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While the deployment of 5G cellular systems will continue well into the next decade, much interest is already being generated toward technologies that will underlie its successor, 6G. Undeniably, 5G will have a transformative impact on the way we live and communicate, but it is still far away from supporting the Internet of Everything, where upward of 1 million devices/km3 (both terrestrial and aerial) will require ubiquitous, reliable, low-latency connectivity. This article looks at some of the fundamental problems that pertain to key physical layer enablers for 6G. This includes highlighting challenges related to intelligent reflecting surfaces, cell-free massive MIMO, and THz communications. Our analysis covers theoretical modeling challenges, hardware implementation issues, and scalability, among others. The article concludes by delineating the critical role of signal processing in the new era of wireless communications. [ABSTRACT FROM AUTHOR]

To fully reap the benefits of massive multiple-input multiple-output hybrid analog and digital precoding in frequency division duplexing single-cell systems, a two-stage precoder is developed utilizing the signal-to-leakage-plus-noise ratio metric. The main idea of this technique is to jointly design the analog precoder based only on the long-term channel statistics information at the transmitter, i.e., the channel mean and reconstructed reduced rank covariance statistics, while the digital precoder is designed based on the instantaneous channel state information of the reduced dimensionality effective reconstructed channel. Consequently, we can significantly reduce the downlink training and uplink feedback overhead analogously to the rank of the resultant effective channel. The two extremes of full channel state information at the transmitter (CSIT) and statistical CSIT are also investigated. The performance gap between the full and statistical CSIT corroborates the importance of the proposed two-stage CSIT approach. These precoders are then extended to multi-cell systems. It is shown that the digital baseband precoder design problem reduces to the generalized Rayleigh quotient problem, while the analog precoder design problem reduces to the quotient trace problem, also known as the ratio trace problem. These dimensionality reduction problems are solved via the generalized eigenvalue decomposition method. Finally, in the presence of multiuser diversity where only a subset of the users are scheduled, to considerably alleviate the channel estimation and feedback overhead burden, a low-complexity one-stage and two-stage CSIT joint user scheduler and precoder algorithms are developed. [ABSTRACT FROM AUTHOR]

Although mmWave systems promise to offer larger bandwidth and unprecedented peak data rates, their practical implementation faces several hardware challenges compared to sub-6 GHz communication systems. These hardware constraints can seriously undermine the performance and deployment progress of mmWave systems and thus necessitate disruptive solutions in the cross-design of analog and digital modules. In this article, we discuss the importance of different hardware constraints and propose a novel system architecture that is able to release these hardware constraints while achieving better performance for future mmWave communication systems. The characteristics of the proposed architecture are articulated in detail, and a representative example is provided to demonstrate its validity and efficacy. [ABSTRACT FROM AUTHOR]

Due to the difficulty in manipulating the distribution of Wishart random matrices, the performance analysis of multiple-input-multiple-output (MIMO) channels has mainly focused on deriving capacity bounds via Jensen’s inequality. However, to the best of our knowledge, the tightness of Jensen’s bounds has not yet been rigorously quantified in the general MIMO context. This paper proposes a new methodology for measuring the tightness of Jensen’s bounds via the sandwich theorem. In particular, we first compare the tightness of two different pairs of upper/lower bounds for a general class of MIMO channels based on the unordered eigenvalue of the instantaneous correlation matrix and for arbitrary numbers of antennas. The tightness of Jensen’s bounds in different channel scenarios is investigated including multiuser MIMO with maximal ratio combining. Our analysis is facilitated by deriving some new results for finite-dimensional Wishart matrices, i.e., for the arbitrary moments of the unordered eigenvalue of central and non-central Wishart matrices. Our results provide very interesting insights into the implications of the system parameters, such as the number of antennas, and signal-to-noise ratio, on the tightness of Jensen’s bounds, and showcase the suitability and limitations of Jensen’s bounds. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the uplink of a single-cell multi-user single-input multiple-output (MU-SIMO) system with in-phase and quadrature-phase imbalance (IQI). In particular, we investigate the effect of receive (RX) IQI on the performance of MU-SIMO systems with large antenna arrays employing maximum-ratio combining receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that the higher the value of signal-to-noise ratio, the higher the impact of IQI on the spectral efficiency (SE). Moreover, a novel pilot-based joint estimator of the augmented multiple-input multiple-output (MIMO) channel matrix and IQI coefficients is described, and then, a low-complexity IQI compensation scheme is proposed, which is based on the IQI coefficients’ estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic SE assuming transmission over Rayleigh fading channels with large-scale fading. Furthermore, we investigate how many mobile stations should be scheduled in massive MIMO systems with IQI and show that the highest SE loss occurs at the optimal operating point. Finally, by deriving asymptotic power scaling laws and proving that the SE loss due to IQI is asymptotically independent of the number of BS antennas, we show that massive MIMO is resilient to the effect of RX IQI. [ABSTRACT FROM AUTHOR]

