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This paper provides an analytical performance characterization of both the uplink (UL) and downlink (DL) user-centric network multiple-input multiple-output (MIMO) systems, where a cooperating base station (BS) cluster is formed for each user individually and the clusters for different users may overlap. In this model, cooperating BSs (each equipped with multiple antennas) jointly perform zero-forcing beamforming to the set of single-antenna users associated with them. As compared with a baseline network MIMO system with disjoint BS clusters, the effect of user-centric clustering is that it improves signal strength in both the UL and DL, while reducing cluster-edge interference in the DL. This paper quantifies these effects by assuming that BSs and users form Poisson point processes and by further approximating both the signal and interference powers using Gamma distributions of appropriate parameters. We show that BS cooperation provides significant gain as compared to single-cell processing for both the UL and DL, but the advantage of user-centric clustering over the baseline disjoint clustering system is significant for the DL cluster-edge users only. Although the analytic results are derived with the assumption of perfect channel state information and infinite backhaul between the cooperating BSs, they nevertheless provide architectural insight into the design of the future cooperative cellular networks. [ABSTRACT FROM AUTHOR]

Molecular communication via diffusion (MCvD) is a molecular communication method that utilizes the free diffusion of carrier molecules to transfer information at the nanoscale. Due to the random propagation of carrier molecules, intersymbol interference (ISI) is a major issue in an MCvD system. Alongside ISI, interlink interference (ILI) is also an issue that increases the total interference for the MCvD-based multiple-input-multiple-output (MIMO) approaches. Inspired by the antenna index modulation (IM) concept in traditional communication systems, this paper introduces novel IM-based transmission schemes for MCvD systems. In this paper, molecular space shift keying (MSSK) is proposed as a novel modulation for molecular MIMO systems, and it is found that this method combats ISI and ILI considerably better than the existing MIMO approaches. For nanomachines that have access to two different molecules, the direct extension of MSSK, quadrature MSSK (QMSSK) is also proposed. QMSSK is found to combat ISI considerably well while not performing well against ILI-caused errors. In order to combat ILI more effectively, another dual-molecule-based novel modulation scheme called the molecular spatial modulation (MSM) is proposed. Combined with the Gray mapping imposed on the antenna indices, MSM is observed to yield reliable error rates for molecular MIMO systems. [ABSTRACT FROM AUTHOR]

This paper presents the system design, calibration, and example measurements of a novel ultra-wideband, low-cost, real-time channel sounder. The channel sounder operates in the frequency range from 3 to 18 GHz with a 15-GHz bandwidth thus providing a Fourier delay resolution of 66.7 ps. It sequentially measures overlapping sub-bands of 1-GHz bandwidth to cover the whole frequency range. By using a waveform generator and a digitizer with relatively lower sample rates, the design significantly lowers the cost compared with sampling the whole band simultaneously. With the transmitting power of 40 dBm, the maximum measurable path loss is 132 dB without accounting for possible antenna gains. In this paper, we also describe the calibration procedure along with the method to stitch sub-bands into a combined channel response across 15 GHz of bandwidth. The channel sounder performance is compared with a vector network analyzer (VNA) measurements acquired in the same static channels. In contrast to VNAs, however, our channel sounder can measure the whole band in 6 ms and can, thus, operate in dynamic environments with coherence time more than 6 ms. Additionally, we present sample results from a measurement campaign performed in an indoor corridor investigating the delay spreads statistics over the range of 3–18 GHz. [ABSTRACT FROM AUTHOR]

In this paper, we consider a simple coding scheme for spatial modulation, where the same set of active transmit antennas is repeatedly used over consecutive multiple transmissions. Based on a Gaussian approximation, an approximate maximum likelihood (ML) detection problem is formulated to detect the indices of active transmit antennas. We show that the solution to the approximate ML detection problem can achieve a full coding gain. Furthermore, we develop a low-complexity iterative algorithm to solve the problem with low complexity based on a well-known machine learning approach, i.e., variational inference. Simulation results show that the proposed algorithm can have a near ML performance. A salient feature of the proposed algorithm is that its complexity is independent of the number of active transmit antennas, whereas an exhaustive search for the ML problem requires a complexity that grows exponentially with the number of active transmit antennas. [ABSTRACT FROM AUTHOR]

