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The effect of the external magnetic field on the millimeter‐wave absorption of rhodium‐substituted epsilon iron oxide, ε‐Rh0.13Fe1.87O3 (1) and ε‐Rh0.19Fe1.81O3 (2) nanomagnets, is investigated. Terahertz time‐domain spectroscopy (THz‐TDS) shows that 1 and 2 display a zero‐field ferromagnetic resonance (the so‐called natural resonance) at 201 GHz with a linewidth of 20 GHz and at 210 GHz with a linewidth of 30 GHz, respectively. The ferromagnetic resonance is measured under an external magnetic field (H ex). Applying +3.5 kOe parallel to the remnant magnetization and −3.5 kOe antiparallel to the remnant magnetization shifts the resonance frequency at 201 GHz in 1 by +6 and −4 GHz and that in 2 by +4 and −4 GHz, respectively. Simulations of the ferromagnetic resonance using the Landau−Lifshitz−Gilbert model reproduce the magnetic field‐induced shifts of the resonance frequencies. The 220 GHz band millimeter wave is the highest frequency with a high transparency for “atmospheric windows” and is expected to be a carrier frequency for sixth‐generation mobile communication systems (6 G) or 7 G. This study may help realize applications for millimeter‐wave isolators, circulators, or shutters.

Non-orthogonal multiple access (NOMA) scheme, potentially enabling high spectral efficiency, is one of the key technological innovations in the 5th generation (5G) cellular networks. The massive machine type communications (mMTC) service category of 5G supports ultra-dense deployment of connected devices with low-power and low data-rate requirements, and so it naturally supports internet-of-things (IoT) communications. Also, the ambient backscatter communications (BsC) holds potential for enabling energy-constrained IoT communications due to its extremely low power requirements. This work analyzes the downlink of a NOMA-enabled cellular system bundled with symbiotic radio-based mMTC. Closed-form expressions of the outage probability for the signal-to-interference and noise ratio (SINR) and the ergodic rate are derived for the symbiotic radio backscatter device as well as the primary cellular user. Several interesting use-cases of the proposed system model are discussed for future massive IoT and cell-free networks. The theoretical results presented are validated through numerical evaluations. [ABSTRACT FROM AUTHOR]

This paper studies the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) services in a cellular network that is assisted by a reconfigurable intelligent surface (RIS). The system model consists of one base station (BS) and one RIS that is deployed to enhance the performance of both eMBB and URLLC in terms of the achievable data rate and reliability, respectively. We formulate two optimization problems, a time slot basis eMBB allocation problem and a mini-time slot basis URLLC allocation problem. The eMBB allocation problem aims at maximizing the eMBB sum rate by jointly optimizing the power allocation at the BS and the RIS phase-shift matrix while satisfying the eMBB rate constraint. On the other hand, the URLLC allocation problem is formulated as a multi-objective problem with the goal of maximizing the URLLC admitted packets and minimizing the eMBB rate loss. This is achieved by jointly optimizing the power and frequency allocations along with the RIS phase-shift matrix. In order to avoid the violation in the URLLC latency requirements, we propose a novel framework in which the RIS phase-shift matrix that enhances the URLLC reliability is proactively designed at the beginning of the time slot. For the sake of solving the URLLC allocation problem, two algorithms are proposed, namely, an optimization-based URLLC allocation algorithm and a heuristic algorithm. The simulation results show that the heuristic algorithm has a low time complexity, which makes it practical for real-time and efficient multiplexing between eMBB and URLLC traffic. In addition, using only 60 RIS elements, we observe that the proposed scheme achieves around 99.99% URLLC packets admission rate compared to 95.6% when there is no RIS, while also achieving up to 70% enhancement on the eMBB sum rate. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel dynamic bandwidth allocation (DBA) scheme for future generation passive optical networks (PON) in order to meet the beyond 5G (B5G) and sixth generation (6G) stringent requirements. Our proposed algorithm is a generalized multi-access DBA (GMA-DBA) that exploits both orthogonal and non-orthogonal multi-access (MA) resources, resulting in a radical enhancement in the network performance. The proposed GMA-DBA algorithm is modeled as an optimization problem for which a closed form solution is derived. Results show that the GMA-DBA is capable of accommodating a network throughput higher than 1 Tbps while securing a latency and jitter below 100 µs and 10 µs, respectively. It can also maintain reliability, simplicity and energy efficiency. Therefore, using a non-orthogonal MA layer seems to be inevitable to achieve the stringent performance needed for the B5G and 6G next generation systems. [ABSTRACT FROM AUTHOR]

ITU-T SG13 established a Focus Group of Network 2030 in 2018 for a two-year study period.FG NET-2030 focuses on the network requirements,scenarios and the network capabilities of the future network,and proposes the key technologies and study directions of the next study period in SG13.Focus on key technology development directions that the industry pays more attention,the network requirements and key technologies of the ITU-T Future Network Architecture Working Group for Beyond 5G and Network 2030 was tracked.The network requirements and challenges for 2030 was summarized,and the key technologies and evolution trends of deterministic networks,new IP architectures,the network-based machine learning architectures and a use case of machine learning applications in 5G network were analyzed.

Intelligent vehicular networks (IVNs) have drawn substantial interests in recent years due to its great potential in enabling diverse applications in the fifth-generation (5G) and beyond communication systems. In IVNs, vehicles are equipped with multi-functional advanced wireless sensors which are capable to collect real-time and practical environmental information. In this paper, we first provide an overview of the existing researches on IVNs for beyond 5G (B5G) communications, while emphasizing the requirements and technical approaches. To fully unleash the potential of vehicular intelligence, smart vehicles should acquire the values of some important variables of interest, e.g. traffic volume in the network. Thus, we introduce a generalized framework which formulates the acquisition of desired variables as a joint estimation and detection problem. Our framework adopts factor graph to solve problems in IVNs. This is done by collecting the observations from vehicles at road side units (RSUs) for inferring such variables and sending them back to vehicles. Nevertheless, this centralized framework critically depends on the functional reliability of the RSUs. To this end, we propose a distributed estimation framework to improve the scalability and robustness, in which vehicles can communicate wirelessly with other vehicles within the communication range. Then, we introduce different consensus operations as a realization of this proposed framework and briefly compare them in terms of implementation feasibility and convergence behavior. Three approximation schemes are further considered for reducing the required communication signaling overhead. To shed light on the proposed distributed estimation framework, we focus on two cases, i.e., target tracking and network decoding in IVNs. Through simulations, we show that the distributed algorithms can efficiently track the target and decode the broadcasted messages, while achieving the same performance of the centralized schemes. Finally, important conclusions are drawn and some challenges and open problems in this research area are outlined.

