Wallenberg Foundation

Previous works on cell-free massive MIMO mostly consider physical-layer and fronthaul transport aspects. How to deploy cell-free massive MIMO functionality in a practical wireless system is an open problem. This paper proposes a new cell-free architecture that can be implemented on top of a virtualized cloud radio access network (V-CRAN). We aim to minimize the end-to-end power consumption by jointly considering the radio, optical fronthaul, virtualized cloud processing resources, and spectral efficiency requirements of the user equipments. The considered optimization problem is cast in a mixed binary second-order cone programming form and, thus, the global optimum can be found using a branch-and-bound algorithm. The optimal power-efficient solution of our proposed cell-free system is compared with conventional small-cell implemented using V-CRAN, to determine the benefits of cell-free networking. The numerical results demonstrate that cell-free massive MIMO increases the maximum rate substantially, which can be provided with almost the same energy per bit. We show that it is more power-efficient to activate cell-free massive MIMO already at low spectral efficiencies (above 1 bit/s/Hz)., Funding Agencies|CELTIC -NEXT project AI4Green; Vinnova, Swedish Innovation Agency

An Intelligent Reflecting Surface (IRS) is an emerging technology for improving the data rate over wireless channels by controlling the underlying channel. In this paper, we describe a novel solution for IRS configuration to maximize the data rate over wideband channels. The optimization is obtained by online training of a deep generative neural network. Inspired by related works in image processing, this network is randomly initialized and acts as a regularization term for the optimization process since the structure of the generator is sufficient to capture a great deal of IRS statistics prior to any learning. In contrast to recent deep learning techniques for IRS configuration, the proposed technique does not require an offline training stage and can adapt quickly to any environment. Compared to the previous state-of-the-art algorithm, the proposed method is significantly faster and obtains IRS configurations that achieve higher data transmission rates.

How to manage the interference introduced by the enormous wireless devices is a crucial issue to address in the prospective sixth-generation (6G) communications. The treating interference as noise (TIN) optimality conditions are commonly used for interference management and thus attract significant interest in existing wireless systems. Cell-free massive multiple-input multiple-output (CF mMIMO) is a promising technology in 6G that exhibits high system throughput and excellent interference management by exploiting a large number of access points (APs) to serve the users collaboratively. In this paper, we take the first step on studying TIN in CF mMIMO systems from a stochastic geometry perspective by investigating the probability that the TIN conditions hold with spatially distributed network nodes. We propose a novel analytical framework for TIN in a CF mMIMO system with both Binomial Point Process (BPP) and Poisson Point Process (PPP) approximations. We derive the probability that the TIN conditions hold in close form using the PPP approximation. Numerical results validate our derived expressions and illustrate the impact of various system parameters on the probability that the TIN conditions hold., Funding Agencies|Fundamental Research Funds for the Central Universities [2021YJS001]; National Key R&D Program of China [2020YFB1807201]; National Natural Science Foundation of China [61971027, 61961130391]; Beijing Natural Science Foundation [L202013]; Natural Science Foundation of Jiangsu Province [BK20212002]; Royal Society Newton Advanced Fellowship [NA191006]; Frontiers Science Center for Smart Highspeed Railway System; Center for Industrial Information Technology (CENIIT); Excellence Center at Linkoping-Lund in Information Technology (ELLIIT)

Wireless power transfer (WPT) is an alternative technology to conventional batteries for powering Internet of things (IoT) devices. WPT is especially beneficial in situations when battery replacement is infeasible or expensive. It can also reduce battery-related e-waste. In this paper, we analyze the limits of adopting WPT technology for remote powering of IoT devices. We assume that an IoT device periodically harvests energy from a base station (BS) and transmits a data packet related to the sensor measurement under shadow fading channel conditions. Our goal is to characterize the epsilon-coverage range, where epsilon is the probability of the coverage. Our analysis shows a tradeoff between the coverage range and the rate of sensor measurements, where the maximal epsilon-coverage range is achieved as the sensor measurement rate approaches zero. We demonstrate that the weighted sum of the sleep power consumption and the harvesting sensitivity power of an IoT device limits the maximal e-coverage range. Beyond that range, the IoT device cannot harvest enough energy to operate. The desired rate of the sensor measurements also significantly impacts the epsilon-coverage range. Our results suggest that for an IoT device designed using current technology, the maximal 0.95-coverage range is in the order of 120 m. When high measurement rates are required, the coverage range drops to 50-100 m. Compared to battery-powered IoT devices, WPT is well-suited for medium-range applications plus when battery replacement is costly.