The matched-filter (MF) detector is the lowest complexity linear detector in practical MIMO spatial multiplexing systems. Its performance is significantly affected by the number of available antennas and an operating channel SNR. In this paper, we analyze the exact performance of the MF detector without any restrictions on the numbers of the transmit and receive antennas. To this end, we first develop the exact, closed-form expression of the MF detector output over uncorrelated Rayleigh fading channels with an arbitrary number of antennas. Based on this result, we derive the exact closed-form bit error rate expressions for uncoded BPSK, QPSK, and $M$ -ary QAM signaling, which can be seen as the generalized forms of the conventional receiver diversity based on maximum ratio combining. We also elucidate the conditions on the numbers of antennas and channel SNR, where the use of MF detector should become effective. Furthermore, in the case of coded MIMO systems, we develop the optimal metric derived from the exact MF output. The corresponding mutual information justifies the simulated performance of LDPC-encoded MIMO spatial multiplexing with the MF detector over ideally interleaved Rayleigh fading channels. Finally, we extend our analysis to more practical systems with imperfect channel estimation. [ABSTRACT FROM AUTHOR]

Physical layer network coding (PNC) has been studied to serve wireless network MIMO systems with much lower backhaul load than approaches such as Cloud Radio Access Network (Cloud-RAN) and coordinated multipoint (CoMP). In this paper, we present a design guideline of engineering applicable PNC to fulfil the request of high user densities in 5G wireless RAN infrastructure. We show that the proposed design criteria guarantee that: 1) the whole system operates over binary system; 2) the PNC functions utilized at each access point overcome all singular fade states; and 3) the destination can unambiguously recover all source messages, while the overall backhaul load remains at the lowest level. We then develop a two-stage search algorithm to identify the optimum PNC mapping functions which greatly reduces the real-time computational complexity. The impact of estimated channel information and reduced number of singular fade states in different QAM modulation schemes are studied in this paper. Numerical results show that the proposed schemes achieve low outage probability with reduced backhaul load. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptively scaled belief (ASB) in Gaussian belief propagation (GaBP) designed for use in large multi-user multi-input multi-output (MU-MIMO) detection under higher order modulation schemes. In practical MU-MIMO systems, the dominant factor in the poor convergence of GaBP iterative detection is approximation errors arising from the fact that the law of large numbers does not work well in many such applications as a result of physical system limitations. Unfortunately, the approximation errors become more severe when there is higher correlation among typical bit-wise prior beliefs when higher order quadrature amplitude modulation schemes are used. To cope with the impairments arising from inter-bit correlation, symbol-wise beliefs can be defined for GaBP self-iterative detection, although this still does not remove approximation errors. As a simple method for mitigating the harmful effects of approximation error, this paper proposes a novel method for adaptive belief scaling while stabilizing the dynamics of random MIMO channels. Based on the functionality of ASB, we also propose a method for approximately calculating conditional expectations with lower computational complexity without sacrificing detection capability. Finally, the validity of using ASB for symbol-wise iterative detection in suppressing the bit-error-rate floor level is confirmed. [ABSTRACT FROM AUTHOR]

This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with a focus on massive multiple input multiple output (MIMO). This distortion is correlated across the antennas but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of distortion correlation are first uncovered. Then, we separately analyze the distortion correlation caused by third-order non-linearities and by quantization. Finally, we study the SE numerically and show that the distortion correlation can be safely neglected in massive MIMO when there are sufficiently many users. Under independent identically distributed Rayleigh fading and equal signal-to-noise ratios (SNRs), this occurs for more than five transmitting users. Other channel models and SNR variations have only minor impact on the accuracy. We also demonstrate the importance of taking the distortion characteristics into account in the receive combining. [ABSTRACT FROM AUTHOR]