The statistical properties of the multivariate gamma–gamma $(\Gamma\Gamma)$ distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (pdf), cumulative distribution function (cdf), and moment generation function (mgf) of the multivariate $\Gamma\Gamma$ distribution with arbitrary correlation. Furthermore, we present novel approximating expressions for the pdf and cdf of the sum of $\Gamma\Gamma$ random variables (RVs) with arbitrary correlation. Based on this statistical analysis, we investigate the performance of radio frequency (RF) and optical wireless communication systems. It is worth noting that the presented expressions include several previous results in the literature as special cases. [ABSTRACT FROM AUTHOR]

Heterogeneous networks, HetNets, are known to enhance the bandwidth efficiency and throughput of wireless networks by more effectively utilizing the network resources. However, the higher density of users and access points in HetNets introduces significant inter-user interference that needs to be mitigated through complex and sophisticated interference cancellation schemes. Moreover, due to significant channel attenuation and the presence of hardware impairments, e.g. phase noise and amplifier nonlinearities, the vast bandwidth in the millimeterwave band has not been fully utilized to date. In order to enable the development of multi-Gigabit per second wireless networks, we introduce a novel millimeter-wave HetNet paradigm, termed hybrid HetNet, which exploits the vast bandwidth and propagation characteristics in the 60 GHz and 70?80 GHz bands to reduce the impact of interference in HetNets. Simulation results are presented to illustrate the performance advantage of hybrid HetNets with respect to traditional networks. Next, two specific transceiver structures that enable hand-offs from the 60 GHz band, i.e. the V-band to the 70?80 GHz band, i.e. the E-band, and vice versa are proposed. Finally, the practical and regulatory challenges for establishing a hybrid HetNet are outlined. [ABSTRACT FROM PUBLISHER]

We analyze the performance of dual-hop two-way amplify-and-forward relaying in the presence of in-phase and quadrature-phase imbalance (IQI) at the relay node. In particular, two power allocation schemes, namely, fixed power allocation and instantaneous power allocation, are proposed to improve the system reliability and robustness against IQI under a total transmit power constraint. For each proposed scheme, the outage probability is investigated over independent, non-identically distributed Nakagami- $m$ fading channels, and exact closed-form expressions and bounds are derived. Our theoretical analysis indicates that, without IQI compensation, IQI can create fundamental performance limits on two-way relaying. However, these limits can be avoided by performing IQI compensation at source nodes. Compared with the equal power allocation scheme, our numerical results show that the two proposed power allocation schemes can significantly improve the outage performance, thus reducing the IQI effects, particularly when the total power budget is large. [ABSTRACT FROM AUTHOR]

We provide the first-ever performance evaluation of orthogonal time frequency space (OTFS) modulation in cell-free massive multiple-input multiple-output (MIMO) systems. To investigate the trade-off between performance and overhead, we apply embedded pilot-aided and superimposed pilot-based channel estimation methods. We then derive a closed-form expression for the individual user downlink and uplink spectral efficiencies (SEs) as a function of the numbers of APs, users and delay-Doppler domain channel estimate parameters. Based on these analytical results, we also present new scaling laws that the AP’s and user’s transmit power should satisfy, to sustain a desirable quality of service. It is found that when the number of APs, $M_{a}$ , grows without bound, we can reduce the transmit power of each user and AP proportionally to $1/M_{a}$ and $1/M_{a}^{2}$ , respectively, during the uplink and downlink phases. We compare the OTFS performance with that of orthogonal frequency division multiplexing (OFDM) at high-mobility conditions. Our findings reveal that, OTFS modulation with embedded pilot-based channel estimation provides up to 20-fold gain over the OFDM counterpart in terms of 95%-likely per-user downlink SE. Finally, with superimposed pilot-based channel estimation, the increase in the uplink sum SE is more pronounced when the channel delay spread is increased. [ABSTRACT FROM AUTHOR]