In this paper, we examine the energy consumption of a user equipment (UE) when it transmits a finite-sized data packet. The receiving base station (BS) controls a reconfigurable intelligent surface (RIS) that can be utilized to improve the channel conditions, if additional pilot signals are transmitted to configure the RIS. We derive a formula for the energy consumption taking both the pilot and data transmission powers into account. By dividing the RIS into subarrays consisting of multiple RIS elements using the same reflection coefficient, the pilot overhead can be tuned to minimize the energy consumption while maintaining parts of the aperture gain. Our analytical results show that there exists an energy-minimizing subarray size. For small data blocks and when the channel conditions between the BS and UE are favorable compared to the path to the RIS, the energy consumption is minimized using large subarrays. When the channel conditions to the RIS are better and the data blocks are large, it is preferable to use fewer elements per subarray and potentially configure the elements individually., Funding Agencies|Swedish Foundation for Strategic Research [FFL18-0277]

RadioWeaves, in which distributed antennas with integrated radio and compute resources serve a large number of users, is envisioned to provide high data rates in next-generation wireless systems. In this paper, we develop a physical layer abstraction model to evaluate the performance of different RadioWeaves deployment scenarios. This model helps speed up system-level simulators of the RadioWeaves and is made up of two blocks. The first block generates a vector of signalto-interference-plus-noise ratios (SINRs) corresponding to each coherence block, and the second block predicts the packet error rate corresponding to the SINRs generated. The vector of SINRs generated depends on different parameters such as the number of users, user locations, antenna configurations, and precoders. We have also considered different antenna gain patterns, such as omni-directional and directional microstrip patch antennas. Our model exploits the benefits of exponential effective SINR mapping (EESM). We study the robustness and accuracy of the EESM for RadioWeaves., Funding Agencies|European Union [101013425]

In this paper, we work on channel estimationtechniques for massive multiple-input multiple-output (MIMO) with Cauchy noise. In the standard massive MIMO setup, the users transmit orthonormal pilots during the training phase and the received signal in the base station is projected onto each orthonormal pilot signal. This process is optimum when the noise is Gaussian. In other words, the obtained signal after this processis the sufficient statistic and we do not lose any information. We show that this process is not optimum when the noise is Cauchy. Hence, we propose a channel estimation technique forthe unprocessed received signal. The proposed channel estimation technique is compared with the channel estimates that are obtained from the projected signal., Funding: Swedish Foundation for Strategic Research (SSF)

The successful emergence of deep learning (DL) in wireless system applications has raised concerns about new security-related challenges. One such security challenge is adversarial attacks. Although there has been much work demonstrating the susceptibility of DL-based classification tasks to adversarial attacks, regression-based problems in the context of a wireless system have not been studied so far from an attack perspective. The aim of this paper is twofold: (i) we consider a regression problem in a wireless setting and show that adversarial attacks can break the DL-based approach and (ii) we analyze the effectiveness of adversarial training as a defensive technique in adversarial settings and show that the robustness of DL-based wireless system against attacks improves significantly. Specifically, the wireless application considered in this paper is the DL-based power allocation in the downlink of a multicell massive multi-input-multi-output system, where the goal of the attack is to yield an infeasible solution by the DL model. We extend the gradient-based adversarial attacks: fast gradient sign method (FGSM), momentum iterative FGSM, and projected gradient descent method to analyze the susceptibility of the considered wireless application with and without adversarial training. We analyze the deep neural network (DNN) models performance against these attacks, where the adversarial perturbations are crafted using both the white-box and black-box attacks., Funding Agencies|Security-Link; SSF SURPRISE project

