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This paper considers the uplink performance of a multi-user massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system with mobile users. Mobility brings two major problems to a MIMO-OFDM system: inter carrier interference (ICI) and channel aging. In practice, it is common to allot multiple contiguous subcarriers to a user as well as schedule multiple users on each subcarrier. Motivated by this, we consider a general subcarrier allocation scheme and derive expressions for the ICI power, uplink signal to interference plus noise ratio and the achievable uplink sum-rate, taking into account the ICI and the multi-user interference due to channel aging. We show that the system incurs a near-constant ICI power that depends linearly on the ratio of the number of users per subcarrier to the number of subcarriers per user, nearly independently of how the UEs distribute their power across the subcarriers. Further, we exploit the coherence bandwidth of the channel to reduce the length of the pilot sequences required for uplink channel estimation. We consider both zero-forcing and maximal-ratio combining at the receiver and compare the respective sum-rate performances. In either case, the subcarrier allocation scheme considered in this paper leads to significantly higher sum-rates compared to previous work, owing to the near-constant ICI property as well as the reduced pilot overhead. [ABSTRACT FROM AUTHOR]

This paper considers a massive random access problem in which a large number of sporadically active devices wish to communicate with a base station (BS) equipped with massive multiple-input multiple-output (MIMO) antennas. Each device is preassigned a unique signature sequence, and the BS identifies the active devices by detecting which sequences are transmitted. This device activity detection problem can be formulated as a maximum likelihood estimation (MLE) problem for which the sample covariance matrix of the received signal is a sufficient statistic. The goal of this paper is to characterize the feasible set of problem parameters under which this covariance based approach is able to successfully recover the device activities in the massive MIMO regime. Through an analysis of the asymptotic behaviors of MLE via its associated Fisher information matrix, this paper derives a necessary and sufficient condition on the Fisher information matrix to ensure a vanishing probability of detection error as the number of antennas goes to infinity, based on which a numerical phase transition analysis is obtained. This condition is also examined from a perspective of covariance matching, which relates the phase transition analysis to a recently derived scaling law. Further, we provide a characterization of the distribution of the estimation error in MLE, based on which the error probabilities in device activity detection can be accurately predicted. Finally, this paper studies a random access scheme with joint device activity and data detection and analyzes its performance in a similar way. [ABSTRACT FROM AUTHOR]

Multiple signal classification (MUSIC) has been widely applied in multiple-input multiple-output (MIMO) receivers for direction-of-arrival (DOA) estimation. To reduce the cost of radio frequency (RF) chains at millimeter-wave bands, hybrid analog-digital structure has been adopted in massive MIMO transceivers. In this situation, received signals at the antennas are unavailable to the digital receiver, and as a consequence, the spatial covariance matrix (SCM), which is essential in MUSIC algorithm, cannot be obtained using traditional sample average approach. Based on our previous work, we propose a novel algorithm for SCM reconstruction in hybrid massive MIMO systems with multiple RF chains in this paper. By switching the analog beamformers to a group of predetermined DOAs, SCM can be reconstructed through the solutions of a set of linear equations. Furthermore, a low-complexity algorithm, as well as a careful selection of the predetermined DOAs, will be also presented in this paper. Simulation results show that the proposed algorithms can reconstruct the SCM accurately so that MUSIC algorithm can be well used in hybrid massive MIMO systems with multiple RF chains. [ABSTRACT FROM AUTHOR]

Millimeter-wave vehicle-to-vehicle communication systems with multiple-input multiple-output antenna array have drawn significant attention because it is expected to satisfy the growing bandwidth requirements for the cooperative intelligent transportation systems. However, maintaining high-quality communication links between communicating vehicles without high overhead is a challenging problem due to the high mobility of vehicles. In this paper, we propose a beam management algorithm with spatially distributed antenna subarrays instead of a single co-located antenna array. Unlike existing methods, we use distributed antenna subarrays to exploit the geometric relationship of the beam directions and the relative distance between communicating vehicles. We reduce the beam alignment errors by minimizing the sum of squared errors between the estimated beam direction after the beam training process and the refined beam direction derived from the measured position and velocity data. Additionally, a position data request protocol is devised to reduce the beam refining errors. Numerical results demonstrate that the proposed beam management algorithm successfully reduces the beam alignment errors and it is robust to position and velocity measurement errors. [ABSTRACT FROM AUTHOR]

This study is motivated by the fact that localization in millimeter wave(mmWave) Vehicle-to-Vehicle communication becomes a more critical problem because both the terminals of the communication link are in motion. The positional awareness merely based on GPS or local sensors has an error margin of around 10 meters, which can worsen in uncertain real-time conditions such as road topology and highway traffic. The paper analyses the relation between vehicle dynamics, beamforming, and beam alignment for highly directive antennas. When the subsystem models presented in this paper are taken into consideration, the joint vehicle dynamics-beamforming approach will optimize the link connectivity and SNR. The vehicle dynamics model is designed to be more realistic considering the non-linear acceleration based on the throttle-brake jerks due to induced noises. The Unscented Kalman Filter based prediction subsystem predicts the alignment values even during non-linear acceleration and jerks. The feasibility of antenna design for the beamforming strategies is supported by the requirements of phase shifters and the number of elements. [ABSTRACT FROM AUTHOR]

Channel predictions are important to achieve high spectral efficiency for high-mobility vehicles. Channel extrapolation, used by many prediction methods, suffers from a limited prediction horizon in difficult radio environments. The predictor antenna (PA) concept provides the prediction horizons required for efficient transmission to fast-moving vehicles by measuring the channel ahead of time with an extra antenna placed on the vehicle. This paper presents a general framework that addresses the practical signal processing challenges of the PA concept. It is adaptable to a vast variety of vehicular deployment, mobility, and communication scenarios. A new theoretical prediction normalized mean-squared error (NMSE) expression is derived based on the presented framework. The framework is demonstrated by applying it to extensive channel measurements and comparing the PA predictions to Kalman-based channel predictions and outdated channel estimates. By studying the impact of vehicular velocity and radio environment on the prediction performance, it is shown that PA prediction is weaker at low velocities, where Kalman prediction methods are sufficient, but is uncontested at high velocities in environments without a dominating path. At high velocities in dominating path environments, the Kalman predictor provides usable predictions, but it is still outperformed by the PA predictions. [ABSTRACT FROM AUTHOR]