We consider the channel estimation and environment mapping problems in multiple-input multiple-output orthogonal frequency division multiplexing systems empowered by intelligent reconfigurable surfaces (IRSs). In order to acquire more in-depth environmental information, as well as, to flexibly take into account existing real-life infrastructure, we propose a novel three-dimensional conformal IRS architecture consisting of reflective unit cells distributed on curved surfaces. We model the training signal as a third-order canonical polyadic tensor and construct a tensor factorization problem. Given specific conditions on the allocated temporal-frequency training resources, we develop four channel estimation approaches, i.e., least squares, direct, wideband direct and wideband subspace methods, by leveraging tensor techniques and nonlinear system solvers. By fully exploiting the characteristics of conformal IRSs, we propose two decoupling modes to precisely recover the multipath parameters without ambiguities, which cannot be supported by the traditional IRS planar topologies. We implement scatterer mapping and user positioning tasks based on precise parameter estimates. Simulation results indicate that the proposed conformal IRS structure and estimation schemes can recover the channel state information with remarkable accuracy, thereby offering a centimeter-level resolution of environment mapping. [ABSTRACT FROM AUTHOR]

Thanks to its low transceiver complexity, mode division multiplexing (MDM) using orbital angular momentum (OAM) has been recently investigated as a new physical layer wireless transmission technique. This is due to the fact that different OAM modes are spatially orthogonal to each other, thus, perfectly suitable for spatial multiplexing and/or diversity. The orthogonality amongst different OAM modes is achieved in the absence of any mode offset between the transceivers’ phase-shifting feeding networks. However, the inherent presence of OAM mode offset destroys the orthogonality between different modes, which gives rise to inter-mode interference (IMI). Therefore, in this paper, in order to theoretically analyze the negative impact of OAM mode offset of MDM-OAM systems on the spectral efficiency of line-of-sight free-space wireless communication systems, an explicit signal-to-interference-plus-noise ratio expression for each OAM mode is derived, through which the spectral efficiency degradation is evaluated. Furthermore, in order to support our theoretical analysis, a $9\times 9$ MDM-OAM practical communication experiment for different OAM mode settings is carried out at a microwave frequency of 5.8 GHz. In addition, by leveraging the fact that all circulant matrices always have the same eigendirections, regardless of the entries of the matrix, a low-complexity optimal OAM mode selection scheme is proposed which significantly improves the spectral efficiency of the system. Finally, in order to completely null-out the impact of OAM mode offset, a baseband zero-forcing stage is embedded at the receiver. [ABSTRACT FROM AUTHOR]

In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. The level of hardware impairments (HWIs) indicates how strong the signal distortion introduced by hardware imperfections is. In particular, the analog-to-digital converters (ADCs) have an important impact on signal distortion and power consumption. This article addresses the fundamental problem of selecting the optimal hardware quality in the Massive MIMO space. In particular, we examine the optimal HWI and ADC bit allocation per BS antenna to maximize the SE. The results show that in co-located arrays with low channel gain variations across antennas, equal ADC bit allocation is optimal. In contrast, cell-free Massive MIMO systems benefit the most from optimizing the ADC bit allocation achieving improvements in the order of 2 [bit-per-channel-use] per user equipment when using regularized zero-forcing (RZF). In addition, when including the impact of power consumption in cell-free Massive MIMO with RZF, allocating low values of mixed ADC bit resolutions across the BS antennas can increase the energy efficiency up to 30% compared to equal ADC bit allocation. [ABSTRACT FROM AUTHOR]

With the inherent benefits, such as, better cell coverage and higher area throughput, extra-large scale massive multiple-input multiple-output (MIMO) has great potential to be one of the key technologies for the next generation wireless communication systems. However, in practice, when the antenna dimensions grow large, spatial non-stationarities occur and users will only see a portion of the base station antenna array, which we call visibility region (VR). To assess the impact of spatial non-stationarities, in this paper, we investigate the uplink transmission of extra-large scale massive MIMO systems by considering VRs. In particular, we first propose a subarray-based system architecture for extra-large scale massive MIMO systems. Then, tight closed-form uplink spectral efficiency (SE) approximations with linear receivers are derived. With the objective of maximizing the achievable SE, we also propose schemes for the subarray phase coefficient design. In addition, based on the obtained ergodic achievable SE approximations, two statistical channel state information (CSI)-based greedy user scheduling algorithms are developed. Our results indicate that the statistical CSI-based greedy joint user and subarray scheduling algorithm collaborating with the on-off switch-based subarray architecture is a promising practical solution for extra-large scale massive MIMO systems. [ABSTRACT FROM AUTHOR]