In this paper, two different timing-mismatch compensation strategies for two-channel time-interleaved analog-to-digital converters are comprehensively analyzed and compared. In the first strategy (SA), one channel serves as a reference channel, and the other channel is compensated to match the reference channel using the timing mismatch between the channels. In the second strategy (SB), both channels are compensated to match each other, using half the value of the channel mismatch with different signs. For SB, the paper introduces a novel compensation structure that utilizes parallel differentiator-multiplier (PDM) branches. Expressions for the spurious-free dynamic range (SFDR) after compensation are derived for both strategies. These expressions reveal that the novel PDM structure achieves a remarkably greater SFDR than the existing cascaded differentiator-multiplier (CDM) compensation structure which can be used for both SA and SB. This is because, after compensation, the remaining aliasing distortion in the proposed PDM structure is shown to be of higher approximation order (in terms of the mismatch value) and thus substantially smaller than in the CDM structure. Simulations included in the paper validate the theoretical results., Funding Agencies|National Natural Science Foundation of China [61701509]; Science and Technology on Analog Integrated Circuit Laboratory [JCKY2019210C027]; Science Support Program of NationalUniversity of Defense and Technology [ZK20-06]

The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field., Funding Agencies|National Key R&D Program of China [2020YFB1807201]; National Natural Sci-ence Foundation of China [61 971 027, U1834210, 61 961 130 391]; Beijing Natural Science Foundation [L202013]; Frontiers Science Center for Smart High-speed Railway System [2020JBZD005]; Royal Society Newton Advanced Fellowship [NA191006]; Swedish Research Council [2019-05 068]

The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field., Funding Agencies|National Key R&D Program of China [2020YFB1807201]; National Natural Sci-ence Foundation of China [61 971 027, U1834210, 61 961 130 391]; Beijing Natural Science Foundation [L202013]; Frontiers Science Center for Smart High-speed Railway System [2020JBZD005]; Royal Society Newton Advanced Fellowship [NA191006]; Swedish Research Council [2019-05 068]

The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field., Funding Agencies|National Key R&D Program of China [2020YFB1807201]; National Natural Sci-ence Foundation of China [61 971 027, U1834210, 61 961 130 391]; Beijing Natural Science Foundation [L202013]; Frontiers Science Center for Smart High-speed Railway System [2020JBZD005]; Royal Society Newton Advanced Fellowship [NA191006]; Swedish Research Council [2019-05 068]

The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field., Funding Agencies|National Key R&D Program of China [2020YFB1807201]; National Natural Sci-ence Foundation of China [61 971 027, U1834210, 61 961 130 391]; Beijing Natural Science Foundation [L202013]; Frontiers Science Center for Smart High-speed Railway System [2020JBZD005]; Royal Society Newton Advanced Fellowship [NA191006]; Swedish Research Council [2019-05 068]

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macro-diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses, Efterfrågan på data ökar ständigt och kravet på hastighet har ökat enormt. Framtida trådlösa nätverk behöver stödja tre generiska heterogena tjänster: enhanced mobile broadband (eMBB), ultra-reliable low latency communica-tion (URLLC) och massive machine type communication (mMTC). Massiv MIMO har visat sig vara en lovande teknik för att möta efterfrågan och är nu en integrerad del av 5G-nätverket. För att få höga datahastigheter övervägs extrem förtätning av nätverket genom att distribuera fler basstationer i samma geografiska område. Detta leder till en ökning av intercellinterferens men systemets kapacitet begränsas av intercellinterferensen. För att mildra intercellinterferensen förespråkas distribuerad MIMO. Cellfri massiv MIMO utnyttjar alla fördelar från ultraförtätning, massiv MIMO och distribuerad MIMO-teknik och fungerar utan cellgränser. I denna avhandling studerar vi random access, extrema multiplexerings möjligheter och synkroniseringsaspekter av distribuerad massiv MIMO. I Paper A studeras aktivitetsdetekteringen i grant-free random access för mMTC i cellfria massiv MIMO-nätverk. En algoritm föreslås för aktivitetsdetektering baserad på˚ maximum likelihood-metoden och resultaten visar att den makro-diversitetsvinst som tillhandahålls av den cellfria arkitekturen förbättrar aktivitetsdetekteringsprestandan jämfört med samlokaliserad arkitektur när täckningsområdet är stort. RadioWeaves-teknologi är en ny trädlös infrastruktur utformad för inomhusapplikationer som utnyttjar fördelarna med massiv MIMO och cellfri massiv MIMO. I Paper B studerar vi den extrema multiplexeringsförmågan hos RadioWeaves som kan ge höga datahastigheter med mycket låg effekt. Vi observerar att RadioWeaves-arkitekturen kan rumsligt separera användare mycket bättre än en konventionell samlokaliserad arkitektur, som uppväger förlusterna orsakade av gitterlober och därmed sparar mycket på sändningseffekten. Paper C studerar synkroniseringsaspekten av distribuerad massiv MIMO. Vi före