5G enables a wide variety of wireless communications applications and use cases. There are different requirements associated with the applications, use cases, channel structure, network and user. To meet all of the requirements, several new configurable parameters are defined in 5G New Radio (NR). It is possible that 6G will have even higher number of configurable parameters based on new potential conditions. In line with this trend, configurable waveform parameters are also varied and this variation will increase in 6G considering the potential future necessities. In this paper, association of users and possible configurable waveform parameters in a cell is discussed for 6G communication systems. An assignment framework of configurable waveform parameters with different types of resource allocation optimization mechanisms is proposed. Most of all, the role and usage of machine learning (ML) in this framework is described. A case study with a simulation based dataset generation methodology is also presented.

The demand for wireless connectivity has grown exponentially over the last few decades. Fifth-generation (5G) communications, with far more features than fourth-generation communications, will soon be deployed worldwide. A new paradigm of wireless communication, the sixth-generation (6G) system, with the full support of artificial intelligence, is expected to be implemented between 2027 and 2030. Beyond 5G, some fundamental issues that need to be addressed are higher system capacity, higher data rate, lower latency, higher security, and improved quality of service (QoS) compared to the 5G system. This paper presents the vision of future 6G wireless communication and its network architecture. This article describes emerging technologies such as artificial intelligence, terahertz communications, wireless optical technology, free-space optical network, blockchain, three-dimensional networking, quantum communications, unmanned aerial vehicles, cell-free communications, integration of wireless information and energy transfer, integrated sensing and communication, integrated access-backhaul networks, dynamic network slicing, holographic beamforming, backscatter communication, intelligent reflecting surface, proactive caching, and big data analytics that can assist the 6G architecture development in guaranteeing the QoS. Besides, expected applications with 6G communication requirements and possible technologies are presented. We also describe potential challenges and research directions for achieving this goal.

The continuous proliferation of applications requiring wireless connectivity will eventually result in latency and reliability requirements beyond what is achievable with current technologies. Such applications can for example include industrial control at the sensor-actuator level, intra-vehicle communication, fast closed loop control in intra-body networks and intra-avionics communication. In this article, we present the design of short range Wireless Isochronous Real Time (WIRT) in-X subnetworks aimed at life-critical applications with communication cycles shorter than 0.1 ms and outage probability below 10-6. Such targets are clearly beyond what is supported by the 5th Generation (5G) radio technology, and position WIRT as a possible 6th Generation (6G) system. WIRT subnetworks are envisioned to be deployed for instance in industrial production modules, robots, or inside vehicles. We identify technology components as well as spectrum bands for WIRT subnetworks and present major design aspects including frame structure and transmission techniques. The performance evaluation considering a dense scenario with up to 2 devices per m2 reveal that a multi-GHz spectrum may be required for ensuring high spatial service availability. The possibility of running WIRT as an ultra-wideband underlay system in the centimeter-wave spectrum region is also discussed. Aspects related to design of techniques for the control plane as well as enhancements to the presented design is the focus of our ongoing research.

Energy efficiency is one of the key performance indicators in 5G New Radio (NR) networks targeted to support diversified use cases including enhanced mobile broadband (eMBB), massive machine type communications (mMTC) and ultra-reliable and low latency communications (URLLC). Trade-offs have to be carefully considered between energy efficiency and other performance aspects such as latency, throughput, connection densities and reliability. Energy efficiency is important for both user equipment (UE) side and base station side. On UE side, UE battery life has great impact on user experience. It is challenging to improve UE experience in other performance aspects without affecting battery life of 5G handsets. On the base station side, efficient network implementation is critical in both environmental and operation cost standpoints. To adapt different requirements and trade-offs, the 5G NR standard is designed to have great flexibility on network operation modes. This paper provides an overview on power saving techniques supported by 5G NR standards according to the current 5G standardization progress. It provides the 5G evolution path of the power saving techniques from the first release of 5G standard to the future beyond-5G releases. In addition to the existing standardized techniques, some major development trends of green communication and the future potential enhancements expected in the beyond-5G standards are discussed.

Tactile Internet (TI) is envisioned to create a paradigm shift from the content-oriented communications to steer/control-based communications by enabling real-time transmission of haptic information (i.e., touch, actuation, motion, vibration, surface texture) over Internet in addition to the conventional audiovisual and data traffics. This emerging TI technology, also considered as the next evolution phase of Internet of Things (IoT), is expected to create numerous opportunities for technology markets in a wide variety of applications ranging from teleoperation systems and Augmented/Virtual Reality (AR/VR) to automotive safety and eHealthcare towards addressing the complex problems of human society. However, the realization of TI over wireless media in the upcoming Fifth Generation (5G) and beyond networks creates various non-conventional communication challenges and stringent requirements in terms of ultra-low latency, ultra-high reliability, high data-rate connectivity, resource allocation, multiple access and quality-latency-rate tradeoff. To this end, this paper aims to provide a holistic view on wireless TI along with a thorough review of the existing state-of-the-art, to identify and analyze the involved technical issues, to highlight potential solutions and to propose future research directions. First, starting with the vision of TI and recent advances and a review of related survey/overview articles, we present a generalized framework for wireless TI in the Beyond 5G Era including a TI architecture, the main technical requirements, the key application areas and potential enabling technologies. Subsequently, we provide a comprehensive review of the existing TI works by broadly categorizing them into three main paradigms; namely, haptic communications, wireless AR/VR, and autonomous, intelligent and cooperative mobility systems. Next, potential enabling technologies across physical/Medium Access Control (MAC) and network layers are identified and discussed in detail. Also, security and privacy issues of TI applications are discussed along with some promising enablers. Finally, we present some open research challenges and recommend promising future research directions.