We give an overview of recent developments in the modeling of radiowave propagation, based on machine learning (ML) algorithms. We identify the input and output specification and the architecture of the model as the main challenges associated with ML-driven propagation models. Relevant papers are discussed and categorized based on their approach to each of these challenges. Emphasis is given on presenting the prospects and open problems in this promising and rapidly evolving area. [ABSTRACT FROM AUTHOR]

As the number of antennas increases, the massive multiple-input multiple-output (MIMO) system can precisely point to user equipments (UEs) with narrow beams. Accurate and timely channel state information (CSI) feedback is crucial to keep UEs in service. Mobile UEs, however, may suffer from the narrow beam nature of the massive MIMO system since UEs can move out of the beam coverage. When intelligent reflecting surface (IRS) is applied to the massive MIMO system, the adjustment of the IRS cannot be frequent as the IRS is controlled remotely by the base station (BS). Limiting the number of CSI feedback and the number of both BS and IRS adjustments significantly reduces the overhead of transmission and computation to the system. In this paper, we consider the UEs’ mobility adaptation problem in an IRS assisted multiuser massive MIMO downlink system with infrequent CSI feedback. We propose a beam control method that adapts to UEs’ mobility. The problem is constructed as a sum rate problem where both the BS and IRS are taken into account to jointly optimize the beamforming matrices. Simulation results show that our proposed algorithm can converge quickly and provide satisfactory performance for mobile UEs. At the same time, our proposed algorithm reduces the frequency of updating the beamforming matrices effectively both at the BS and at the IRS. [ABSTRACT FROM AUTHOR]

Extremely large-scale multiple-input-multiple-output (XL-MIMO) is promising to meet the high rate requirements for future 6G. To realize efficient precoding, accurate channel state information is essential. Existing channel estimation algorithms with low pilot overhead heavily rely on the channel sparsity in the angular domain, which is achieved by the classical far-field planar-wavefront assumption. However, due to the non-negligible near-field spherical-wavefront property in XL-MIMO, this channel sparsity in the angular domain is not achievable. Therefore, existing far-field channel estimation schemes will suffer from severe performance loss. To address this problem, in this paper, we study the near-field channel estimation by exploiting the polar-domain sparsity. Specifically, unlike the classical angular-domain representation that only considers the angular information, we propose a polar-domain representation, which simultaneously accounts for both the angular and distance information. In this way, the near-field channel also exhibits sparsity in the polar domain, based on which, we propose on-grid and off-grid near-field XL-MIMO channel estimation schemes. Firstly, an on-grid polar-domain simultaneous orthogonal matching pursuit (P-SOMP) algorithm is proposed to efficiently estimate the near-field channel. Furthermore, an off-grid polar-domain simultaneous iterative gridless weighted (P-SIGW) algorithm is proposed to improve the estimation accuracy. Finally, simulations are provided to verify the effectiveness of our schemes. [ABSTRACT FROM AUTHOR]

In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis. [ABSTRACT FROM AUTHOR]

Applying non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) networks has the potential to significantly enhance the spectral efficiency. In this paper, we propose an opportunistic beam-splitting NOMA scheme to fully exploit the antenna array gain in downlink mmWave networks, where single- and double-beam NOMA transmissions are dynamically enabled according to the spatial angle difference between the paired NOMA users, thereby enhancing the flexibility of applying NOMA in mmWave networks. The base station with a single radio frequency chain implements the double-beam NOMA transmission by adopting the beam-splitting technique. We develop a unified theoretical performance analysis framework for the proposed scheme, while taking into account the spatially random users, link blockage model, and general distance-based user pairing strategy. By using tools from stochastic geometry, we derive the exact expressions of the coverage probability and the sum rate of the proposed scheme under both the LoS exponential and ball models. We further derive the corresponding upper bound to simplify the analytical expressions. Simulations validate the theoretical analysis and demonstrate the performance gains of the proposed scheme in terms of the coverage probability and sum rate over the conventional single-beam NOMA and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

Feature-based physical layer authentication (PLA) schemes, using position-specific channel characteristics as identifying features, can provide lightweight protection against impersonation attacks in overhead-limited applications like e.g., mission-critical and low-latency scenarios. However, with PLA-aware attack strategies, an attacker can maximize the probability of successfully impersonating the legitimate devices. In this paper, we provide worst-case detection performance bounds under such strategies for a distributed PLA scheme that is based on the channel-state information (CSI) observed at multiple distributed remote radio-heads. This distributed setup exploits the multiple-channel diversity for enhanced detection performance and mimics distributed antenna architectures considered for 4G and 5G radio access networks. We consider (i) a power manipulation attack, in which a single-antenna attacker adopts optimal transmit power and phase; and (ii) an optimal spatial position attack. Interestingly, our results show that the attacker can achieve close-to-optimal success probability with only statistical CSI, which significantly strengthens the relevance of our results for practical scenarios. Furthermore, our results show that, by distributing antennas to multiple radio-heads, the worst-case missed detection probability can be reduced by 4 orders of magnitude without increasing the total number of antennas, illustrating the superiority of distributed PLA over a co-located antenna setup. [ABSTRACT FROM AUTHOR]

In this paper, we study the three-dimensional (3D) path planning problem for cellular-connected unmanned aerial vehicle (UAV) taking into account the impact of 3D antenna radiation patterns. The cellular-connected UAV has a mission to travel from an initial location to a destination. In this process, there is a trade-off between the flight time and the expected communication outages duration, which requires planning a suitable route to avoid the weak coverage region. However, as the existing cellular networks are primarily designed for ground coverage, the communication coverage in the sky tends to be intermittent and irregular due to the potential for severe interference and obstructions (such by buildings), which brings great challenges to 3D path planning. To address this challenge, we first construct a 3D coverage map that stores the expected outage probability over each locations. We then propose a multi-step dueling DDQN (multi-step D3QN) based algorithm to design the local optimal UAV path by leveraging the constructed coverage map. In this algorithm, the UAV acts as the agent to learn the appropriate action to complete the flight mission. Numerical results show the effectiveness of the proposed algorithm for connectivity-aware UAV path planning and the superiority of 3D path design over its 2D counterparts. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel generalized space-code index modulation (GSCIM) scheme for spectrum-efficient and energy-saving transmission. In our proposed scheme, the input information bits are transmitted not only by modulated symbols, but also by the activated transmit antennas pattern and the selected spreading code patterns for the in-phase and quadrature components. Due to the increase of the index dimension, more information bits can be implicitly transmitted, which can improve energy efficiency and have a higher data rate compared with spatial modulation (SM), generalized SM (GSM), generalized CIM-aided SM (GCIM-SM) and CIM-aided quadrature spatial modulation (CIM-QSM). In order to further reduce the complexity of despreading-based maximum likelihood (ML) detection, we propose an enhanced low-complexity detector that can achieve near-ML error performance. An analytical upper bound on the average bit error probability associated with the optimal ML detection is derived, which is verified by simulation results. Simulation results also show that the proposed GSCIM scheme outperforms SM, GSM, GCIM-SM and CIM-QSM schemes in terms of error performance. [ABSTRACT FROM AUTHOR]