The availability of accurate channel state information (CSI) is essential in multiuser massive multiple-input multiple-output (MIMO) systems. However, most published works focus on frequency-flat channel estimation which requires that the estimation must be repeated for every frequency slot, e.g., subcarrier, in a broadband system. Since the channels in the frequency-domain are the Fourier transform of a small set of time-domain channel coefficients, the time-domain channel estimation requires that fewer parameters be estimated. In this paper, we propose a semi-blind, time-domain, channel estimation technique for frequency-selective massive MIMO systems. Our solution depends on the subspace spanned by the signal eigenvectors of the received signal covariance matrix. Importantly, since the receiver samples at the symbol rate, time-domain-based estimation inherently has available enough samples for an accurate matrix estimate. To avoid asymptotic assumptions, we express each channel vector as a linear combination of the signal eigenvectors. We estimate the linear combination using a set of training symbols. Given the many samples of the received signal in the time-domain, we obtain a better channel estimate compared to conventional subcarrier-wise frequency-domain channel estimation. Unlike the previous published results, in this paper, we do not assume orthogonality of users’ channels or knowledge of large-scale fading coefficients. In addition, our estimation procedure does not require orthogonality between the training symbols of the users in all cells. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) technology equips the transmitters with the multiple antennas. It can combine with energy harvesting (EH) to lift the spectrum efficiency and make use of a greener energy resource. A power grid is added to serve as a supplementary source to regulate the not-so-stable harvested energy supply of the system. Besides the MIMO technology being used, the power allocated to the user provided by both EH and the power grid is subject to the epoch power upper bound constraints. The background of these constraints comes from field requirements, such as avoiding the saturation of power allocated to the user(s), avoiding system-level out-of-band power leakage, and reducing interference with other transmitter(s) due to the non-linearity generated via the transmitting mechanisms to the user(s). The epoch power upper bound constraints make this problem more challenging, with the controllable power grid energy budget and its allocation. This paper applies our recently proposed geometric water-filling with group upper bounded power constraints and recursion machinery to form the proposed algorithm for solving the proposed throughput maximization problem. Our algorithm is precisely defined, and further provides the exact solution via the lower degree polynomial complexity. This point is very suitable for the massive MIMO system. To the best of our knowledge, no prior algorithm has been reported in the open literature to solve the targeted problem in this paper. [ABSTRACT FROM PUBLISHER]

Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key concepts are adopted into the 5G New Radio Standard and base stations (BSs) with $M=64$ fully digital transceivers have been commercially deployed in sub-6GHz bands. The fast progress was enabled by many solid research contributions of which the vast majority assume spatially uncorrelated channels and signal processing schemes developed for single-cell operation. These assumptions make the performance analysis and optimization of Massive MIMO tractable but have three major caveats: 1) practical channels are spatially correlated; 2) large performance gains can be obtained by multicell processing, without BS cooperation; 3) the interference caused by pilot contamination creates a finite capacity limit, as $M\to \infty $. There is a thin line of papers that avoided these caveats, but the results are easily missed. Hence, this tutorial article explains the importance of considering spatial channel correlation and using signal processing schemes designed for multicell networks. We present recent results on the fundamental limits of Massive MIMO, which are not determined by pilot contamination but the ability to acquire channel statistics. These results will guide the journey towards the next level of Massive MIMO, which we call “Massive MIMO 2.0”. [ABSTRACT FROM AUTHOR]

This paper considers precoding for multi-group multicasting with a common message. The multiple antenna base station communicates with $K$ clusters, each with $L$ users. There is a common message destined to all users and a private multicast message for each cluster. We study the weighted sum rate (WSR) maximization problem for two different schemes: 1) the base station transmits the superposition of common and multicast messages and 2) the base station concatenates the multicast message vector with the common message. We also formulate a second problem, weighted minimum mean square error (WMMSE) minimization, and prove that WSR maximization and WMMSE minimization are equivalent at the optimal solution. Inspired by the WMMSE problem, we suggest a suboptimal algorithm, based on alternating optimization. We apply this algorithm to the two transmission schemes and understand that there is a fundamental difference between the two. We compare the results with maximal ratio transmission (MRT) and zero-forcing (ZF) precoding and investigate the effects of the number of base station antennas, the number of groups, and the number of users in a group. Finally, we study imperfect successive interference cancellation (SIC) at the receivers and show that the first transmission scheme is more robust. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS), which consists of many low-cost reflecting elements, can enhance the reception of the desired signal and suppress the interference. Considering the above advantages, this paper investigates the RIS-assisted wireless communication in the presence of an interferer, where a receiver receives the desired signal and interference from a transmitter and an interferer, respectively, and the RIS is deployed to assist this system. First, an interference-limited channel capacity maximization problem is formulated, and a numerical algorithm based on the fraction programming and optimality conditions is proposed to obtain the optimal solution. Then, this paper shows the upper boundary of the maximal capacity with interference and discusses what kind of channel conditions can achieve the upper boundary and the corresponding optimal phase shifts. Next, this paper analyzes the asymptotic behaviors of the maximal capacity in the scenarios that some or all of the number of reflecting elements, antennas at the transmitter, and interferer go to infinity. Finally, this paper generalizes the above results to the multiple interferers scenario. [ABSTRACT FROM AUTHOR]