The concept of large intelligent surface (LIS)-based communication has recently raised research attention, in which a LIS is regarded as an antenna array whose entire surface area can be used for radio signal transmission and reception. To provide a fundamental understanding of LIS-based communication, this paper studies the uplink (UL) performance of LIS-based communication with matched filtering. We first investigate the new properties introduced by LIS. In particular, the array gain, spatial resolution, and the capability of interference suppression are theoretically presented and characterized. Then, we study two possible LIS system layouts in terms of UL, i.e., centralized LIS (C-LIS) and distributed LIS (D-LIS). Our analysis showcases that a centralized system has strong capability of interference suppression; in fact, interference can nearly be eliminated if the surface area is sufficient large or the frequency band is sufficient high. For D-LIS, we propose a series of resource allocation algorithms, including user association scheme, orientation control, and power control, to extend the coverage area of a distributed system. Simulation results show that the proposed algorithms significantly improve the system performance, and even more importantly, we observe that D-LIS outperforms C-LIS in microwave bands, while C-LIS is superior to D-LIS in mmWave bands. These observations serve as useful guidelines for practical LIS deployments. [ABSTRACT FROM AUTHOR]

Although uplink (UL) downlink (DL) decoupling (DUDe) brings significant gains in the UL throughput of decoupled user equipments (DeUEs) in heterogeneous networks, channel estimation and DL performance of DeUEs are worse than the coupled UEs due to the DUDe property and the cell edge effect. To address these fundamental problems, we propose a transmission scheme with data-aided (DA) minimum mean square error (MMSE) channel estimator and zero-forcing (ZF) interference nulling (IN) precoding for a two-tier multi-cell HetNet with DUDe. We first present a method to estimate the bit error rate (BER) of UL data, then, derive the form of DA MMSE estimator, which utilizes decoded UL data, estimated BER and known UL training sequences to jointly estimate the DL channels of DeUEs. ZF IN precoding uses the estimated channels of DeUEs to cancel the nearest DL interference without any cooperation and message transmission. Also, we derive a tight approximation to the achievable DL rate of DeUEs and analyze the benefits of the DA estimator and ZF IN precoding. Our simulations show that DA MMSE estimator outperforms the conventional MMSE counterpart, while the proposed scheme improves the DL performance of both DeUEs and macro UEs, though the rate gain may be degraded by pilot contamination and inter-cell interference. [ABSTRACT FROM AUTHOR]

We consider the channel estimation problem in millimeter wave (mmWave) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems with hybrid analog-digital architectures. Leveraging the spatial- and frequency-wideband (dual-wideband) effects in massive MIMO scenarios, we derive a spatial-frequency channel model with dual-wideband effects that incorporates the multipath parameters, i.e., time delay, complex gain, angle of departure/arrival. We adopt a successive beam training scheme and formulate the training OFDM signal as a third-order low-rank tensor fitting a canonical polyadic (CP) model with factor matrices containing the channel parameters. Exploiting the Vandermonde nature of factor matrices, we propose a structured CP decomposition-based channel estimation strategy aided by the spatial smoothing method, where two dedicated algorithms with particular tensor modeling and parameter recovery operations are developed. The proposed scheme leverages standard linear algebra, and, hence, avoids the random initialization problem and iterative procedure. An analysis of the uniqueness condition of CP decomposition is also pursued. Simulation results indicate that the proposed strategy achieves enhanced estimation performance, which outperforms the traditional approaches in terms of accuracy, robustness and complexity. [ABSTRACT FROM AUTHOR]

This article considers a multi-pair massive multiple-input multiple-output relaying channel where $K$ single-antenna sources communicate with $K$ single-antenna destinations via the assistance of a decode-and-forward relay equipped with massive antenna arrays. The relay station uses maximum-ratio processing to decode the signals transmitted from the sources and precode the signals before broadcasting to the destinations. To perform maximum-ratio processing, the relay needs to know the channels to the sources and the destination. This is done during the training phase where all sources and destinations send pilot sequences to the relay. We consider a very general case in which the pilot sequences are arbitrary. An exact closed-form expression for the end-to-end spectral efficiency is derived taking into account the imperfect channel estimates with arbitrary power control coefficients. From the spectral efficiency formula, we formulate and propose to solve a max-min fairness power allocation. With this power control scheme, the spectral efficiency improves significantly, compared to the uniform power control. In particular, a simple greedy pilot assignment scheme is proposed to reduce the pilot contamination effect, and hence, improve the system performance under the limitations of training duration. [ABSTRACT FROM AUTHOR]