Massive MIMO is one of the promising techniques to improve spectral efficiency and network performance for reaching its targeted multi-gigabit throughput in 5G systems. For 5G New Radio (NR) systems, one of the key differences compared to 4G systems is the utilization of high frequency millimeter wave (mmWave) bands in addition to sub-6GHz bands. To keep the complexity and implementation cost low, hybrid analog-digital beam-forming with large-scale antenna array has become a common design approach to address the issue of higher propagation loss as well as to improve spectral efficiency in mmWave communication in 5G NR. The 5G NR standard is designed to adapt to different beam-forming architecture and deployment scenarios. This paper provides the overview on beam management procedure according to the current 5G standardization progress. We discuss some major challenges of millimeter-wave communications encountered in the current 5G NR standard and present some expected enhancements considered for the future beyond-5G standard.

This paper provides a survey of resource allocation for network slicing. We focus on two classes of existing solutions: (i) reservation-based approaches, which allocate resources on a reservation basis, and (ii) share-based approaches, which allocate resources based on static overall shares associated to individual slices. We identify the requirements that a slice-based resource allocation mechanism should satisfy, and evaluate the performance of both approaches against these requirements. Our analysis reveals that reservation-based approaches provide a better level of isolation as well as stricter guarantees, by enabling tenants to explicitly reserve resources, but one must pay a price in terms of efficiency unless reservations can be updated very dynamically; in particular, efficiency falls below 50% when reservations are performed over long timescales. We provide further comparisons in terms of customizability, complexity, privacy and cost predictability, and discuss which approach might be more suitable depending on the network slices' characteristics. We also describe the additional mechanisms required to implement the desired resource allocations while meeting the latency and reliability requirements of the different slice types, and outline some issues for future work.

Future generations of wireless networks are expected to provide new services with an unprecedented level of diverse and stringent requirements. Fog Radio Access Network (FRAN) and Non-Orthogonal Multiple Access (NOMA) have emerged as complimentary enablers to meet such requirements. On the one hand, FRAN architecture is designed to reduce the delay caused by the fronthaul link by pushing control and storage to the network edge. On the other hand, in addition to increasing the spectral and energy efficiency and the number of connected devices, NOMA has the potential to improve network latency. This paper overviews the joint benefits of enabling NOMA schemes in an FRAN architecture, by means of examining the applicability and adequateness of the NOMA-based FRAN features in achieving specific objectives of next generation of mobile networks, mainly those related to enhanced mobile broadband (eMBB), massive machine type communications (mMTC), and ultra-reliable low latency communication (URLLC). The paper further depicts the challenges and future research directions that must be addressed in order to meet such opportunities.

Massive machine-type communication (mMTC) and ultra-reliable and low-latency communication (URLLC) are two key service types in the fifth-generation (5G) communication systems, pursuing scalability and reliability with low-latency, respectively. These two extreme services are envisaged to agglomerate together into critical mMTC shortly with emerging use cases (e.g., wide-area disaster monitoring, wireless factory automation), creating new challenges to designing wireless systems beyond 5G. While conventional network slicing is effective in supporting a simple mixture of mMTC and URLLC, it is difficult to simultaneously guarantee the reliability, latency, and scalability requirements of critical mMTC (e.g., ¡ 4ms latency, 106 devices/km2 for factory automation) with limited radio resources. Furthermore, recently proposed solutions to scalable URLLC (e.g., machine learning aided URLLC for driverless vehicles) are ill-suited to critical mMTC whose machine type users have minimal energy budget and computing capability that should be (tightly) optimized for given tasks. To this end, our paper aims to characterize promising use cases of critical mMTC and search for their possible solutions. To this end, we first review the state-of-the-art (SOTA) technologies for separate mMTC and URLLC services and then identify key challenges from conflicting SOTA requirements, followed by potential approaches to prospective critical mMTC solutions at different layers.

The capacity and coverage requirements for 5th generation (5G) and beyond wireless connectivity will be significantly different from the predecessor networks. To meet these requirements, the anticipated deployment cost in the United Kingdom (UK) is predicted to be between £30bn and £50bn, whereas the current annual capital expenditure (CapEX) of the mobile network operators (MNOs) is £2.5bn. This prospect has vastly impacted and has become one of the major delaying factors for building the 5G physical infrastructure, whereas other areas of 5G are progressing at their speed. Due to the expensive and complicated nature of the network infrastructure and spectrum, the second-tier operators, widely known as mobile virtual network operators (MVNO), are entirely dependent on the MNOs. In this paper, an extensive study is conducted to explore the possibilities of reducing the 5G deployment cost and developing viable business models. In this regard, the potential of infrastructure, data, and spectrum sharing is thoroughly investigated. It is established that the use of existing public infrastructure (e.g., streetlights, telephone poles, etc.) has a potential to reduce the anticipated cost by about 40% to 60%. This paper also reviews the recent Ofcom initiatives to release location-based licenses of the 5G-compatible radio spectrum. Our study suggests that simplification of infrastructure and spectrum will encourage the exponential growth of scenario-specific cellular networks (e.g., private networks, community networks, micro-operators) and will potentially disrupt the current business models of telecommunication business stakeholders – specifically MNOs and TowerCos. Furthermore, the anticipated dense device connectivity in 5G will increase the resolution of traditional and non-traditional data availability significantly. This will encourage extensive data harvesting as a business opportunity and function within small and medium-sized enterprises (SMEs) as well as large social networks. Consequently, the rise of new infrastructures and spectrum stakeholders is anticipated. This will fuel the development of a 5G data exchange ecosystem where data transactions are deemed to be high-value business commodities. The privacy and security of such data, as well as definitions of the associated revenue models and ownership, are challenging areas – and these have yet to emerge and mature fully. In this direction, this paper proposes the development of a unified data hub with layered structured privacy and security along with blockchain and encrypted off-chain based ownership/royalty tracking. Also, a data economy-oriented business model is proposed. The study found that with the potential commodification of data and data transactions along with the low-cost physical infrastructure and spectrum, the 5G network will introduce significant disruption in the Telco business ecosystem.

As the technical specifications of the 5th Generation (5G) wireless communication standard are being wrapped up, there are growing efforts amongst researchers, industrialists, and standardisation bodies on the enabling technologies of a 6G standard or the so-called Beyond 5G (B5G) one. Although the 5G standard has presented several benefits, there are still some limitations within it. Such limitations have motivated the setting up of study groups to determine suitable technologies that should operate in the year 2030 and beyond, i.e., after 5G. Consequently, this Special Issue of Future Internet concerning what possibilities lie ahead for a 6G wireless network includes four high-quality research papers (three of which are review papers with over 412 referred sources and one regular research). This editorial piece summarises the major contributions of the articles and the Special Issue, outlining future directions for new research.

Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance. [ABSTRACT FROM AUTHOR]

The Fisher–Snedecor (F-S) F distribution has recently been introduced as a tractable turbulence-induced (TI) fading model that fits well with the experimental data. This paper provides a performance evaluation of a free-space optical (FSO) re-configurable intelligent surface (RIS)-assisted communications (ACs) link over the F-S F TI fading channels, assuming the intensity modulation–direct detection (IM–DD) technique. In particular, novel and closed-form (C-F) analytical expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) in terms of Gaussian hyper-geometric functions are efficiently derived. Capitalizing on the obtained results, novel C-F analytical expressions for the moment generating function ( M M G F ), outage probability (OP), average bit error rate (BER) and ergodic channel capacity (C γ) of the FSO RIS-ACs system over the F-S F TI fading channels are provided and numerically evaluated under the various TI fading severity conditions. Furthermore, the second-order (S-O) statistical expressions for the level crossing rate (LCR) and average fade duration (AFD) are obtained and thoroughly examined for various FSO RIS-ACs system model parameters. [ABSTRACT FROM AUTHOR]

In this work, we propose a hybrid multiple access (HMA) scheme that combines heterogeneous non‐orthogonal multiple access (H‐NOMA) with heterogeneous orthogonal multiple access (H‐OMA), aiming at increasing the sum‐rate of 5G and beyond (B5G) networks. More specifically, the HMA strategy is applied in the network slicing of enhanced mobile broadband (eMBB) and grant‐free ultra‐reliable low‐latency communications (URLLC), two important use cases in the scope of B5G. By considering that the max‐matching diversity (MMD) algorithm is used to allocate channels to eMBB users, we show that the proposed HMA scheme can achieve considerable gains when compared to the standalone MMD‐aided H‐OMA and H‐NOMA schemes. [ABSTRACT FROM AUTHOR]

In uplink (UL) grant-free sparse code multiple access (SCMA) systems, unlike the conventional contentionbased transmission, users' activities should be known before data decoding due to sporadic transmission in massive machine-type communication (mMTC). Since compressed sensing (CS) is the theory of sparse signal reconstruction with fewer samples, this theory is a good solution to detect active users. In this paper, we propose the dynamic and sparsity adaptive compressed sensing (DSACS) based active user detection (AUD) and channel estimation (CE) of UL grant-free SCMA. Unlike most of the CS-based methods, sparsity knowledge or potential active user list is not needed in the proposed algorithm, which is already not known in the practical systems. The proposed algorithm adopts a stagewise approach to expand the set of accurate active users for adaptively achieve the sparsity level. It uses the temporal correlation of users' activity to improve performance and reduce complexity. Then, false detected users are eliminated with joint message passing algorithm (JMPA), and channel gains of the accurate active users are estimated again in CE with feedback. The simulation results show that the proposed method without sparsity knowledge is capable of achieving detection in various scenarios in case of sporadic transmission in mMTC. [ABSTRACT FROM AUTHOR]

As data rates demands are exploding, 5G will soon rely on mmWaves that offer much higher bandwidths. Yet at these frequencies, attenuation and diffraction of waves require point to point communications with beamforming base stations that are complex and power greedy. Furthermore, since any obstacle at these frequencies completely blocks the waves, the networks must be extremely dense, resulting in dramatic increase of its cost. One way to avoid this problem is to redirect beams coming from base stations at many locations with Reconfigurable Intelligent Surfaces, in order to increase their coverage even in cluttered environments. Here we describe and experimentally demonstrate a binary tunable metasurface operating at 28 GHz, based on standard PCB and off the shelves PIN diodes. We show that it can be used as a Reconfigurable Intelligent Surface that beamforms an incoming plane wave at a given angle to one or several outgoing plane waves at angles reconfigurable in real time. Most importantly we use this 20 cm × 20 cm reconfigurable Intelligent Surface alongside software defined radio and up/down converters at 28 GHz, and demonstrate a wireless link between an emitter and a receiver 10 m away, in a non-line-of-sight configuration, hence proving the validity of the approach.

Fifth-generation (5G) wireless technology promises to be the critical enabler of use cases far beyond smartphones and other connected devices. This next-generation 5G wireless standard represents the changing face of connectivity by enabling elevated levels of automation through continuous optimization of several Key Performance Indicators (KPIs) such as latency, reliability, connection density, and energy efficiency. Mobile Network Operators (MNOs) must promote and implement innovative technologies and solutions to reduce network energy consumption while delivering high-speed and low-latency services to deploy energy-efficient 5G networks with a reduced carbon footprint. This research evaluates an energy-saving method using data-driven learning through load estimation for Beyond 5G (B5G) networks. The proposed ‘ECO6G’ model utilizes a supervised Machine Learning (ML) approach for forecasting traffic load and uses the estimated load to evaluate the energy efficiency and OPEX savings. The simulation results demonstrate a comparative analysis between the traditional time-series forecasting methods and the proposed ML model that utilizes learned parameters. Our ECO6G dataset is captured from measurements on a real-world operational 5G base station (BS). We showcase simulations using our ECO6G model for a given dataset and demonstrate that the proposed ECO6G model is accurate within $4.3 million over 100,000 BSs over 5 years compared to three other models that would increase OPEX cost from $370 million to $1.87 billion during varying network load scenarios against other data-driven and statistical learning models.

We propose a novel vision to trade and allocate wireless spectrum in 6G communication networks inspired by the concept of the sharing economy. We argue that such an approach will help ease the surge in demands for wireless spectrum that will characterise the 6G world. We also introduce HODNET (Heterogeneous on Demand NETwork resource negotiation), an open platform that is able to realise this new spectrum-sharing model. To demonstrate the benefits of spectrum trading and allocation in this new paradigm, we considered the use-case of massive Internet of Things (IoT) on a local scale. We simulated a large IoT deployment and evaluated the spectral efficiency of the system when managed using HODNET compared with a standard 5G deployment. Our experiments show that HODNET can indeed offer better allocation, based on our spectrum sharing model, of spectrum resources compared with standard allocation approaches.