We consider the problem of differentiated rate scheduling for the downlink (i.e., multi-antenna broadcast channel), in the sense that the rates required by different users must satisfy certain constraints on their ratios. When full channel state information (CSI) is available at the transmitter and receivers, the problem can be readily solved using dirty paper coding (DPC) and the application of convex optimization techniques on the dual problem which is the multiple access channel (MAC). Since in many practical application full CSI may not be feasible and computational complexity prohibitive when the number of users is large, we focus on other simple schemes that require very little CSI: time-division opportunistic (TO) beamforming where in different time slots (of different lengths) the transmitter performs opportunistic beamforming to .the users requiring the same rate, and weighted opportunistic (WO) beamforming where the random beams are assigned to those users having the largest weighted SINR. For single antenna systems we also look at the capacity-achieving superposition coding (SC) scheme. In all cases, we determine explicit schedules to guarantee the rate constraints and show that, in the limit of large number of users, the throughput loss compared to the unconstrained throughput (sum-rate capacity) tends to zero. We further provide bounds on the rate of convergence of the sum-rates of these schemes to the sum-rate capacity. Finally, we provide simulation results of the performance of different scheduling schemes considered in the paper. [ABSTRACT FROM AUTHOR]

As a new energy saving approach for green communications, energy harvesting (EH) could be suitable technique to facilitate massive connections for large number of devices in such networks. The spectrum shortage occurs in huge number of devices which access with small-cell and macro-cell networks. To tackle these challenges, we develop a tractable framework relying on prominent techniques such as non-orthogonal multiple access (NOMA), antenna selection and energy harvesting. In this paper, we aim at practical scenarios of small cell networks by jointly evaluating capable of interference management and EH. We benefit from transmission approaches including full duplex (FD) and bi-directional transmission to improve the main performance system metrics such as outage probability and throughput. Three useful schemes are explored by considering EH and inter-cell interference. We derive the closed-form and asymptotic expressions for system metrics. We then perform extensive simulations with different system configurations to confirm the effectiveness of the proposed small-cell NOMA systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate secure transmission over the large-scale multiple-antenna wiretap channel with finite alphabet inputs. First, we investigate the case where instantaneous channel state information (CSI) of the eavesdropper is known at the transmitter. We show analytically that a generalized singular value decomposition (GSVD)-based design, which is optimal for Gaussian inputs, may exhibit a severe performance loss for finite alphabet inputs in the high signal-to-noise ratio regime. In light of this, we propose a novel Per-Group-GSVD (PG-GSVD) design, which can effectively compensate the performance loss caused by the GSVD design. More importantly, the computational complexity of the PG-GSVD design is by orders of magnitude lower than that of the existing design for finite alphabet inputs while the resulting performance loss is minimal. Then, we extend the PG-GSVD design to the case where only statistical CSI of the eavesdropper is available at the transmitter. Numerical results indicate that the proposed PG-GSVD design can be efficiently implemented in large-scale multiple-antenna systems and achieves significant performance gains compared with the GSVD design. [ABSTRACT FROM PUBLISHER]

In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems. In particular, we analyze different hardware architectures for implementing the RF switching matrices required in AS designs with a reduced number of RF chains. We explicitly show that fully-flexible switching matrices, which facilitate the selection of any possible subset of antennas and attain the maximum theoretical sum rates of AS, present numerous drawbacks such as the introduction of significant insertion losses, particularly pronounced in massive multiple-input multiple-output (MIMO) systems. Since these disadvantages make fully-flexible switching suboptimal in the energy efficiency sense, we further consider partially-connected switching networks as an alternative switching architecture with reduced hardware complexity, which we characterize in this work. In this context, we also analyze the impact of reduced switching connectivity on the analog hardware and digital signal processing of AS schemes that rely on received signal power information. Overall, the analytical and simulation results shown in this paper demonstrate that partially-connected switching maximizes the energy efficiency of massive MIMO systems for a reduced number of RF chains, while fully-flexible switching offers sub-optimal energy efficiency benefits due to its significant switching power losses. [ABSTRACT FROM PUBLISHER]