The data traffic in wireless networks is steadily growing. The long-term trend follows Coopers law, where the traffic is doubled every Two-and-a-half year, and it will likely continue for decades to come. The data transmission is tightly connected with the energy consumption in the power amplifiers, transceiver hardware, and baseband processing. The relation is captured by the energy efficiency metric, measured in bit/Joule, which describes how much energy is consumed per correctly received information hit. While the data rate is fundamentally limited by the channel capacity, there is currently no clear understanding of how energy-efficient a communication system can become. Current research papers typically present values on the order of 10Mbit/Joule, while previous network generations seem to operate at energy efficiencies on the order of 10 kbit/Joule. Is this roughly as energy-efficient future systems (5G and beyond) can become, or are we still far from the physical limits? These questions are answered in this paper. We analyze a different cases representing potential future deployment and hardware characteristics., Funding Agencies|ELLIIT; Swedish Foundation for Strategic Research (SSF); Swedish Research Council (VR)

We study downlink (DL) channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in a time-division duplex. The users must know their effective channel gains to decode their received DL data signals. A common approach is to use the mean value as the estimate, motivated by channel hardening, but this is associated with a substantial performance loss in non-isotropic scattering environments. We propose two novel estimation methods. The first method is model-aided and utilizes asymptotic arguments to identify a connection between the effective channel gain and the average received power during a coherence block. The second one is a deep-learning-based approach that uses a neural network to identify a mapping between the available information and the effective channel gain. We compare the proposed methods against other benchmarks in terms of normalized mean-squared error and spectral efficiency (SE). The proposed methods provide substantial improvements, with the learning-based solution being the best of the considered estimators., Funding agencies: This paper was supported by ELLIIT and the Grant 2019-05068 from the Swedish Research Council.

Reconfigurable intelligent surfaces (RISs) have recently received widespread attention in the field of wireless communication. An RIS can be controlled to reflect incident waves from the transmitter towards the receiver; a feature that is believed to fundamentally contribute to beyond SG wireless technology. The typical RIS consists of entirely passive elements, which requires the high-dimensional channel estimation to be done elsewhere. Therefore, in this paper, we present a semi-passive large-scale RIS architecture equipped with only a small fraction of simplified receiver units with only 1-bit quantization. Based on this architecture, we first propose an alternating direction method of multipliers (ADMM)-based approach to recover the training signals at the passive RIS elements, We then obtain the global channel by combining a channel sparsification step with the generalized approximate message passing (GAMP) algorithm. Our proposed scheme exploits both the sparsity and low-rankness properties of the channel in the joint spatial-frequency domain of a wideband mmWave multiple-input-multiple-output (MIMO) communication system. Simulation results show that the proposed algorithm can significantly reduce the pilot signaling needed for accurate channel estimation and outperform previous methods, even with fewer receiver units.