To deal with recent increasing mobile traffic, ultra-broadband communication with millimeter-wave (mmWave) has been regarded as a key technology for 5G cellular networks. In a previous study, a mmWave heterogeneous network was composed of several mmWave small cells overlaid on the coverage of a macro cell. However, as seen from the optical fiber penetration rate worldwide, it is difficult to say that backhaul with Gbps order is available everywhere. In the case of using mmWave access under a limited backhaul capacity, it becomes a bottleneck at the backhaul; thus, mmWave access cannot fully demonstrate its potential. On the other hand, the concept of multi-access edge computing (MEC) has been proposed to decrease the response latency compared to cloud computing by deploying storage and computation resources to the user side of mobile networks. This paper introduces MEC into mmWave heterogeneous networks and proposes a content prefetching algorithm to resolve such backhaul issues. Context information, such as the destination, mobility, and traffic tendency, is shared through the macro cell to the prefetch application and data that the users request. Prefetched data is stored in the MEC and then transmitted via mmWave without a backhaul bottleneck. The effectiveness is verified through computer simulations where we implement realistic user mobility as well as traffic and backhauling models. The results show that the proposed framework achieved 95% system capacity even under the constraint of a 1 Gbps backhaul link.

Given the increasing demand for high data-rate, high-performance wireless communications services, the demand on the radio access networks (RAN) has been increasing significantly, where optical fiber has been widely used both for the backhaul and fronthaul. Additionally, advances in signal processing such as multiple-input multiple-output (MIMO) techniques, have improved the performance as well as transmission rate of communications networks. Beamforming has been used as an efficient MIMO technique for providing a signal to noise ratio (SNR) gain as well as reducing the multi-user interference. However, beamforming requires the employment of phase-shifters, which suffers from reduced phase resolutions, degraded noise figures as well as beam-squinting in addition to the implementation challenges. Hence, in this paper we employ an analogue radio over fiber (A-RoF) aided architecture for supporting the requirements of the current and future mobile networks, where we design a photonics aided beamforming technique in order to eliminate the bulky electronic phase-shifters and the beam-squinting effect, while also providing a low-cost RAN solution. Additionally, this photonics aided beamforming is combined with a reconfigurable multi-user MIMO technique, where users can communicate with one or multiple remote radio heads (RRHs), while employing stand-alone beamforming, beamforming combined with diversity or with multiplexing depending on the available resources and the user channel information as well as the quality of service requirements.

Summary: To design new revolutionary wireless communication systems, orthogonal frequency‐division multiplexing (OFDM)‐based massive multiuser (MU) multiple‐input multiple‐output (MIMO) has been shown to be the most promising technology to significantly enhance the spectral, energy, and hardware efficiencies. However, massive MU‐MIMO‐OFDM transmitters exhibit signal with high peak‐to‐average power ratio (PAPR). Accordingly, the nonlinearity of the radio frequency (RF) power amplifier (PA), which causes the most severe hardware impairment, is expected to be a low‐cost and energy‐efficient component to enable cost‐ and energy‐efficient massive MU‐MIMO‐OFDM BS deployments, generating harmful in‐band distortion and out‐of‐band (OOB) emissions. In this paper, we develop a PAPR‐aware downlink transmission scheme in an OFDM‐based large‐scale MU‐MIMO. Linear precoding of data and peak‐canceling signals (PCSs) are employed to reduce the PAPRs of the transmitted signals by exploiting the excess degrees of freedom (DoFs) provided by equipping the base station (BS) by a large number of transmit antennas. Specifically, we design PCSs to be added to the frequency‐domain precoded data signals, with the goal of reducing the PAPRs of their time‐domain counterpart signals. Most importantly, the added PCSs have to lie in the null spaces of their associated MIMO channel matrices such that they do not cause any MU interference (MUI) and OOB radiation. In this regard, an efficient algorithm is developed, which is based on different data and PCSs precoders, and the corresponding achievable PAPR reduction and bit error rate (BER) performance are analyzed. Moreover, to optimize a tradeoff between performance and complexity, linear precoders based on matrix polynomials (M‐POLYs) and gradient‐iterative approaches are studied for both data and PCSs precoding. Simulation results reveal that these latter provide similar performance as the regularized zero‐forcing (RZF) and orthogonal projection null space (OPNS)‐based data and PCSs precoders, while they need much lower computational complexity. The substantial PAPR reduction provided by the proposed algorithm offers interesting insights for the design of energy‐efficient massive MU‐MIMO‐OFDM systems. [ABSTRACT FROM AUTHOR]

Routing is fundamental in any wireless network for path selection, which provides the most effective way that legitimizes the data to be transmitted from a source to a destination device. In gigantic network demand nowadays, routing is pertinent to ensure fast and reliable data transfer. Ineffective routing may cause route flapping and degrade the overall Quality of Service (QoS). Meanwhile, Device-to-Device communications (D2D) is a technology that allows the devices to be connected without or partial involvement of the conventional cellular network. With these natures of qualities, D2D communication provides a reliable propitious medium that caters for the needs of many different telecommunications scenarios. The interconnectivity of multiple devices creates the Internet of Things (IoT), which will be an essential insistent in future technologies. With the dynamic nature of D2D technology, the routing approach act as a principal architecture that essential to be implemented in every niche D2D aspect. If wrong routing decisions are made in D2D communication, the QoS performance would be worse than the conventional cellular network. This paper present the state of the art of fundamentals, recent progress, current challenges, future directions, and potential routing applications for D2D and Beyond IoT 5G Networks. This review will also act as a guide and reference for future researchers and scientists to explore and integrate the routing technique in D2D communication and Beyond IoT 5G Networks. [ABSTRACT FROM AUTHOR]

This brief presents a broadband D-band down-conversion mixer in a cost efficient 130nm SiGe BiCMOS technology with a ft/fmax of 250/370GHz from Infineon Technologies AG. The proposed mixer covers the entire D-band with a 32dB peak conversion gain and a 3dB bandwidth of 35GHz at a measured noise figure between 9.5 and 12dB in the specified band while consuming only 65mW DC power. To achieve large RF and IF bandwidths and a low noise figure, the mixer design is based on a low-biased switching quad, which is loaded with a modified Cherry-Hooper transimpedance amplifier. The results, which are verified by measurements, are based on a detailed analysis of the transistor characteristics, broadband matching networks and an appropriate layout parasitic extraction. All interfaces to the circuit are designed single-ended for a dense chip-to-package transition. For this purpose, high performance Marchand baluns are used at RF- and LO-port, respectively. With a moderate noise figure and a low power consumption, the presented circuit meets the requirements for beyond 5G systems. [ABSTRACT FROM AUTHOR]