This paper studies the behavior of the sum-rate of outdoor multi-user multiple input multiple output systems, where a uniform linear array is utilized at the base station (BS), as the number of BS antennas and the number of users increase. Two schemes are studied for the downlink, the zero-forcing and the maximum ratio transmission (MRT). To begin with, the channel matrix is described deterministically using direct scattering theory. Its matrix elements are the Fourier coefficients of functions that have a physical significance, being connected to the geometry of the environment. For the case when the energy is not arriving at the BS from every spatial direction, we prove for the ZF scheme that the achievable sum-rate behavior is sublinear in the number of antennas at the BS. For the MRT scheme, we prove that there is a link between the sum-rate and the distribution of the users in the city. To numerically evaluate the sum-rate for a given city, schematically described by its streets and its buildings, we introduce a model for the Fourier coefficients of the aforementioned functions, which mixes geometrical and statistical ingredients. We randomly distribute high buildings that will act as strong scatterers and look at the influence of their number on the sum-rate. With the ZF scheme, we perform the calculations for the case where the number of BS antennas, MT , is equal to the number of users, MR, and for the case where MT is larger than MR . We observe that the sum-rate first increases linearly with the number of BS antennas, and becomes sublinear after MT reaches a certain value. The threshold depends on the number of high buildings. With the MRT scheme, the calculations confirm the theoretical predictions, and the sum-rate is greater if the users are spread over all of the city. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the uplink of massive MIMO systems where the channel capacity is almost deterministic and varies slowly over time. We exploit this fact, by appropriately choosing the length of the codeword only once based on an initial estimate of the uplink channel capacity fed back by the base station (BS). The user terminal (UT) then transmits the codeword over consecutive coherence time intervals without waiting for any acknowledgement (ACK/NACK) from the BS. The BS sends only a single ACK/NACK after it completes decoding. Therefore, the proposed method has significantly less latency and signaling overhead when compared with stop-and-wait type hybrid automatic repeat request (HARQ) methods (as in LTE uplink) where a lot of delay is introduced as the UT needs to wait for the BS to signal the ACK/NACK for every retransmission. Analysis reveals that for sufficiently large number of antennas at the BS, the average codeword length of the proposed method (in number of coherence intervals) is the same as the average number of retransmissions (in number of coherence intervals) required by incremental redundancy (IR)-based HARQ and also that the energy efficiency of the proposed method and IR-HARQ is the same. [ABSTRACT FROM AUTHOR]

In this paper, we consider the uplink channel parameter estimation problem in the presence of pilot contamination for massive multiple-input-multiple-output (MIMO) systems. We propose a parallel factor (PARAFAC)-based estimation scheme, which exploits the low-rank property of massive MIMO channels caused by the finite scattering in a physical environment. Specifically, we first parameterize the channel in terms of three parameters, i.e., fading coefficients, directions of arrival (DOAs), and delays; thereby, the channel is characterized via three equivalent PARAFAC models. Then, the proposed PARAFAC-based scheme is developed, which jointly estimates these three channel parameters using an alternating least squares (ALS) algorithm. Therein, we certify the identifiability of the three channel parameters of the PARAFAC models to mitigate the pilot contamination and state the convergence of the ALS algorithm, which guarantees that the three channel parameters can be uniquely determined with the proposed scheme. Moreover, to further reduce the computational complexity, two advanced schemes are proposed by antenna selection and reducing the estimation frequency of DOAs and delays, respectively. Simulation results show that the proposed schemes can achieve both low computational complexities and close to optimal Cramer–Rao Bound performance. [ABSTRACT FROM AUTHOR]