In this paper, an antenna synthesis process is investigated for Intelligent Transportation System (ITS) application. The wireless communication between Road Side Units (RSUs) and On Board Units (OBUs) located in the vehicles enables smart mobility. However, to support high speed vehicles and high data rates, a wider coverage area by the RSU antennas projected on the highway is required. This is defined by the radiation patterns of the RSU antennas. On a multi-lane highway, interference from the adjacent lanes is a critical issue which determines the communication reliability in terms of Single-to-Interference plus Noise Ratio (SINR). Hence, in this paper, an interference-aware antenna synthesis process is proposed and a planar array is optimized based on the objective function of obtaining a wide coverage area in terms of SINR distribution for a given modulation scheme. The proposed antenna array enhances the reliable communication area and provides improved SINR distribution across the lane for misaligned vehicles from the center of the lane. The results indicate that the proposed antenna array performs better than the existing designs in terms of communication reliability. [ABSTRACT FROM AUTHOR]

This paper, for the first time, reports the fabrication of an on-Silicon aperture-coupled 3D Patch antenna using micromachining and low-temperature, low-pressure Copper(Cu)-Copper(Cu) thermo-compression bonding. Micromachining technique was used to reduce the effective dielectric constant of Silicon (Si), thereby increasing the radiation efficiency. One of the main challenges in fabricating the aperture coupled patch antenna on Si is the realization of its 3D structure. The top and bottom substrates of the 3D antenna have to be bonded together without disturbing the micromachined thin membrane. This was achieved using thermo-compression bonding under optimized temperature and pressure conditions with a 3 nm Gold (Au) passivation layer, which prevents the oxidation of the Cu layer underneath and thereby reducing the inter-diffusion barrier across the interface. The proposed fabrication process flow introduces the novelty of using bonding/stacking metal inter-layer as the common ground of the antenna. The device was fabricated on high resistivity Si wafers to minimize the conduction losses. Herein, we have fabricated an aperture coupled 3D patch antenna with a cavity depth of $200\pm ~10\mu \text{m}$ , and the device characteristics were compared with the HFSS simulation results. The reliability of the fabricated antenna was assessed by bond strength analysis, cross sectional FESEM and TEM imaging. The on-chip antenna yielded a resonance frequency of 13.4 GHz, with VSWR 1.16. The radiation pattern of the antenna was also analyzed experimentally. This technology is the way forward to fabricating miniaturized high performance on-chip antennas. [ABSTRACT FROM AUTHOR]

Direction-of-arrival (DOA) information is vital for multiple-input-multiple-output (MIMO) systems to complete localization and beamforming tasks. Switched antenna arrays have recently emerged as an effective solution to reduce the cost and power consumption of MIMO systems. Switch-based array architectures connect a limited number of radio frequency chains to a subset of the antenna elements forming a subarray. This paper addresses the problem of antenna selection to optimize DOA estimation performance. We first perform a subarray layout alignment process to remove subarrays with identical beampatterns and create a unique subarray set. By using this set, and based on a DOA threshold region performance approximation, we propose two antenna selection algorithms; a greedy algorithm and a deep-learning-based algorithm. The performance of the proposed algorithms is evaluated numerically. The results show a significant performance improvement over selected benchmark approaches in terms of DOA estimation in the threshold region and computational complexity. [ABSTRACT FROM AUTHOR]

This paper presents a technique for circuit breaker radiometric monitoring using broadband plana monopole antennas (PMA). Considering that this work represents the continuity of a previous research, the antenna has been miniaturized using a bioinspired geometry based on the Acer Macrophyllum leaf. The monitoring system consists in measuring the signal radiated by electric arcs in circuit breaker poles during its switching operations. By analyzing these signals, it is possible to evaluate, non-intrusively, the equipment electric and mechanical status, providing important information to maintenance crews regarding the need for interventions. By performing laboratory tests, it was confirmed that the developed bioinspired PMA has adequate gain values, radiation pattern and frequency range to circuit breaker monitoring applications. Moreover, field tests on a 230 kV SF6 circuit breaker were carried out, from which the proposed technique applicability was confirmed. The proposed monitoring technique can be considered a continuous and non-invasive solution, since the antennas can be placed at a safe distance from the equipment under analysis, without compromising the insulation. In the substation, the technique has the potential to detect problems of electrical and mechanical nature, since important operational parameters can be detected, such as opening time and pole synchronicity. [ABSTRACT FROM AUTHOR]

As an efficient and interference-resistant coding technique, multiple description coding (MDC) is proposed with the aim to solve the transmission unreliability problem caused by packet errors, loss or blocking delays. The integration of MDC with non-orthogonal multiple access (NOMA) scheme (MDC-NOMA) can effectively boost the robustness and throughput of the underlying system. Additionally, space-time block coding (STBC) can further enhance the system reliability with increased diversity gain, as well as reduced decoding complexity. In this paper, we propose a novel framework referred to as MDC-NOMA-STBC, in which we apply Alamouti STBC integrated with MDC and NOMA to implement more reliable transmission. Specifically, NOMA signals are constructed by superimposing the descriptions from different users, then transmitted by the base station (BS) using Alamouti STBC. In order to substantiate the performance of the proposed framework, first, we derive closed-form expressions of both the outage probability and ergodic rate for each user in a two-antenna BS scenario. Second, for multi-antenna BS, we investigate different antenna selection strategies to further enhance the outage performance under the considered framework, whose analytical expression is provided wherever possible. Third, Monte Carlo simulation results are presented to validate our theoretical framework and to corroborate the superiority of the proposed MDC-NOMA-STBC over state-of-the-art MDC-NOMA scheme. Moreover, under realistic contexts with image transmission, it is confirmed that MDC-NOMA-STBC outperforms its counterpart MDC-NOMA in terms of the peak signal-to-noise ratio and the bit error rate. [ABSTRACT FROM AUTHOR]