The design of green cellular networking according to the traffic arrivals has the capability to reduce the overall energy consumption to a cluster in a cost-effective way. The cell zooming approach has appealed much attention that adaptively offloads the BS load demands adjusting the transmit power based on the traffic intensity and green energy availability. Besides, the researchers are focused on implementing renewable energy resources, which are considered the most attractive practices in designing energy-efficient wireless networks over the long term in a cost-efficient way in the existing infrastructure. The utilization of available solar can be adapted to acquire cost-effective and reliable power supply to the BSs, especially that sunlight is free, available everywhere, and a good alternative energy option for the remote areas. Nevertheless, planning a photovoltaic scheme necessitates viability assessment to avoid poor power supply, particularly for BSs. Therefore, cellular operators need to consider both technical and economic factors before the implementation of solar-powered BSs. This paper proposed the usercentric cell zooming policy of solar-powered cellular base stations taking into account the optimal technical criteria obtained by the HOMER software tool. The results have shown that the proposed system can provide operational expenditure (OPEX) savings of up to 47%. In addition, the efficient allocation of resource blocks (RBs) under the cell zooming technique attain remarkable energy-saving performance yielding up to 27%. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the use of reconfigurable intelligent surfaces (RIS) to allow multiple user pairs to communicate simultaneously over the same channel. We propose a Riemannian manifold optimization approach to solve the problem of configuring the RIS passive reflection coefficients to minimize the total interference under constant modulus constraints. We compare the proposed approach to the widely-used semidefinite relaxation approach (SDR) for dealing with the constant modulus constraints. We investigate, using extensive numerical simulations, the effects of various system parameters, such as the number of users, the number of RIS elements, and the fraction of power received through the RIS. Our results demonstrate that RISs can substantially minimize interference allowing multiple user pairs to simultaneously communicate over the same channel and that the proposed approach vastly outperforms the semidefinite relaxation-based approach, which fails to find satisfactory solutions. [ABSTRACT FROM AUTHOR]

Wireless communications in the low terahertz band (0.1 THz–1 THz) is a promising candidate to enable ultra-high-rate vehicular networks beyond 5G. The successful design and adoption of such systems require a deep understanding of the low THz channel specifics in complex vehicular scenarios. In this paper, a comprehensive measurement campaign is reported with the aim of analyzing the wave propagation at 300 GHz in typical vehicular deployments. Following a modular approach, the generic vehicular scenario is decomposed into basic propagation setups that are further analyzed in detail. The obtained measurement data are then applied to derive the mathematical approximations that characterize the low THz band channel properties for each scenario. Finally, the combination of measurement and modeling results is used to identify the critical propagation effects that has to be accounted for in the applied studies. The presented approach, raw and processed data, as well as the contributed analysis, serve as building blocks for future analytical and simulation tools to model prospective vehicular communication systems in the low THz band. [ABSTRACT FROM AUTHOR]

In this paper, we address a multiple-input multiple-output (MIMO) communication system based on generalized spatial modulation (GSM) and dual-polarized (DP) antennas in sub-TeraHertz (sub-THz) bands to improve the Spectral Efficiency (SE) while reducing the spatial correlation effect and the space occupancy. Moreover, the joint Maximum Likelihood (ML) detector and a Modified Ordered Block Minimum Mean-Squared Error (MOB-MMSE) detector algorithm are proposed to detect jointly the complex symbols and the virtual bits conveyed by the activated polarization and the transmit antenna combination index. MOB-MMSE can achieve near-ML performance with low complexity. The performance of DP-GSM system over correlated Rayleigh/Rician fading and indoor sub-THz channels is studied. Provided results show that DP-GSM system is robust to the spatial correlation effects under Rician fading channel. In addition, an average bit-error probability (ABEP) upper bounding is derived and analyzed for the DP-GSM system over correlated Rayleigh/Rician fading channels. Since the sub-THz band suffers from many technological limitations and severe RF-impairments such as low transmit output power and important phase noise (PN), the DP-GSM system is studied by considering the sub-THz impairments. Moreover, the Dual Polarized Spatial Multiplexing (DP-SMX) and the Uni-Polarized GSM (UP-GSM) are compared with the DP-GSM system. The results reveal that DP-GSM with low order modulation schemes as QPSK outperforms the UP-GSM. Besides, DP-GSM and DP-SMX provide a good performance up to medium PN, which is interesting for sub-THz bands, but DP-GSM can reduce the transceiver cost by using a lower number of RF chains when the used transmitter architecture is based on RF-switching. [ABSTRACT FROM AUTHOR]

The highly anticipated 5G network is projected to be introduced in 2020. 5G stakeholders are unanimous that densification of mobile networks is the way forward. The densification will be realized by means of small cell technology, and it is capable of providing coverage with a high data capacity. The EU-funded H2020-MSCA project “SECRET” introduced covering the urban landscape with mobile small cells, since these take advantages of the dynamic network topology and optimizes network services in a cost-effective fashion. By taking advantage of the device-to-device communications technology, large amounts of data can be transmitted over multiple hops and, therefore, offload the general network. However, this introduction of mobile small cells presents various security and privacy challenges. Cryptographic security solutions are capable of solving these as long as they are supported by a key management scheme. It is assumed that the network infrastructure and mobile devices from network users are unable to act as a centralized trust anchor since these are vulnerable targets to malicious attacks. Security must, therefore, be guaranteed by means of a key management scheme that decentralizes trust. Therefore, this paper surveys the state-of-the-art key management schemes proposed for similar network architectures (e.g., mobile ad hoc networks and ad hoc device-to-device networks) that decentralize trust. Furthermore, these key management schemes are evaluated for adaptability in a network of mobile small cells.