In this paper, we consider a cellular-based Internet of things (IoT) network consisting of IoT devices that can communicate directly with each other in a device-to-device (D2D) fashion as well as send real-time status updates about some underlying physical processes observed by them. We assume that such real-time applications are supported by cellular networks where cellular base stations (BSs) collect status updates over time from a subset of the IoT devices in their vicinity. We characterize two performance metrics: i) the network throughput which quantifies the performance of D2D communications, and ii) the Age of Information which quantifies the performance of the real-time IoT-enabled applications. Concrete analytical results are derived using stochastic geometry by modeling the locations of IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another Independent PPP. Our results provide useful design guidelines on the efficient deployment of future IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications., Funding Agencies|U.S. NSF [CPS-1739642]

Reconfigurable intelligent surfaces (RISs) have attracted great attention as a potential beyond SG technology. These surfaces consist of many passive elements of metamaterials whose impedance can be controllable to change the phase, amplitude, or other characteristics of wireless signals impinging on them. Channel estimation is a critical task when it comes to the control of a large RIS when having a channel with a large number of multipath components. In this paper, we propose a novel channel estimation scheme that exploits spatial correlation characteristics at both the massive multiple-input multiple-output (MIMO) base station and the planar RISs, and other statistical characteristics of multi-specular fading in a mobile environment. Moreover, a novel heuristic for phase-shift selection at the RISs is developed, inspired by signal processing methods that are effective in conventional massive MIMO. Simulation results demonstrate that the proposed uplink RIS-aided framework improves the spectral efficiency of the cell-edge mobile users substantially in comparison to a conventional single-cell massive MIMO system., Funding Agencies|Swedish Foundation for Strategic Research [FFL18-0277]

Wireless communication technology has evolved rapidly during the last 20 years. Nowadays, there are huge networks providing communication infrastructures to not only people but also to machines, such as unmanned air and ground vehicles, cars, household appliances and so on. There is no doubt that new wireless communication technologies must be developed, that support the data traffic in these emerging, large networks. While developing these technologies, it is also important to investigate the vulnerability of these technologies to different malicious attacks. In particular, spoofing and jamming attacks should be investigated and new countermeasure techniques should be developed. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal-to-interference-and-noise ratio (SINR) on the receiver side. In this thesis, we analyze the effects of spoofing and jamming both on global navigation satellite system (GNSS) and on massive multiple-input multiple-output (MIMO) communications. GNSS is everywhere and used to provide location information. Massive MIMO is one of the cornerstone technologies in 5G. We also propose countermeasure techniques to the studied spoofing and jamming attacks. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation’s cellular networks? Which jamming attack strategies are the best from the jammer’s perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number

Wireless communication technology has evolved rapidly during the last 20 years. Nowadays, there are huge networks providing communication infrastructures to not only people but also to machines, such as unmanned air and ground vehicles, cars, household appliances and so on. There is no doubt that new wireless communication technologies must be developed, that support the data traffic in these emerging, large networks. While developing these technologies, it is also important to investigate the vulnerability of these technologies to different malicious attacks. In particular, spoofing and jamming attacks should be investigated and new countermeasure techniques should be developed. In this context, spoofing refers to the situation in which a receiver identifies falsified signals, that are transmitted by the spoofers, as legitimate or trustable signals. Jamming, on the other hand, refers to the transmission of radio signals that disrupt communications by decreasing the signal-to-interference-and-noise ratio (SINR) on the receiver side. In this thesis, we analyze the effects of spoofing and jamming both on global navigation satellite system (GNSS) and on massive multiple-input multiple-output (MIMO) communications. GNSS is everywhere and used to provide location information. Massive MIMO is one of the cornerstone technologies in 5G. We also propose countermeasure techniques to the studied spoofing and jamming attacks. More specifically, in paper A we analyze the effects of distributed jammers on massive MIMO and answer the following questions: Is massive MIMO more robust to distributed jammers compared with previous generation’s cellular networks? Which jamming attack strategies are the best from the jammer’s perspective, and can the jamming power be spread over space to achieve more harmful attacks? In paper B, we propose a detector for GNSS receivers that is able to detect multiple spoofers without having any prior information about the attack strategy or the number

Novel network architectures for 6G distributed massive MIMO systems rely on coherent signaling by distributed antenna panels which are coordinated by a central controller. This type of network architecture is based on reciprocity operation where antenna panels rely on uplink channel estimates for coherent downlink precoding. This paper proposes a calibration method for distributed massive MIMO systems, which overcomes hardware non-reciprocities in order to enable reciprocity-based operation. Measurements for system calibration are collected via a beam-sweep between all pairs of antenna panels. We lay out the system model for this new setup, and propose a maximum likelihood-based procedure to compute calibration coefficients based on the collected measurement set. The procedure is computationally efficient and stable, since 1) each iteration has a closed-form, and 2) the procedure is guaranteed to converge to at least a local optimum (or saddle point). Simulations indicate significant calibration improvements compared to re-using state of the art calibration schemes for the problem at hand., Funding agencies: This project has received funding from the European Union's Horizon 2020 research andinnovation programme under grant agreement No. 101013425.