In this paper, we present the error performance analysis of a multiple-input multiple-output (MIMO) physical-layer network coding (PNC) system with two different user-antenna selection (AS) schemes in asymmetric channel conditions. For the first antenna selection scheme (AS1), where the user antenna is selected in order to maximize the overall channel gain between the user and the relay, we give an explicit analytical proof that for binary modulations, the system achieves full diversity order of $\min ({N}_{{A}}, {N}_{{B}}) \times {N}_{{R}}$ in the multiple-access (MA) phase, where $N_{A}, N_{B}$ , and $N_{R}$ denote the number of antennas at user ${A}$ , user ${B}$ , and relay ${R}$ , respectively. We present a detailed investigation of the diversity order for the MIMO-PNC system with AS1 in the MA phase for any modulation order. A tight closed-form upper bound on the average SER is also derived for the special case when ${N}_{{R}} = {1}$ , which is valid for any modulation order. We show that in this case, the system fails to achieve transmit diversity in the MA phase, as the system diversity order drops to 1 irrespective of the number of transmit antennas at the user nodes. Additionally, we propose a Euclidean distance (ED) based user-antenna selection scheme (AS2) that outperforms the first scheme in terms of error performance. Moreover, by deriving upper and lower bounds on the diversity order for the MIMO-PNC system with AS2, we show that this system enjoys both transmit and receive diversity, achieving full diversity order of $\min ({N}_{{A}}, {N}_{{B}}) \times {N}_{{R}}$ in the MA phase for any modulation order. Monte Carlo simulations are provided which confirm the correctness of the derived analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we propose computationally efficient yet near-optimal soft-output detection methods for coded millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) systems with low-precision analog-to-digital converters (ADCs). The underlying idea of the proposed methods is to construct an extremely sparse inter-symbol-interference channel model by jointly exploiting the delay-domain sparsity in mmWave channels and a high quantization noise caused by low-precision ADCs. Then, we harness this sparse channel model to create a trellis diagram with a reduced number of states and a factor graph with very sparse edge connections, which are used for the computationally efficient soft-output detection methods. Using the reduced trellis diagram, we present a soft-output detection method that computes the log-likelihood ratios (LLRs) of coded bits by optimally combining the quantized received signals obtained from multiple receive antennas using a forward-and-backward algorithm. To reduce the computational complexity further, we also present a low-complexity detection method using the sparse factor graph to compute the LLRs in an iterative fashion based on a belief propagation algorithm. Simulations results demonstrate that the proposed soft-output detection methods provide significant frame-error-rates gains compared with the existing frequency-domain equalization techniques in a coded mmWave MIMO system using one- or two-bit ADCs. [ABSTRACT FROM AUTHOR]

This paper considers a Massive MIMO network with $ {L}$ cells, each comprising a base stations (BS) with $ {M}$ antennas and $K$ single-antenna user equipments. Within this setting, we are interested in deriving approximations of the achievable rates in the uplink and downlink under the assumption that single-cell linear processing is used at each BS and that each intracell link forms an uncorrelated MIMO Rician fading channel matrix; that is, with a deterministic line-of-sight (LoS) path and a stochastic non-LoS component describing a spatial uncorrelated multipath environment. The analysis is conducted assuming that $ {N}$ and $ {K}$ grow large with a given ratio ${\textbf {N/K}}$ under the assumption that the data transmission in each cell is affected by channel estimation errors, pilot contamination, an arbitrary large scale attenuation and LoS components. Numerical results are used to prove that the approximations are asymptotically tight, but accurate for systems with finite dimensions. The asymptotic results are also used to evaluate the impact of LoS components. In particular, we exemplify how the number of antennas for achieving a target rate can be substantially reduced with LoS links of only a few dBs of strength. [ABSTRACT FROM AUTHOR]