Multi-numerology transmission is a promising multiple access scheme for flexible communication systems, which can simultaneously support users with different service requirements. To this end, both inter- and intra-numerology interference (inter-NI and intra-NI) should be suppressed, which is not straightforward. This paper proposes a novel zero-forcing (ZF) precoding design, which perfectly eliminates all the interference, for massive multiple-input multiple-output (MIMO) systems with multi-numerology. First of all, we express the signal-to-interference-plus-noise ratio (SINR) of the multi-numerology system with spectrum sharing. From the SINR representation, we identify the channels that precoders must nullify to suppress inter-NI. After that, we propose a ZF precoder suppressing both inter-NI and intra-NI perfectly. The lower bound of ergodic achievable rate with perfect channel state information at the transmitter (CSIT) is analyzed. Based on the lower bound of ergodic achievable rate, we present the feasible rate region. Also, we propose two power allocation schemes: user fairness and the ergodic sum rate maximization. The simulation results demonstrate the advantage of the proposed precoding design and verify our analysis results. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) is considered as a critical technique in 5 G New Radio (NR), due to its capability to significantly improve data rate and link reliability for the radio link. To make it a reality, it is essential to evaluate massive MIMO performance in realistic spatial fading channel conditions. Specifically, dynamic spatial channel emulation is crucial to evaluate the massive MIMO beam operations. Due to the high cost associated with both the traditional conduced testing method and the standardized multi-probe anechoic chamber (MPAC) based Over-the-Air (OTA) testing setup for massive MIMO performance testing, fading channel emulation for massive MIMO testing using a conductive phase matrix setup has been proposed in the literature. However, it is still a challenging problem to emulate dynamic spatial channels in a cost-effective and efficient manner for the conductive phase matrix setup, since traditional algorithms suffer from high computational complexity and system cost. This paper proposes a fast and accurate framework to emulate dynamic spatial channels in the phase matrix setup, where the basic idea is to mimic a virtual MPAC setup. By doing so, we can mimic MPAC setup with flexible probe configurations. Furthermore, a novel successive cancellation strategy and a closed-form algorithm are proposed to determine the probe locations and probe weights, respectively, which can significantly reduce the computational complexity associated with dynamic channel emulation. Simulation results show that the proposed algorithm is highly accurate and computationally efficient, compared to state-of-art solutions. Further, we apply our developed algorithm to emulate measured non-stationary channels and excellent emulation accuracy can be achieved. The proposed method can be employed for emulating dynamic spatial channels, which is of great importance for massive MIMO performance testing. [ABSTRACT FROM AUTHOR]

Providing seamless connectivity to unmanned aerial vehicle user equipment (UAV-UE) is very challenging due to the encountered line-of-sight interference and reduced gains of down-tilted base station (BS) antennas. For instance, as the altitude of UAV-UEs increases, their cell association and handover procedure become driven by the side-lobes of the BS antennas. In this paper, the performance of cellular-connected UAV-UEs is studied under 3D practical antenna configurations. Two scenarios are studied: scenarios with static, hovering UAV-UEs and scenarios with mobile UAV-UEs. For both scenarios, the UAV-UE coverage probability is characterized as a function of the system parameters. The effects of the number of antenna elements on the UAV-UE coverage probability and handover rate are then investigated. Moreover, a lower bound on the handover probability is derived as a function of the number of antenna elements and the UAV-UE mobility speed. Results reveal that the UAV-UE coverage probability under a practical antenna pattern is lower than that under a simple antenna model. Moreover, vertically-mobile UAV-UEs are susceptible to altitude handover due to consecutive crossings of the nulls and peaks of the antenna side-lobes. The effect of altitude handover is also shown to be effectively mitigated by serving UAV-UEs cooperatively from multiple ground BSs. [ABSTRACT FROM AUTHOR]

In this paper, a dual circularly-polarized (CP) multi-beam antenna is proposed for future vehicular radar applications. The antenna is composed of two pillbox reflector beamforming networks (BFNs) and a series-fed microstrip line based dual CP leaky-wave antenna (LWA) array, which has a symmetrical structure and can obtain both left hand circular polarization (LHCP) and right hand circular polarization (RHCP) by switching the exciting current direction of the microstrip line. Besides, a shorted stub is loaded in the LWA to suppress the open-stop band (OSB), and thus achieve the broadside radiation and good impedance matching of the LWA. To realize the dual-polarized radiation characteristic with low-cost passive beam scanning capability, two pillbox BFNs are connected at both sides of the LWA to share the LWA aperture. The two different BFNs can excite different CP radiation patterns. A prototype of the proposed antenna is fabricated in the frequency band 23.5–24.5 GHz, and the measured results approve that the proposed antenna can realize ±36° beam scanning range with −4.0 dB crossover level, and the gain is higher than 17.7 dBi in the operating band. The advantages of the proposed antenna, including low-profile, low-cost, passive beam scanning ability, and dual circular polarization, make it an attractive choice for low-cost millimeter-wave radar applications. [ABSTRACT FROM AUTHOR]

It is well accepted that acquiring downlink channel state information in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems is challenging because of the large overhead in training and feedback. In this paper, we propose a deep generative model (DGM)-based technique to address this challenge. Exploiting the partial reciprocity of uplink and downlink channels, we first estimate the frequency-independent underlying channel parameters, i.e., the magnitudes of path gains, delays, angles-of-arrivals (AoAs) and angles-of-departures (AoDs), via uplink training, since these parameters are common in both uplink and downlink. Then, the frequency-specific underlying channel parameters, specifically, the phase of each propagation path, are estimated via downlink training using a very short training signal. In the first step, we incorporate the underlying distribution of the channel parameters as a prior into our channel estimation algorithm. We use DGMs to learn this distribution. Simulation results indicate that our proposed DGM-based channel estimation technique outperforms, by a large gap, the conventional channel estimation techniques in practical ranges of signal-to-noise ratio (SNR). In addition, a near-optimal performance is achieved using only few downlink pilot measurements. [ABSTRACT FROM AUTHOR]

Detection of the high impedance fault caused by vegetation is one of the biggest challenges brought by the usage of covered conductors in medium voltage overhead power lines. One of the accompanying events of long-term contact of vegetation with the XLPE insulation is partial discharge which damages the insulation. Current systems for the detection of partial discharge have two major problems: the price and difficult installation. In this paper, an approach for the detection of the partial discharge from the data collected by the antenna is described. This approach is focused on the small computational demand and low false positive rate. Thanks to the small computational requirements, it can be run on the remote gateway devices which are collecting the data from the antenna. It is composed of four steps: outlier detection, outlier clustering, feature extraction, and classification. It is shown that this approach greatly improves the detection rate and lowers false positives compared to the previous algorithm used for partial discharge detection based on the data from an antenna, making it fit to use in the production environment. [ABSTRACT FROM AUTHOR]