The Network Slice Selection Function (NSSF) in heterogeneous technology environments is a complex problem, which still does not have a fully acceptable solution. Thus, the implementation of new network selection strategies represents an important issue in development, mainly due to the growing demand for applications and scenarios involving 5G and future networks. This work presents an integrated solution for the NSSF problem, called the Network Slice Selection Function Decision-Aid Framework (NSSF DAF), which consists of a distributed solution in which a part is executed on the user’s equipment (for example, smartphones, Unmanned Aerial Vehicles, IoT brokers) functioning as a transparent service, and another at the Edge of the operator or service provider. It requires a low consumption of computing resources from mobile devices and offers complete independence from the network operator. For this purpose, protocols and software tools are used to classify slices, employing the following four multicriteria methods to aid decision making: VIKOR (Visekriterijumska Optimizacija i Kompromisno Resenje), COPRAS (Complex Proportional Assessment), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Promethee II (Preference Ranking Organization Method for Enrichment Evaluations). The general objective is to verify the similarity among these methods and applications to the slice classification and selection process, considering a specific scenario in the framework. It also uses machine learning through the K-means clustering algorithm, adopting a hybrid solution in the implementation and operation of the NSSF service in multi-domain slicing environments of heterogeneous mobile networks. Testbeds were conducted to validate the proposed framework, mapping the adequate quality of service requirements. The results indicate a real possibility of offering a complete solution to the NSSF problem that can be implemented in Edge, in Core, or even in the 5G Radio Base Station itself, without the incremental computational cost of the end user’s equipment, allowing for an adequate quality of experience.

The recent upsurge of smart cities’ applications and their building blocks in terms of the Internet of Things (IoT), Artificial Intelligence (AI), federated and distributed learning, big data analytics, blockchain, and edge-cloud computing has urged the design of the upcoming 6G network generation, due to their stringent requirements in terms of the quality of services (QoS), availability, and dependability to satisfy a Service-Level-Agreement (SLA) for the end users. Industries and academia have started to design 6G networks and propose the use of AI in its protocols and operations. Published papers on the topic discuss either the requirements of applications via a top-down approach or the network requirements in terms of agility, performance, and energy saving using a down-top perspective. In contrast, this paper adopts a holistic outlook, considering the applications, the middleware, the underlying technologies, and the 6G network systems towards an intelligent and integrated computing, communication, coordination, and decision-making ecosystem. In particular, we discuss the temporal evolution of the wireless network generations’ development to capture the applications, middleware, and technological requirements that led to the development of the network generation systems from 1G to AI-enabled 6G and its employed self-learning models. We provide a taxonomy of the technology-enabled smart city applications’ systems and present insights into those systems for the realization of a trustworthy and efficient smart city ecosystem. We propose future research directions in 6G networks for smart city applications.

The emergence of 5G-IoT opens up unprecedented connectivity possibilities for new service use cases and players. Multi-access edge computing (MEC) is a crucial technology and enabler for Beyond 5G, supporting next-generation communications with service guarantees (e.g., ultra-low latency, high security) from an end-to-end (E2E) perspective. On the other hand, one notable advance is the platform that supports virtualization from RAN to applications. Deploying Radio Access Networks (RAN) and MEC, including third-party applications on virtualization platforms, and renting other equipment from legacy telecom operators will make it easier for new telecom operators, called Private/Local Telecom Operators, to join the ecosystem. Our preliminary studies have discussed the ecosystem for private and local telecom operators regarding business potential and revenue and provided numerical results. What remains is how Private/Local Telecom Operators can manage and deploy their MEC applications. In this paper, we designed the architecture for fully virtualized MEC 5G cellular networks with local use cases (e.g., stadiums, campuses). We propose an MEC/Cloud Orchestrator implementation for intelligent deployment selection. In addition, we provide implementation schemes in several cases held by either existing cloud owners or private and local operators. In order to verify the proposal’s feasibility, we designed the system level in E2E and constructed a Beyond 5G testbed at the Ōokayama Campus of the Tokyo Institute of Technology. Through proof-of-concept in the outdoor field, the proposed system’s feasibility is verified by E2E performance evaluation. The verification results prove that the proposed approach can reduce latency and provide a more stable throughput than conventional cloud services.

Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication systems and beyond. By imbuing intelligence into the network edge, edge nodes can proactively carry out decision-making and, thereby, react to local environmental changes and disturbances while experiencing zero communication latency. To achieve this goal, it is essential to cater for high ML inference accuracy at scale under the time-varying channel and network dynamics, by continuously exchanging fresh data and ML model updates in a distributed way. Taming this new kind of data traffic boils down to improving the communication efficiency of distributed learning by optimizing communication payload types, transmission techniques, and scheduling, as well as ML architectures, algorithms, and data processing methods. To this end, this article aims to provide a holistic overview of relevant communication and ML principles and, thereby, present communication-efficient and distributed learning frameworks with selected use cases. [ABSTRACT FROM AUTHOR]

Extending the frequency range of the Walfisch‐Bertoni (W‐B) model, which is a representative theory‐based model, was investigated. To extend the W‐B model, three changes to the original W‐B model were made: (i) remodeling over rooftop path, (ii) introducing a slant path, and (iii) modeling of multiple reflections between buildings. To validate the proposed model, propagation loss predicted by the model was compared with measurement results. Comparison with the measurement results shows that root mean square errors of propagation loss predicted by the proposed model are 5.8 dB for radiowave frequency of 2.2 GHz, 6.6 dB for 5.2 GHz, and 3.3 dB for 26.4 GHz. It is therefore concluded that the proposed model has can achieve high estimation accuracy for all measured frequency bands. Key Points: Extending the frequency range of the Walfisch‐Bertoni (W‐B) model, which is a representative theoretical model, was investigatedTo extend the W‐B model, three changes to the original W‐B model were madeTo validate the proposed model, propagation loss predicted by the model was compared with measurement data [ABSTRACT FROM AUTHOR]

As the deployment of 5G mobile radio networks gains momentum across the globe, the wireless research community is already planning the successor of 5G. In this paper, we highlight the shortcomings of 5G in meeting the needs of more data-intensive, low-latency, and ultra-high-reliability applications. We then discuss the salient characteristics of the 6G network following a hierarchical approach including the social, economic, and technological aspects. We also discuss some of the key technologies expected to support the move towards 6G. Finally, we quantify and summarize the research work related to beyond 5G and 6G networks through an extensive search of publications and research groups and present a possible timeline for 6G activities.