Novel network architectures for 6G distributed massive MIMO systems rely on coherent signaling by distributed antenna panels which are coordinated by a central controller. This type of network architecture is based on reciprocity operation where antenna panels rely on uplink channel estimates for coherent downlink precoding. This paper proposes a calibration method for distributed massive MIMO systems, which overcomes hardware non-reciprocities in order to enable reciprocity-based operation. Measurements for system calibration are collected via a beam-sweep between all pairs of antenna panels. We lay out the system model for this new setup, and propose a maximum likelihood-based procedure to compute calibration coefficients based on the collected measurement set. The procedure is computationally efficient and stable, since 1) each iteration has a closed-form, and 2) the procedure is guaranteed to converge to at least a local optimum (or saddle point). Simulations indicate significant calibration improvements compared to re-using state of the art calibration schemes for the problem at hand., Funding agencies: This project has received funding from the European Union's Horizon 2020 research andinnovation programme under grant agreement No. 101013425.

This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or approximately, when having a sequential fronthaul. More precisely, each access point (AP) in the network computes partial sufficient statistics locally, fuses it with received partial statistics from another AP, and then forward the result to the next AP. Once the sufficient statistics reach the central processing unit, it performs the soft demodulation by computing the log-likelihood ratio (LLR) per bit, and then a channel decoding algorithm (e.g., a Turbo decoder) is utilized to decode the bits. We derive the distributed computation of LLR analytically., Funding: Swedish Research Council (VR)Swedish Research Council; ELLIIT

In a distributed multi-antenna system, multiple geographically separated transmit nodes communicate simultaneously to a receive node. Synchronization of these nodes is essential to achieve a good performance at the receiver. RadioWeaves is a new paradigm of cell-free massive MIMO array deployment using distributed multi-antenna panels in indoor environments. In this paper, we study the carrier frequency synchronization problem in distributed RadioWeave panels. We propose a novel, over-the-air synchronization protocol, which we call as BeamSync, to synchronize all the different multi-antenna transmit panels. We also show that beamforming the synchronization signal in the dominant direction of the channel between the panels is optimal and the synchronization performance is significantly better than traditional beamforming techniques.

The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry. Most papers make theoretical studies based on elementary models, while the prototyping of RIS-aided wireless communication and real-world field trials are scarce. In this paper, we describe a new RIS prototype consisting of 1100 controllable elements working at 5.8 GHz band. We propose an efficient algorithm for configuring the RIS over the air by exploiting the geometrical array properties and a practical receiver-RIS feedback link. In our indoor test, where the transmitter and receiver are separated by a 30 cm thick concrete wall, our RIS prototype provides a 26 dB power gain compared to the baseline case where the RIS is replaced by a copper plate. A 27 dB power gain was observed in the short-distance outdoor measurement. We also carried out long-distance measurements and successfully transmitted a 32 Mbps data stream over 500 m. A 1080p video was live-streamed and it only played smoothly when the RIS was utilized. The power consumption of the RIS is around 1 W. Our paper is vivid proof that the RIS is a very promising technology for future wireless communications., Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [62071192, 62071191]; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research

Classification between different activities in an indoor environment using wireless signals is an emerging technology for various applications, including intrusion detection, patient care, and smart home. Researchers have shown different methods to classify activities and their potential benefits by utilizing WiFi signals. In this paper, we analyze classification of moving objects by employing machine learning on real data from a massive multi-input-multi-output (MIMO) system in an indoor environment. We conduct measurements for different activities in both line-of-sight and non line-of-sight scenarios with a massive MIMO testbed operating at 3.7 GHz. We propose algorithms to exploit amplitude and phase-based features classification task. For the considered setup, we benchmark the classification performance and show that we can achieve up to 98% accuracy using real massive MIMO data, even with a small number of experiments. Furthermore, we demonstrate the gain in performance results with a massive MIMO system as compared with that of a limited number of antennas such as in WiFi devices., Funding Agencies|ELLIIT, Security-Link; Ericsson ABEricsson