In cellular communication systems, it is conventional to assume the absence of a line of sight (LoS) path between the users and theirassociated access points (APs). This assumption however becomes questionable in the context of recent developments in the direction of cell-free (CF) massive MIMO systems. In the CF massive MIMO, the AP density is assumed to be comparable with the user density, which increases probability of existence of an LoS path between the users and their associated APs. In this paper, we analyze the performance of an uplink CF massive MIMO system, with a probabilistic LoS channel model. Here, we first derive the effective statistics of this channel model, and argue that their behaviour is fundamentally different from that of the conventional rich scattering channels. Utilizing these statistics, we next compare the rates achievable by CF massive MIMO systems, under both stream-wise and joint decoding at the central processing unit. Following this, we also discuss the centralized MMSE based data detection to obtain a complexity/ performance trade-off. Finally, using detailed Monte-Carlo simulations, we validate our analytical results, and evaluate the performance of the three data detection schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose an adaptive opportunistic spatial modulation scheme (AOSM), in which, our unique opportunistic group-antenna-selection scheme is amalgamated with a simple phase alignment (PA) transmit pre-scaling to boost the transmit-diversity of SM. To characterize and analytically evaluate the AOSM, a comprehensive error performance analysis is presented with single antenna reception. We theoretically derive a tight upper-bound for the symbol error probability (SEP) in closed-form based on an improved union-bound. The exact explicit asymptotic formula of the SEP at high SNR is provided as well. These results demonstrate that the transmit-diversity of proposed AOSM-(multiple-input single-output) MISO scheme is not only successfully achieved, but also elevated to be equal to the number of antennas in each antenna group. Moreover, it also reveals an important performance trend: at high SNR, with a fixed number of transmit antennas and a given data-rate, the SEP performance of the AOSM-MISO scheme can be successively enhanced by utilizing less antennas groups and bigger size of the signal constellation, because of the increase in transmit-diversity. Furthermore, the PA-aided SM-MISO is a special case of our AOSM-MISO. We are the first to provide the exact transmit-diversity gain for this conventional system and show that the PA pre-scaling scheme only can not improve the transmit-diversity of SM. This result sharpens the empirical diversity approximation results proposed in the existing literature. Simulation results well validate the analytical derivations, and indicate that our AOSM system can effectively improve system performance with high transmit-diversity at low-complexity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) communication system using hybrid precoding of subarray-connected structure at the base station. To maximize the received signal power of the user, we jointly optimize the active beamforming at the BS and passive beamforming at the IRS, respectively. Exploiting the rank-one property of mmWave channels, we transform the original problem into an approximate optimization problem and give the closed-form solution of the approximated problem. Simulation results show that our proposed scheme can effectively improve the received signal quality of the user with a high energy efficiency. [ABSTRACT FROM AUTHOR]

Aiming for 5G-NR vehicular applications, this paper proposes two miniaturized wideband pattern reconfigurable antennas with different pattern steering capabilities. They are inspired by an end-fire structure that could be easily mounted on cars. This newly proposed planar pattern reconfigurable end-fire structure is firstly presented and studied by current distribution and equivalent circuit analysis. By turning the ON / OFF state of the PIN diodes on the passive dipole, a planar reconfigurable antenna with one omnidirectional and two end-fire beams is implemented. Additionally, a low-profile pattern diversity antenna with a compact size of 0.311 λ0 × 0.244 λ0 × 0.106 λ0 is implemented by loading a reactive metasurface, its main lobe can be steered in the broadside direction (35°, 0°, and −35°). Both antennas achieve a wideband response over 3.30 to 4.20 GHz (24.0%) range and good radiation efficiency of 84.0%. They feature the advantages of a miniaturized size (low-profile), structurally simple and fabrication friendly design, wideband, good radiation efficiency (low-loss), and flexible multi-beam switching capability, which are well suited for the coming sub 6 GHz vehicular applications in different scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a novel general sixth-generation (6G) irregular-shaped geometry-based stochastic model (IS-GBSM) for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless communication systems. The proposed IS-GBSM can model spherical wavefront propagation, high delay resolution, and three-dimensional (3D) space-time-frequency non-stationarity of channels with time-space consistency, and thus can be applied to integrated communication and sensing systems. To capture the 3D non-stationarity with channel consistency, a new hybrid method combining geometric and parametric methods is developed. Based on the geometric method, i.e., visibility region (VR), the smooth and consistent appearance and disappearance of clusters during array-time evolution are modeled. With the help of the parametric method, a frequency-dependent path gain is introduced, and a visible factor based on uniform continuity theorem and bounded variation function is further proposed to capture the soft cluster power handover during cluster array-time evolution. Key channel statistics of the proposed IS-GBSM are derived and investigated. Simulation results demonstrate that the space-time-frequency non-stationarity is modeled and time-space consistency is captured. Finally, the utility of the proposed IS-GBSM is verified by the excellent agreement between simulation results and measurement. [ABSTRACT FROM AUTHOR]

Massive multiple-input-multiple-output (MIMO) and millimeter wave have been adopted as the enabling technologies for the 5G and beyond 5G (B5G) systems. A challenging problem introduced by the use of large antenna size and wide bandwidth is beam squint, i.e., spatial-wideband effect. Beam squint can significantly degrade the channel estimation performance for conventional channel estimators. Research effort on channel estimation under beam squint conditions has been very limited. For the few available work that attempts to address this problem, they require either all subcarriers or multiple symbols used as pilot for channel estimation, so large overhead becomes inevitable. Therefore, in this paper, we propose an efficient channel estimation method that only requires a small number of subcarriers. The channel estimation problem is formulated as a nonlinear least squares optimization problem. Initial parameter estimation is critical, which will affect the efficiency and convergence of the proposed algorithm. Using a densely-spaced antenna structure and consecutive subcarriers assignment approach, we can effectively avoid the aliasing effect and reduce the ambiguity during the initialization phase. A subcarrier assignment criterion is proposed to achieve the optimal performance. Closed-form expressions of the Cramér-Rao lower bound (CRLB) and the achievable rate are derived to evaluate the performance. Both simulation results and theoretical analysis show that even with a small number of subcarriers, the estimation error closely approaches the CRLB, and its effect is negligible compared with the noise when evaluating the signal-to-noise ratio with a simple linear detector. Furthermore, the number of pilot subcarriers has little impact on the achievable rate. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) of mobile communications givesbirth to the evolution of the base stations. They progressively include arrays of antennas in the sub-6 GHz frequency band worldwide. Moreover, 5G takes advantage of the beamforming capabilities to gain power efficiency and higher throughputs. Within this framework, achieving high decoupling performance between any pairs of antennas and compactness at the same time become a major challenge. The present paper describes an advanced solution based on the interposition of a thin and low-profile absorbing wall operating in the 3.4–3.6 GHz frequency band. The absorption is provided by a frequency selective surface whose elementary pattern size is first optimized. Then, the compact absorbing wall that associates back-to-back pieces of absorber is interposed between elements of an antenna array. Moreover, the fabrication of both antenna array and decoupling device involve lightweight and low-cost composite technology. The results show that such a compact decoupling device achieves excellent decoupling capabilities while keeping up the antenna array performance. [ABSTRACT FROM AUTHOR]