In this paper, we study a multi-pair two-way half-duplex decode-and-forward (DF) massive multiple-input multiple-output (MIMO) relaying system, in which multiple single-antenna user pairs can exchange information through a massive MIMO relay. For low-complexity processing, zero-forcing reception/zero-forcing transmission (ZFR/ZFT) is employed at the relay. First, we analytically study the large-scale approximations of the sum spectral efficiency (SE). Furthermore, we focus on three specific power scaling laws to study the trade-off between the transmit powers of each pilot symbol, each user and the relay, and also focus on how the transmit powers scale with the number of relay antennas, $M$ , to maintain a finite SE performance. Additionally, we consider a practical power consumption model to investigate the energy efficiency (EE), and illustrate the impact of $M$ and the interplay between the power scaling laws and the EE performance. Finally, we consider the system fairness via maximizing the minimum achievable SE among all user pairs. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface- (RIS) assisted mobile communication is a promising technological paradigm thanks to the attractive advantages of low cost and flexible control of electromagnetic waves. However, the low-cost features of RISs entail some fundamental challenges to the acquisition of channel state information (CSI), which is essential for the optimal RIS design. To tackle this problem, there have been extensive studies on CSI acquisition in RIS-assisted mobile communication systems, from the perspective of architectural improvement as well as specific mathematical solutions. This article aims to overview the existing works on CSI acquisition in RIS-assisted mobile communication systems. [ABSTRACT FROM AUTHOR]

We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas $M$ becomes sufficiently large. In addition, we study how the transmit power reduces with $M$ to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to $1/M^\alpha$ , $1/M^\beta$ , and $1/M^\gamma$ for certain combinations of $\alpha$ , $\beta$ , and $\gamma$ , respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE. [ABSTRACT FROM AUTHOR]

Hybrid transceiver designs for millimeter wave massive multiple-input multiple-output systems are feasible candidates to reduce the volume of radio frequency (RF) chains, decomposing the signal processing into the analog and digital domains. The existing schemes heavily depend on the singular value decomposition to obtain subchannels with uneven power gains, causing bit error rate (BER) performance degradation. In this paper, we propose a hybrid transceiver design based on the uniform channel decomposition (UCD), yielding subchannels with identical gains to improve the BER performance. Inspired by the UCD concept, we derive an equivalent optimization problem and propose two schemes, namely, phase-extraction and iterative update, to determine the RF beamformers, yielding an effective baseband channel with the greatest possible geometric mean of singular values. We apply the UCD with a minimum mean squared error criterion to complete the baseband beamforming. Finally, we combine the hybrid UCD beamforming with the vertical-Bell Labs layered space-time and dirty paper coding, to eliminate the inter-subchannel interference. An asymptotic analysis of the scheme performance is also pursued. The simulation results show that the proposed hybrid scheme outperforms the conventional schemes on the transmission BER, which achieves a spectral efficiency close to that of the fully-digital counterpart. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) avails of simple transceiver design which can tackle many drawbacks of relay systems in terms of complicated signal processing, latency, and noise amplification. However, the cost and circuit complexity of having one radio frequency (RF) chain dedicated to each antenna element are prohibitive in practice. In this paper, we address this critical issue in amplify-and-forward (AF) relay systems using a hybrid analog and digital (A/D) transceiver structure. More specifically, leveraging the channel long-term properties, we design the analog beamformer which aims to minimize the channel estimation error and remain invariant over a long timescale. Then, the beamforming is completed by simple digital signal processing, i.e., maximum ratio combining/maximum ratio transmission (MRC/MRT) or zero forcing (ZF) in the baseband domain. We present analytical bounds on the achievable spectral efficiency taking into account the spatial correlation and imperfect channel state information at the relay station. Our analytical results reveal that the hybrid A/D structure with ZF digital processor exploits spatial correlation and offers a higher spectral efficiency compared to the hybrid A/D structure with MRC/MRT scheme. Our numerical results show that the hybrid A/D beamforming design captures nearly 95% of the spectral efficiency of a fully digital AF relaying topology even by removing half of the RF chains. It is also shown that the hybrid A/D structure is robust to coarse quantization, and even with 2-bit resolution, the system can achieve more than 93% of the spectral efficiency offered by the same hybrid A/D topology with infinite resolution phase shifters. [ABSTRACT FROM AUTHOR]