Novel network architectures for 6G distributed massive MIMO systems rely on coherent signaling by distributed antenna panels which are coordinated by a central controller. This type of network architecture is based on reciprocity operation where antenna panels rely on uplink channel estimates for coherent downlink precoding. This paper proposes a calibration method for distributed massive MIMO systems, which overcomes hardware non-reciprocities in order to enable reciprocity-based operation. Measurements for system calibration are collected via a beam-sweep between all pairs of antenna panels. We lay out the system model for this new setup, and propose a maximum likelihood-based procedure to compute calibration coefficients based on the collected measurement set. The procedure is computationally efficient and stable, since 1) each iteration has a closed-form, and 2) the procedure is guaranteed to converge to at least a local optimum (or saddle point). Simulations indicate significant calibration improvements compared to re-using state of the art calibration schemes for the problem at hand., Funding agencies: This project has received funding from the European Union's Horizon 2020 research andinnovation programme under grant agreement No. 101013425.

Deep learning (DL) is becoming popular as a new tool for many applications in wireless communication systems. However, for many classification tasks (e.g., modulation classification) it has been shown that DL-based wireless systems are susceptible to adversarial examples; adversarial examples are well-crafted malicious inputs to the neural network (NN) with the objective to cause erroneous outputs. In this paper, we extend this to regression problems and show that adversarial attacks can break DL-based power allocation in the downlink of a massive multiple-input-multiple-output (maMIMO) network. Specifically, we extend the fast gradient sign method (FGSM), momentum iterative FGSM, and projected gradient descent adversarial attacks in the context of power allocation in a maMIMO system. We benchmark the performance of these attacks and show that with a small perturbation in the input of the NN, the white-box attacks can result in infeasible solutions up to 86%. Furthermore, we investigate the performance of black-box attacks. All the evaluations conducted in this work are based on an open dataset and NN models, which are publicly available.

Caching popular contents at a large number of access points and edge-clouds is a promising solution to alleviate the increasing backhaul congestion in beyond fifth-generation (B5G) networks. By integrating with cell-free massive multiple-input multiple-output (CF mMIMO), wireless caching can harness their combined virtues, i.e., almost uniform service quality, strong macro-diversity, and reduction of the data traffic from the core network. In this paper, we consider an offline cache-aided scenario with two caching strategies to minimize the total energy consumption (TEC), which are evaluated from the cache hit probability (CHP). The TEC minimization is showed to be NP-complete and, hence, dealt with a proposed greedy algorithm. An adaptive power control policy is proposed to reduce the TEC. We compare CF mMIMO with small cells in terms of the successful content delivery probability (SCDP) and TEC, respectively. The numerical results show that CF mMIMO can offer a much more uniform service, significantly higher SCDP, and lower average TEC when compared to than SC.

Novel network architectures for 6G distributed massive MIMO systems rely on coherent signaling by distributed antenna panels which are coordinated by a central controller. This type of network architecture is based on reciprocity operation where antenna panels rely on uplink channel estimates for coherent downlink precoding. This paper proposes a calibration method for distributed massive MIMO systems, which overcomes hardware non-reciprocities in order to enable reciprocity-based operation. Measurements for system calibration are collected via a beam-sweep between all pairs of antenna panels. We lay out the system model for this new setup, and propose a maximum likelihood-based procedure to compute calibration coefficients based on the collected measurement set. The procedure is computationally efficient and stable, since 1) each iteration has a closed-form, and 2) the procedure is guaranteed to converge to at least a local optimum (or saddle point). Simulations indicate significant calibration improvements compared to re-using state of the art calibration schemes for the problem at hand., Funding agencies: This project has received funding from the European Union's Horizon 2020 research andinnovation programme under grant agreement No. 101013425.