This paper studies a multiuser mobile edge computing (MEC) system in which one base station (BS) serves multiple users with intensive computation tasks. We exploit the multi-antenna non-orthogonal multiple access (NOMA) technique for multiuser computation offloading, such that different users can simultaneously offload their computation tasks to the multi-antenna BS over the same time/frequency resources, and the BS can employ successive interference cancelation (SIC) to efficiently decode all users’ offloaded tasks for remote execution. In particular, we pursue energy-efficient MEC designs by considering two cases with partial and binary offloading, respectively. We aim to minimize the weighted sum-energy consumption at all users subject to their computation latency constraints, by jointly optimizing the communication and computation resource allocation as well as the BS’s decoding order for SIC. For the case with partial offloading, the weighted sum-energy minimization is a convex optimization problem, for which an efficient algorithm based on the Lagrange duality method is presented to obtain the globally optimal solution. For the case with binary offloading, the weighted sum-energy minimization corresponds to a mixed Boolean convex optimization problem that is generally more difficult to be solved. We first use the branch-and-bound (BnB) method to obtain the globally optimal solution and then develop two low-complexity algorithms based on the greedy method and the convex relaxation, respectively, to find suboptimal solutions with high quality in practice. Via numerical results, it is shown that the proposed NOMA-based computation offloading design significantly improves the energy efficiency of the multiuser MEC system as compared to other benchmark schemes. It is also shown that for the case with binary offloading, the proposed greedy method performs close to the optimal BnB-based solution, and the convex relaxation-based solution achieves a suboptimal performance but with lower implementation complexity. [ABSTRACT FROM AUTHOR]

This paper considers an unlicensed multiple-access channel (MAC) that coexists with a licensed point-to-point user, following the underlay cognitive radio paradigm. We assume that every transceiver except the secondary base station has one antenna and that the primary user (PU) is protected by a minimum rate constraint. In contrast to the conventional assumption of proper Gaussian signaling, we allow the secondary users to transmit improper Gaussian signals, which are correlated with their complex conjugate. When the secondary base station performs zero-forcing, we show that improper signaling is optimal if the sum of the interference channel gains (in an equivalent canonical model) is above a certain threshold. Additionally, we derive an efficient algorithm to compute the transmission parameters that attain the rate region boundary for this scenario. The proposed algorithm exploits a single-user representation of the secondary MAC along with new results on the optimality of improper signaling in the single-user case when the PU is corrupted by an improper noise. [ABSTRACT FROM AUTHOR]

In this paper, a high-rate and diversity-achieving spatial modulation transmission scheme is proposed, which uses the stacked Alamouti code as the transmitted signal matrix and then is named as stacked Alamouti based spatial modulation (SA-SM) scheme. In this scheme, the spatial constellation (SC) is composed of all the possible activated antennas combinations. According to a specific SC codeword, the corresponding symbols in the stacked Alamouti code are simultaneously activated. Owing to the structure of stacked Alamouti code, the SA-SM scheme can work with arbitrary even number of transmit antennas $n_{T}$ , and any number of activated antennas from 1 to $n_{T}$. With the same number of activated antennas $n_{A}$ , the SA-SM scheme carries more symbols than the spatially modulated orthogonal space-time block codes (SM-OSTBC) scheme, thus SA-SM can achieve higher spectral efficiency. Without the need of any parameter or matrix optimization, the SA-SM scheme enjoys the non-vanishing determinants property. Moreover, owing to possessing the block-orthogonal structure, SA-SM enables faster metric computations in the QR decomposition-M detection, and then it achieves significant decoding complexity reduction without performance loss. Under various system configurations, the performance advantages of SA-SM over several existing diversity-achieving SM schemes such as GSTSK and SM-OSTBC, are shown by simulation results for various spectral efficiencies. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal signaling schemes and capacities of non-coherent correlated multiple-input single-output (MISO) channels in fast Rayleigh fading. We consider both channels under per-antenna power constraints as well as channels under joint per-antenna and sum power constraints. For per-antenna power constraint channels, we first establish the convex and compact properties of the feasible sets, and demonstrate the existence of optimal input distribution and the uniqueness of optimal effective magnitude input distribution. By exploiting the solutions of a quadratic optimization problem, we show that the Kuhn–Tucker condition on the optimal inputs can be simplified to a single dimension. As a result, we can apply the Identity Theorem to show the discrete and finite nature of the optimal effective magnitude distribution, with a mass point located at the origin. By using this distribution, we then construct a finite and discrete optimal input vector distribution. The use of this input allows us to determine the capacity gain of MISO over SISO via the phase solutions of a constrained quadratic optimization problem on a sphere, which can be obtained using a proposed penalized optimization algorithm. We also extend the results to MISO channels subject to the joint per-antenna and sum power constraints. Under this consideration, it is shown that not all per-antenna constraints are active. While the finiteness and discreteness of the optimal effective magnitude and the optimal input vector distributions still hold, the optimal phases and the optimal power allocation among the transmit antennas need to be determined simultaneously via a quadratic optimization problem under inequality constraints. These solutions can finally be used to obtain the MISO capacity gain. [ABSTRACT FROM AUTHOR]