We consider a multi-way decode-and-forward relaying network with very large antenna arrays at the relay station. In this system, each user and the relay operate in half-duplex and time-division duplexing modes. To exchange information among all users, we propose a new transmission protocol which combines massive multiple-input multiple-output technology with linear processing, self-interference cancelation, and successive cancelation decoding. Our proposed transmission protocol reduces the number of time-slots for data exchange among users by approximately 2 times, compared with the conventional data transmission protocol. For this new topology, we derive a very tight approximation of the spectral efficiency in closed-form assuming perfect channel state information (CSI). Then, a CSI acquisition method at the relay and the users is provided and analyzed. We show via numerical simulations, that the performance gap between imperfect and perfect CSI cases is small. The closed-form expression of the spectral efficiency enables us to design two power allocation schemes. In the first power allocation scheme, we choose the transmit powers at the users and the relay to maximize the sum spectral efficiency, subject to a given quality-of-service requirement for each user. In the second power allocation scheme, the objective is the energy efficiency taking into account the hardware power consumption. Both power allocation schemes can be efficiently executed by iteratively solving a sequence of convex problems. Numerical results verify the effectiveness of the proposed transmission protocol and the power allocation schemes compared with the state of the art. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for millimeter wave (mmWave) networks. In this paper, we utilize tools from stochastic geometry to study the performance of a RIS-assisted mmWave cellular network. Specifically, the locations of the base stations (BSs) and the midpoints of the blockage are modeled as two independent Poisson point processes (PPPs), where the blockages are modeled by a Boolean model and a fraction of the blockages are coated with RISs. The particular characteristics of mmWave communications, i.e., directional beamforming and different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation, are incorporated into our analysis. We derive analytical expressions for the success probability and the area spectral efficiency. The success probability under the special case where the blockage parameter is sufficiently small is also derived. Numerical results demonstrate that better coverage performance and higher energy efficiency can be achieved by a large-scale deployment of RISs. In addition, the tradeoff between the BS and RIS densities is investigated and the results show that the RISs can indeed enable the traditional networks to improve the success probability, especially for the cell-edge region, with limited power consumption. [ABSTRACT FROM AUTHOR]

The κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the κ−μ/ inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the η−μ/ inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-average distance. As a result, it is shown that the κ−μ/ inverse gamma composite fading model provides a better fit compared to the η−μ/ inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the η−μ/ inverse gamma composite fading model outperforms the κ−μ/ inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter η is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical. [ABSTRACT FROM AUTHOR]

Cell-free massive multiple-input multiple-output (MIMO) system is a promising architecture for next generation wireless systems by deploying a very large number of distributed access points (APs), which simultaneously serve a smaller number of user equipments (UEs) over the same time-frequency resources. It guarantees uniformly good service at high spectral efficiency with simple linear precoding techniques and max-min power control. In this article, we propose a new joint maximum-ratio and zero-forcing (JMRZF) precoding scheme, where part of APs are combined to perform centralized zero-forcing (ZF), while other APs apply simple maximum-ratio transmission (MRT). Our proposed precoder offers an adaptable trade-off between the spectral efficiency and front-haul signalling overhead. A corresponding AP subset selection scheme is also proposed which is based on large-scale fading coefficients. A closed-form expression for the achievable spectral efficiency of our proposed scheme is derived, which represents a generalized result including both fully distributed MRT and fully centralized ZF cases. Based on this closed-form expression, max-min power control is formulated and solved via the second order cone and first order methods. The former can obtain the global optimal solution, but its computational complexity is very high. On the other hand, the latter technique is sub-optimal, yet, it has very low computational complexity. Hence, it is suitable for large-scale cell-free massive MIMO systems with hundreds or thousands of APs and users. Numerical results show that our proposed JMRZF scheme can substantially outperform the local precoding schemes, even when a small part of APs are combined to deploy ZF and is implementable even when each AP has very few antennas. In addition, it is shown that our max-min power controls improves the spectral efficiency significantly, compared to the uniform power control scheme. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) communications have attracted considerable interest due to the massive available spectrum. However, to establish communication links, a beam training procedure is indispensable. How to accelerate the beam training process is one of the key challenges towards realizing mmWave communications in practice. In this study, we first propose a novel low-cost digital beamforming (DBF) module assisted hybrid (DA-hybrid) architecture, by exploiting both the capabilities of analog and digital modules. To make this topology practical, we deploy coarse radio frequency (RF) chains and low-resolution analog-to-digital converters in the low-cost DBF module to reduce cost and power consumption. Second, we design a fast beam training method (named DAH-BT) by utilizing the proposed DA-hybrid architecture and leveraging the sparse nature of mmWave channels, in which an internal calibration method is adapted to obtain the parameters of the RF impairments and the orthogonal matching pursuit algorithm is utilized to estimate beams. We also prove that the developed measurement matrices satisfy the restricted isometry property. Extensive simulation results show that the DA-hybrid architecture can not only provide close to $\text{100}\%$ beam matching accuracy, but also dramatically reduce the system power consumption and cost. In addition, the proposed DAH-BT scheme consumes the shortest time for beam training over the state-of-art methods with comparable spectral efficiency. [ABSTRACT FROM AUTHOR]