In this paper, a 3D geometry-based double-spherical terahertz (THz) channel model is proposed for ultra massive multiple-input multiple-output (MIMO) communications. To reflect real THz ultra massive MIMO communications, the characteristic of nano-material array antenna and the high loss of THz bands are considered in channel modeling. Based on the proposed geometry-based stochastic model (GBSM), power delay profile (PDP), space-time-frequency correlation function, and the Doppler power spectral density are derived and analyzed. Furthermore, the proposed model is validated by comparing the simulated results with the measurement reference. Influences of channel parameters, namely, antenna element spacing, carrier frequency, number and location of clusters, on the correlation functions are investigated. The results indicate that antenna element spacing and number of clusters have significant impacts on channel correlation, and the decreasing of correlation function becomes slower when antenna element spacing decreases. Moreover, location of clusters also affects the drop rate of correlation function. The influences of the number of clusters and concentration of intra-cluster multipath components (MPCs) on the Doppler power spectral density are analyzed. It is found that a larger number of clusters and a more concentrated distribution of intra-cluster MPCs increase the degree of Doppler spectrum variation. The proposed channel model and the corresponding statistical properties are insightful for designing and realizing THz ultra massive MIMO systems for 6G and beyond. [ABSTRACT FROM AUTHOR]

Supporting reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has recently become a critical requirement to enable various different use cases of UAVs. Due to their widespread deployment footprint, cellular networks can support beyond visual line of sight (BVLOS) communications for UAVs. In this paper, we consider cellular connected UAVs (C-UAVs) that are served by massive multiple-input-multiple-output (MIMO) links to extend coverage range, while also improving physical layer security and authentication. We consider Rician channel and propose a novel linear precoder design for transmitting data and artificial noise (AN). We derive the closed-form expression of the ergodic secrecy rate of C-UAVs for both conventional and proposed precoder designs. In addition, we obtain the optimal power splitting factor that divides the power between data and AN by asymptotic analysis. Then, we apply the proposed precoder design in the fingerprint embedding authentication framework, where the goal is to minimize the probability of detection of the authentication tag at an eavesdropper. In simulation results, we show the superiority of the proposed precoder in both secrecy rate and the authentication probability considering moderate and large number of antenna massive MIMO scenarios. [ABSTRACT FROM AUTHOR]

In the face of the unprecedented demand for higher data rates while coping with the constraints from physical size (i.e., windward area), it is profitable to deploy compact planar arrays (CPAs) on the base stations (BSs). But massively densified antenna deployment not only leads to antenna mutual coupling (MC), but also consumes additional energy due to the equipment of more radio frequency (RF) chains. This paper studies energy efficiency (EE) optimization for massive multi-input multi-output (MIMO) wireless systems with a CPA in the presence of MC. In comprehensive consideration of the spectral efficiency (SE) and power consumption, a joint optimization problem of beamforming and antenna subset (AS) is proposed. Our motivation is to relieve the effects of MC and reduce the relevant energy consumption by constructing irregular AS. Particularly, considering the nonconvexity of the objective and the discrete 0-1 constraints, an available iterative algorithm, named the energy-efficient beamforming and AS (EE-BF&AS) algorithm, is developed. Numerical results illustrate that when MC is modeled, the proposed EE-BF&AS algorithm outperforms conventional related approaches in EE. By using the AS switching strategy, the irregular AS can be constructed to make MC less serious and let the relevant energy consumption decrease. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel deep unsupervised learning-based approach that jointly optimizes antenna selection and hybrid beamforming to improve the hardware and spectral efficiencies of massive multiple-input-multiple-output (MIMO) downlink systems. By employing ResNet to extract features from the channel matrices, two neural networks, i.e., the antenna selection network (ASNet) and the hybrid beamforming network (BFNet), are respectively proposed for dynamic antenna selection and hybrid beamformer design. Furthermore, a deep probabilistic subsampling trick and a specially designed quantization function are respectively developed for ASNet and BFNet to preserve the differentiability while embedding discrete constraints into the network structures. With the aid of a flexibly designed loss function, ASNet and BFNet are jointly trained in a phased unsupervised way, which avoids the prohibitive computational cost of acquiring training labels in supervised learning. Simulation results demonstrate the advantage of the proposed approach over conventional optimization-based algorithms in terms of both the achieved rate and the computational complexity. [ABSTRACT FROM AUTHOR]

This paper presents low-complexity decision rules as well as the pertinent analysis for data fusion in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). The proposed framework considers both unknown and known parameter scenarios, and the spatial correlation arising due to close proximity of the sensors for both the centralized MIMO (C-MIMO) and distributed MIMO (D-MIMO) antenna configurations. The resulting detection performance is characterized by determining the closed-form expressions of probabilities of detection and false alarm for both antenna configurations. The optimal sensor gains are also determined for both the D-MIMO and C-MIMO architectures to further improve the detection performance. Additionally, asymptotic analysis is presented for both antenna configurations to determine the power scaling laws for the mmWave massive MIMO WSN, which lead to an improved sensor battery life without sacrificing the system performance. Furthermore, decision rules are also derived along with the pertinent analysis for a practical scenario with uncertainty in the channel state information (CSI) at the fusion center, wherein CSI of the mmWave massive MIMO channel is estimated using the novel sparse Bayesian learning (SBL) framework. Simulation results are presented to illustrate the performance of the proposed schemes and to validate the analytical results. [ABSTRACT FROM AUTHOR]