5G and its evolution towards 6G is unlocking new use cases that will require the reconsideration of the existing network architectures and its operation. As the network will be required to support new service types and radio protocol splits, the traditional physical point to point connections will need to be replaced with a transport network up to the antenna site to guarantee low latency services and high bandwidth. Optical based transport is a key enabler to realize such a convergent network, where the traditional fixed infrastructure in use for mobile services and mobile infrastructure should also support enterprises services. The Software Defined Network (SDN) and Network Function Virtualization (NFV) technology plays a key role to evolve towards digitalization. It allows to simplify the creation of new services and to implement a real decoupling between the infrastructure and the network functions that run virtually, on generic processing units located everywhere in the network. Supporting automation is a key requirement that traditional optical technology is not able to meet. In this paper the reference scenarios for the access network are presented with the analysis of their requirements and the enabling optical solutions based on integrated silicon photonics. [ABSTRACT FROM AUTHOR]

In this study, the performance of hexagonal quadrature amplitude modulation (HQAM) for a dual-branch selection combining (SC) receiver for beyond fifth-generation (B5G) is analyzed in detail. For general applicability, the links are modeled with η-μ fading channels. In this context, analytical expressions of error probability (EP) are derived in terms of the Chernoff, Chiani, Prony (2 and 3 terms), and Trapezoidal approximations for Gaussian Q-function. For the high signal to noise ratio (SNR) analysis, asymptotic EP expression is also derived by using the Chernoff approximation. Further, for the comparison, the analytical EP expressions with rectangular QAM and quadrature phase-shift keying modulation schemes are obtained by using the Chiani approximation. Moreover, a comprehensive work of various modulation schemes is presented and the effects of fading parameters, type of Gaussian Q-function approximations, and average SNR values of first and second links are highlighted on the EP performance. Finally, to show the accuracy of the proposed analytical derivations, some results for the exact simulations and numerical results are demonstrated. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) vehicular channels are highly dynamic, and the communication link needs to be reconfigured frequently. In this work, we propose to use a passive radar receiver at the roadside unit to reduce the training overhead of establishing an mmWave communication link. Specifically, the passive radar will tap the transmissions from the automotive radars of the vehicles on the road. The spatial covariance of the received radar signals will be estimated and used to establish the communication link. We propose a simplified radar receiver that does not require the transmitted waveform as a reference. To leverage the radar information for beamforming, the radar azimuth power spectrum (APS) and the communication APS should be similar. We outline a radar covariance correction strategy to increase the similarity between the radar and communication APS. We also propose a metric to compare the similarity of the radar and communication APS that has a connection with the achievable rate. We present simulation results based on ray-tracing data. The results show that: (i) covariance correction improves the similarity of radar and communication APS, and (ii) the radar-assisted strategy significantly reduces the training overhead, being particularly useful in non-line-of-sight scenarios. [ABSTRACT FROM AUTHOR]

Ever since the introduction of fifth generation (5G) mobile communications, the mobile telecommunications industry has been debating whether 5G is an “evolution” or “revolution” from the previous legacy mobile networks, but now that 5G has been commercially available for the past few years, the research direction has recently shifted towards the upcoming generation of mobile communication system, known as the sixth generation (6G), which is expected to drastically provide significant and evolutionary, if not revolutionary, improvements in mobile networks. The promise of extremely high data rates (in terabits), artificial intelligence (AI), ultra-low latency, near-zero/low energy, and immense connected devices is expected to enhance the connectivity, sustainability, and trustworthiness and provide some new services, such as truly immersive “extended reality” (XR), high-fidelity mobile hologram, and a new generation of entertainment. Sixth generation and its vision are still under research and open for developers and researchers to establish and develop their directions to realize future 6G technology, which is expected to be ready as early as 2028. This paper reviews 6G mobile technology, including its vision, requirements, enabling technologies, and challenges. Meanwhile, a total of 11 communication technologies, including terahertz (THz) communication, visible light communication (VLC), multiple access, coding, cell-free massive multiple-input multiple-output (CF-mMIMO) zero-energy interface, intelligent reflecting surface (IRS), and infusion of AI/machine learning (ML) in wireless transmission techniques, are presented. Moreover, this paper compares 5G and 6G in terms of services, key technologies, and enabling communications techniques. Finally, it discusses the crucial future directions and technology developments in 6G.

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The future evolution of wireless networks, throughout the 5G era and beyond, will require the expansion and augmentation of millimetre-wave systems for both terrestrial and satellite communications. Photonic technologies offer a cost efficient and high bandwidth platform for millimetre-wave carrier generation and distribution, but can introduce high levels of phase noise through optical heterodyning, which is highly problematic for mobile signal waveforms. In this work, a detailed analytical model of a hybrid photonic/mm-wave system is developed and discussed. Through careful system design, the system is found to support both 5G compatible multi-carrier (OFDM) and single carrier (APSK) modulation at 60 GHz. APSK is found to offer higher tolerance mm-wave phase noise compared to OFDM, ultimately easing optical linewidth restrictions to ∼30 kHz. The model is extended to include a novel millimetre wave phase noise cancelling receiver, which is shown to significantly alleviate these restrictions even further—enabling phase noise free mm-wave operation for optical linewidths up to ∼2 MHz. Detailed analysis and discussion of this extended system lead to the establishment of a theoretical relationship between the mm-wave receiver design and the achievable system performance in terms of error vector magnitude (EVM). Excellent matching of the predicted theoretical with simulated performances is shown. [ABSTRACT FROM AUTHOR]

Multiple antenna technologies have attracted much research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are adopted. Since multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna technologies to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. Radically new approaches are required to achieve orders-of-magnitude improvements in these metrics. There will be large technical challenges, many of which are yet to be identified. In this paper, we survey three new multiple antenna technologies that can play key roles in beyond 5G networks: cell-free massive MIMO, beamspace massive MIMO, and intelligent reflecting surfaces. For each of these technologies, we present the fundamental motivation, key characteristics, recent technical progresses, and provide our perspectives for future research directions. The paper is not meant to be a survey/tutorial of a mature subject, but rather serve as a catalyst to encourage more research and experiments in these multiple antenna technologies. [ABSTRACT FROM AUTHOR]