It is well established that the utilization of unused millimeter-wave (mmWave) spectrum is inevitable due to unavailability of required bandwidth in the conventional RF band to support the high data demands of 5G. Large antenna arrays with beamforming capabilities are required to compensate for the high path loss at mmWave frequencies. We are at the verge of a massive mmWave radio front-end deployment, and low-complexity low-cost hardware beamforming solutions are required now at this stage than ever before. In this paper, one such solution is demonstrated and analyzed. A high-performance and low-complexity lens-based beamformer consisting of constant dielectric material ($\epsilon _{r}$) with antenna feeds is presented for multibeam operation. A prototype is developed based on the classical synthesis approach, and in line with the requirements of mmWave hybrid multiuser multiple-input multiple-output (MU-MIMO) systems. A characterization at 28 GHz is performed wherein an uplink signal-to-noise ratio of user terminals is evaluated with the zero-forcing (ZF) baseband signal processing. Radiation performance of a single-source beamformer is measured in an anechoic environment, and end-to-end ergodic sum spectral efficiency performance is estimated based on the measured data. It is shown that the constant- $\epsilon _{r}$ -based beamformer solution is simple, yet significantly outperforms conventional antenna array beamformers with analog phase shifter networks, making it a promising candidate for future hybrid massive MIMO systems. [ABSTRACT FROM AUTHOR]

Ultra-dense cloud radio access networks (C-RANs) are an example of the architectures that will be critical components of the next-generation wireless systems. In a C-RAN architecture, an amorphous cellular framework, where each user connects to a few nearby remote radio heads (RRHs) to form its own cell, appears to be promising. In this paper, we study the ergodic capacity of such amorphous cellular networks at high signal-to-noise ratios (SNRs) where we model the distribution of the RRHs by a Poisson point process. We derive tractable approximations of the ergodic capacity at high-SNRs for arbitrary antenna configurations, and tight lower bounds for the ergodic capacity when the numbers of antennas are the same at both ends of the link. In contrast to prior works on distributed antenna systems, our results are derived based on random matrix theory and involve only standard functions which can be much more easier evaluated. The impact of the system parameters on the ergodic capacity is investigated. By leveraging our analytical results, we propose two efficient scheduling algorithms for RRH selection for energy-efficient transmission. Our algorithms offer a substantial improvement in energy efficiency compared with the strategy of connecting a fixed number of RRHs to each user. [ABSTRACT FROM AUTHOR]

In this paper, we propose a relative channel estimation error (RCEE) metric, and derive closed-form expressions for its expectation \rm Exprcee and the achievable uplink rate holding for any number of base station antennas $M$ , with the least squares (LS) and minimum mean squared error (MMSE) methods. It is found that RCEE and \rm Exprcee converge to the same constant value when $M\rightarrow \infty $ , which renders the pilot power allocation (PPA) substantially simplified and a PPA algorithm is proposed to minimize the average \rm Exprcee per user under a total pilot power budget $P$ in multi-cell massive multiple-input multiple-output systems. Numerical results show that the PPA algorithm brings considerable gains for the LS estimation compared with equal PPA (EPPA), while the gains are significant only with large frequency reuse factor (FRF) for the MMSE estimation. Moreover, for large FRF and large $P$ , the performance of the LS approaches to that of the MMSE. Besides, a scheduling strategy is proposed to allocate pilot power in the whole system, which can approach the optimal performance. For the achievable uplink rate, the PPA scheme and improves the minimum achievable uplink rate compared with the EPPA scheme. [ABSTRACT FROM AUTHOR]