In frequency division duplex (FDD) massive multi-input multi-output (MIMO), the two-stage beamforming (TSB) using channel covariance matrices significantly reduces the downlink training length (DTL) and channel feedback. Nevertheless, most of the TSB methods focus on the one-ring channel. In this paper, we consider the multiple scatterer clusters (MSC) channel in massive MIMO systems and propose a TSB method based on cluster group. To reduce the channel state information (CSI) feedback, for each cluster we use a cluster-group-based eigen-prebeamformer to sparsify the effective channel matrix. The DTL is also reduced by a graph-based downlink training design. We further develop a multi-user beamformer to mitigate the inter-user interference. To further reduce the DTL, two other methods are also proposed based on the vertex and edge deletion. Simulation results confirm the efficiency of the proposed schemes in improving the effective spectral efficiency. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) printed Luneburg lens with nearly isotropic properties is presented. The cubical-lattice-type and the rod-type gradient-index materials are employed together to construct the novel printable spherical lens geometry, whose nearly isotropic properties improve the antenna radiation characteristics significantly. The dual-polarized radiation beam generated by the lens antenna can steer in a wide angular range with stable performance throughout a wide operating band. A prototype with an equivalent radius of 16.8 mm is printed and measured in the Ka-band. An impedance bandwidth of more than 40% for |S11| of less than −17.5 dB, a gain of up to 21.3 dBi, and promising radiation patterns with the dual polarization scanning in an angular range of ±60° are obtained experimentally. With the advantages of satisfying operating performance and ease of realization, the lens investigated in this paper would be an attractive candidate for the wireless applications in millimeter-wave vehicular networks. [ABSTRACT FROM AUTHOR]

A novel ultra-wideband (UWB) reflectarray antenna for the Internet of Vehicles (IoV) is introduced in this paper. By simply connecting the neighboring reflectarray elements, the proposed reflectarray antenna achieves a remarkable radiation pattern bandwidth of 20 GHz, ranging from 10 GHz to 30 GHz. To explain the operating principles of the proposed reflectarray antenna, the equivalent circuit (EQC) model of the unit cell is built, which also provides an efficient and rapid way to analyze the performance of the proposed reflectarray element. It is found from the EQC analysis that the connected elements can achieve better reflection phase responses than conventional separated elements, thereby improving the array bandwidth. As a proof of concept, a 503-element reflectarray antenna simultaneously covering the vehicle-to-satellite bands (12.25–12.75 GHz/14.0–14.5 GHz/19.6–21.2 GHz/29.4–31.0 GHz), the 24-GHz short-range vehicle radar band (24.25–26.65 GHz) and the 5G millimeter-wave band (27.5–28.35 GHz) is designed, fabricated, and characterized. The experimental results demonstrate that the presented reflectarray antenna can maintain undistorted beams, high antenna gain, low cross-pol level, and moderate aperture efficiency over a bandwidth of 100%, i.e., from 10 to 30 GHz. With its simple and planar aperture as well as excellent performance, the proposed reflectarray antenna can be a promising candidate for vehicles that require reliable high data-rate satellite links and 5G millimeter-wave connections simultaneously. [ABSTRACT FROM AUTHOR]

Decentralized baseband processing (DBP) architecture, which partitions the base station antennas into multiple antenna clusters, has been recently proposed to alleviate the excessively high interconnect bandwidth, chip input/output data rates, and detection complexity for massive multi-user multiple-input multiple-output (MU-MIMO) systems. In this paper, we propose a novel decentralized Gaussian message passing (GMP) detection for the DBP architecture. Based on the message passing rule, each antenna cluster iteratively calculated the local means and variances which are fused to generate the global symbol beliefs for demodulation. The state evolution framework of the decentralized GMP algorithm is presented under the assumptions of large-system limit and Gaussian sources. Analytical results corroborated by simulations demonstrate that the nonuniform antenna cluster partition scheme exhibits a higher convergence rate than the uniform counterpart. Simulation results illustrate that the proposed decentralized GMP detection outperforms the recently proposed decentralized algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a switched multibeam multi-sector array antenna is proposed to provide 3-D coverage for vehicle to infrastructure (V2I) under 5G-IoT application framework. The multi-sector design is optimized using a quality-conscious communication area synthesis process to achieve $\mathbf {360}^\circ$ coverage in azimuth. Each sector of the design has two microstrip array antenna (MAA) to obtain coverage in the upper and lower halves of the elevation region. The proposed antenna is designed to enhance frequency-dependent beam squint phenomena exploited to achieve multibeam coverage in the elevation region. The simulation results of the proposed antenna having $\mathbf {3\times 2}$ size of MAA indicates the achieved desired radiation characteristics, and a prototype of the same operating in WLAN band ($\mathbf {5.15-5.825}$ GHz) is fabricated for verification. The experimental results show the maximum realized gain is $\mathbf {7.85}$ dBi and the beam tilt of $\mathbf {10.8}^\circ$ to $\mathbf {46.8}^\circ$ in elevation is achieved at central frequencies $\mathbf {5.15}$ GHz and $\mathbf {5.825}$ GHz, respectively. The coverage obtained is $\mathbf {360}^\circ$ in azimuth and $\mathbf {93.6}^\circ$ in elevation. The signal to interference ratio is measured around the antenna, which shows interference suppression of more than $\mathbf {10}$ dB achieved between the MAAs of alternate sectors. Moreover, the port isolation is better than $\mathbf {26}$ dB. Hence, sixteen simultaneous beams utilizing frequency re-use can be operated in the 3-D space around the access point to communicate with multiple drones/vehicles and IoT nodes to realize a smart vehicular application. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communications with multi-GHz bandwidth are envisioned as a key technology for 6G systems. Ultra-massive (UM) MIMO with hybrid beamforming architectures are widely investigated to provide a high array gain to overcome the huge propagation loss at THz band. However, most of the existing hybrid beamforming architectures can only utilize the multiplexing offered by the multipath components, i.e., inter-path multiplexing, which is very limited due to the spatially sparse THz channel. In this paper, a widely-spaced multi-subarray (WSMS) hybrid beamforming architecture is proposed, which improves the multiplexing gain by exploiting a new type of intra-path multiplexing provided by the spherical-wave propagation among $k$ widely-spaced subarrays, in addition to the inter-path multiplexing. The resulting multiplexing gain of WSMS architecture is $k$ times of the existing architectures. For WSMS architecture, a novel design problem is formulated by optimizing the number of subarrays, subarray spacing, and hybrid beamforming matrices to maximize the spectral efficiency, which is decomposed into two subproblems. An optimal closed-form solution is derived for the first hybrid beamforming subproblem, while a dominant-line-of-sight-relaxation algorithm is proposed for the second array configuration subproblem. Extensive simulation results demonstrate that the WSMS architecture and proposed algorithms enhance the spectral efficiency substantially. [ABSTRACT FROM AUTHOR]

This paper presents a gain enhanced wide azimuth beam automotive antenna using half-mode substrate integrated waveguide (HMSIW) cavity for automotive applications. The antenna is separated into two HMSIW cavities by electrical via walls. The two HMSIW cavities are excited through differential feeding, including a 180 $^{\circ }$ delay line in the center of the antenna. The antenna was operated in $TM_{11}$ mode and investigated using aperture theory based on the cavity model. The antenna size is small enough to mount in the rear-view mirror, which has a long rectangular shape. For comparison, the proposed antenna and a conventional 1 × 2 microstrip square patch antenna array were fabricated to the same dimensions. Then, these antennas were tested to provide validation. The tested results were consistent with the simulation results. The tested results show that the antenna, with the overall dimensions of 70 mm × 35 mm × 1.52 mm (1.38 $\lambda _{0}$ × 0.69 $\lambda _{0}$ × 0.03 $\lambda _{0}$), operates at 5.9 GHz. The gain of the antenna is 9.49 dB, and the azimuth beam width is 74.0 $^{\circ }$. The proposed antenna has a wider azimuth beam width (74.0 $^{\circ }$) than a conventional 1 × 2 square patch array antenna (42.0 $^{\circ }$) with similar gain and size. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is foreseen to be a key technology for the 6G wireless communications. In this paper, the performance of downlink Terahertz (THz) communication systems with low-resolution digital-to-analog converters (DACs) at the Access Point (AP) and/or finite-bit analog-to-digital converters (ADCs) at the user sides are investigated. Array-of-subarrays architecture is assumed at the AP, where each RF chain uniquely activates a disjoint subset of antennas, each of which is connected to an exclusive phase shifter. Hybrid precodings including maximum ratio transmission (MRT) and zero-forcing (ZF) precoding are considered. The best beamsteering direction for the phase shifters in the large subarray antenna regime is first proved to be the direction of the line-of-sight (LOS) path. Subsequently, the closed-form expression of the lower-bound of the achievable rate in the large subarray antenna regime is derived, which is the same for both MRT and ZF and is independent of the transmit power. Moreover, numerical results show that the rate loss caused by the phase uncertainties can be negligible in large subarray antenna regime and moderate resolution DACs and ADCs can achieve performance close to the infinite-resolution one. Numerical results validating the analysis are provided as well. Overall, the impact of finite-bit precoding and finite-bit ADCs on the achievable rate of indoor THz communication systems is characterized. [ABSTRACT FROM AUTHOR]

In this paper, we study an unmanned aerial vehicle (UAV)-enabled wireless powered communication network, where a UAV serves multiple energy constrained wireless sensor nodes (WSNs). In such a network, a UAV transmits wireless power to a group of WSNs which exploits the harvested power to transfer their own information towards the UAV in the uplink. For practical scenarios, a nonlinear energy harvesting saturation model is considered at WSNs. We aim to design resource allocation which maximizes the achievable sum rate in the uplink and minimizes the downlink transmit power simultaneously. The design is formulated as a multi-objective optimization problem (MOOP) which optimizes the UAV's 3D position, its transmit power, the time splitting ratio, the uplink transmission time and the beamwidth angle of the UAV. The formulated problem is a non-convex problem which is generally intractable. To address the MOOP, a weighted Tchebycheff method is proposed. The numerical results show a trade-off between the minimum power in the downlink and the maximum rate as well as energy efficiency in the uplink. [ABSTRACT FROM AUTHOR]

Differential modulation schemes are very relevant in receivers having power and processing limitations, as these schemes dispense with the need for knowledge of channel coefficients for symbol detection. Spatial modulation (SM) is a scheme used in multi-antenna transmission scenarios where the data is transmitted in the amplitude, phase and spatial domains through selected antennas. In the coherent domain, generalized SM (GSM) employs multiple antennas in combination during every time slot to enhance the spectral efficiency (SE). In this paper, we propose two differential schemes which activate two or more antennas at a time to transmit the modulated symbol. These schemes achieve higher SE using a lesser number of antennas and lower order modulation schemes instead of the higher number of antennas required for conventional SM schemes based on differential modulation. Simulation studies reveal that the proposed schemes have better bit error rate performance than traditional differential SM schemes. We also derive the analytical union bound for the proposed schemes and is satisfied from medium to high signal-to-noise ratio (SNR) ranges. [ABSTRACT FROM AUTHOR]

Cell-free massive multiple-input multiple-output (MIMO) provides more uniform spectral efficiency (SE) for users (UEs) than cellular technology. The main challenge to achieve the benefits of cell-free massive MIMO is to realize signal processing in a scalable way. In this paper, we consider scalable full-pilot zero-forcing (FZF), partial FZF (PFZF), protective weak PFZF (PWPFZF), and local regularized ZF (LRZF) combining by exploiting channel statistics. We derive closed-form expressions of the uplink SE for FZF, PFZF, and PWPFZF combining with large-scale fading decoding over independent Rayleigh fading channels, taking channel estimation errors and pilot contamination into account. Moreover, we investigate the impact of the number of pilot sequences, antennas per AP, and APs on the performance. Numerical results show that LRZF provides the highest SE. However, PWPFZF is preferable when the number of pilot sequences is large and the number of antennas per AP is small. The reason is that PWPFZF has lower computational complexity and the SE expression can be computed in closed-form. Furthermore, we investigate the performance of PWPFZF combining with fractional power control and the numerical results show that it improves the performance of weak UEs and realizes uniformly good service for all UEs in a scalable fashion. [ABSTRACT FROM AUTHOR]

Thanks to the short wavelength at high frequency (HF), it is promising to combine massive multiple-input and multiple-output (MIMO) with HF communications. In particular, HF massive MIMO differs from the conventional MIMO in array structure and radio propagation. In this paper, we investigate the HF massive MIMO system with a compact planar array (CPA) deployed at the base station (BS) in the presence of electromagnetic mutual coupling (MC) for the asymptotic case under unlimited antenna elements assumption. Specifically, the HF sparse channel is analyzed asymptotically to show that the randomness characteristic of channel decreases in the asymptotic regime, which is conducive to the design of communication systems. Moreover, on the basis of the asymptotic analysis results, the optimal beamforming to maximize the minimum user signal-to-interference-plus-noise ratio (SINR) is derived by applying random matrix theory. Numerical results verify the accuracy of the asymptotic analysis, indicate the performance superiority of the proposed scheme to the traditional minimum mean squared error (MMSE) and maximum ratio transmission (MRT) schemes, and reveal the robustness of the proposal to electromagnetic MC. [ABSTRACT FROM AUTHOR]