This paper presents an analytical performance investigation of both beamforming (BF) and interference cancellation (IC) strategies for a device-to-device (D2D) communication system underlaying a cellular network with an $M$-antenna base station (BS). We first derive new closed-form expressions for the ergodic achievable rate for BF and IC precoding strategies with quantized channel state information (CSI), as well as, perfect CSI. Then, novel lower and upper bounds are derived which apply for an arbitrary number of antennas and are shown to be sufficiently tight to the Monte-Carlo results. Based on these results, we examine in detail three important special cases including: high signal-to-noise ratio (SNR), weak interference between cellular link and D2D link, and BS equipped with a large number of antennas. We also derive asymptotic expressions for the ergodic achievable rate for these scenarios. Based on these results, we obtain valuable insights into the impact of the system parameters, such as the number of antennas, SNR and the interference for each link. In particular, we show that an irreducible saturation point exists in the high SNR regime, while the ergodic rate under IC strategy is verified to be always better than that under BF strategy. We also reveal that the ergodic achievable rate under perfect CSI scales as {\log _2}M, whilst it reaches a ceiling with quantized CSI. [ABSTRACT FROM AUTHOR]

This paper investigates the achievable sum-rate of massive multiple-input multiple-output (MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base station (BS) deploys maximum ratio combining (MRC) or zero-forcing (ZF) receivers, we present tight closed-form lower bounds on the achievable sum-rate for both receivers with aged channel state information (CSI). In addition, the benefit of implementing channel prediction methods on the sum-rate is examined, and closed-form sum-rate lower bounds are derived. Moreover, the impact of channel aging and channel prediction on the power scaling law is characterized. Extension to the downlink scenario and multicell scenario is also considered. It is found that, for a system with/without channel prediction, the transmit power of each user can be scaled down at most by 1/\sqrtM (where $M$ is the number of BS antennas), which indicates that aged CSI does not degrade the power scaling law, and channel prediction does not enhance the power scaling law; instead, these phenomena affect the achievable sum-rate by degrading or enhancing the effective signal to interference and noise ratio, respectively. [ABSTRACT FROM AUTHOR]

We investigate the cell coverage optimization problem for the massive multiple-input multiple-output (MIMO) uplink. By deploying tilt-adjustable antenna arrays at the base stations (BSs), cell coverage optimization can become a promising technique that is able to strike a compromise between covering cell-edge users and pilot contamination suppression. We formulate a detailed description of this optimization problem by maximizing the cell throughput, which is shown to be mainly determined by the user distribution within several key geometrical regions. Then, the formulated problem is applied to different example scenarios. For a network with hexagonal cells and uniformly distributed users, we derive an analytical lower bound of the ergodic throughput in the objective cell; based on this, it is shown that the optimal choice for the cell coverage should ensure that the coverage of different cells does not overlap. For a more generic network with sector-shaped cells and nonuniformly distributed users, we propose an analytical approximation of the ergodic throughput. After that, a practical coverage optimization algorithm is proposed, where the optimal solution can be easily obtained through a simple 1-D line searching within a confined searching region. Our numerical results show that the proposed coverage optimization method is able to greatly increase the system throughput in macrocells for the massive MIMO uplink transmission, compared with the traditional schemes where the cell coverage is fixed. [ABSTRACT FROM PUBLISHER]

We study multicarrier multiuser multiple-input multiple-output (MU-MIMO) systems, in which the base station employs an asymptotically large number of antennas. We analyze a fully correlated channel matrix and provide a beam domain channel model, where the channel gains are independent of sub-carriers. For this model, we first derive a closed-form upper bound on the achievable ergodic sum-rate, based on which, we develop asymptotically necessary and sufficient conditions for optimal downlink transmission that require only statistical channel state information at the transmitter. Furthermore, we propose a beam division multiple access (BDMA) transmission scheme that simultaneously serves multiple users via different beams. By selecting users within non-overlapping beams, the MU-MIMO channels can be equivalently decomposed into multiple single-user MIMO channels; this scheme significantly reduces the overhead of channel estimation, as well as, the processing complexity at transceivers. For BDMA transmission, we work out an optimal pilot design criterion to minimize the mean square error (MSE) and provide optimal pilot sequences by utilizing the Zadoff-Chu sequences. Simulations demonstrate the near-optimal performance of BDMA transmission and the advantages of the proposed pilot sequences. [ABSTRACT FROM PUBLISHER]