A base-station (BS) equipped with multiple antennas can use its spatial dimensions in three different ways: 1) to serve multiple users, thereby achieving a multiplexing gain; 2) to provide spatial diversity in order to improve user rates; and 3) to null interference in neighboring cells. This paper answers the following question: What is the optimal balance between these three competing benefits? We answer this question in the context of the downlink of a cellular network, where multi-antenna BSs serve multiple single-antenna users using zero-forcing beamforming with equal power assignment, while nulling interference at a subset of out-of-cell users. Any remaining spatial dimensions provide transmit diversity for the scheduled users. Utilizing tools from stochastic geometry, we show that, surprisingly, to maximize the per-BS ergodic sum rate, with an optimal allocation of spatial resources, interference nulling does not provide a tangible benefit. The strategy of avoiding inter-cell interference nulling, reserving some fraction of spatial resources for multiplexing, and using the rest to provide diversity, is already close-to-optimal in terms of the sum-rate. However, interference nulling does bring significant benefit to cell-edge users, particularly when adopting a range-adaptive nulling strategy where the size of the cooperating BS cluster is increased for cell-edge users. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel modulation technique for dual-polarization communication systems, which reduces the error rate compared with the existent schemes. This modulation places the symbols in a 3-D constellation, rather than the classic approach of 2-D. Adjusting the phase of these symbols depending on the information bits, we are able to increase the bit rate. Hence, the proposed scheme conveys information by selecting both polarization state and the phase of radiated electromagnetic wave. We also analyses the performance of the 3-D polarized modulation (PMod) for different constellation sizes and we obtain a curve of rate adaptation. Finally, we compare the proposed 3-D PMod with the other existing schemes, such as single polarization phase shift keying and double polarization vertical Bell Laboratories layer space–time, both carrying the same number of information bits. The results show that the 3-D PMod always outperforms all other schemes, except for low-order modulation. Therefore, we can conclude that the 3-D PMod is an excellent candidate for medium- and high-modulation-order transmissions. [ABSTRACT FROM AUTHOR]

An energy efficiency (EE) maximization problem with multiple transmit antennas (multiple-input-single-output or distributed antennas setups) is considered in this paper. Besides the constraint on the total transmit power, per-antenna transmit power constraints, and a total weighted power constraint are jointly considered. Moreover, a quality-of-service constraint is also considered. Both linear and nonlinear high power amplifier (HPA) cases are studied. Because the original problem for the linear HPA case is a fractional convex problem, Dinkelbach’s algorithm is implemented to reformulate the problem. By investigating the Karush-Kuhn-Tucker conditions, the mathematical properties of the globally optimal solution are studied and proved, which provides a deeper understanding of the structure of power allocation among antennas. These properties also lead to a reduction of the complexity of the algorithms proposed to find the global optimum. For the nonlinear HPA cases, the reformulated problem after successive convex approximation is shown to be exactly in the same form as that of the previous problem with linear HPA with different weights of power consumption at each antenna. On the basis of numerical results comparing our EE maximization algorithms against different benchmarks, the efficiency and the superiority of our algorithms can be concluded. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) technology has been advocated as a promising infrastructure to provide reliable communications, both in indoor and outdoor environments. In this paper, we extend the application of mmWave to the uplink communication between smart meters (SMs) and a gateway. Such a communication is subject to interference from SMs belonging to adjacent networks and blockage caused by human bodies. Using a 3-D stochastic blockage model, we derive the outage probability. When human-body blockage is neglected, the high signal-to-noise-ratio (SNR) analysis shows a diversity gain of $(m_{L}M)$ , where $m_{L}$ is the Nakagami-fading parameter of the line of sight (LOS) of the reference transmitter’s channel, and $M$ is the number of receive antennas at the gateway. Accounting for human-body blockage, the diversity gain reduces to $(m_{N}M)$ , where $m_{N}$ is the Nakagami-fading parameter of the non LOS of the reference transmitter’s channel. Our analysis shows that the probability that an SM is in LOS decays exponentially with the link length and the density of blockages. Although at high SNR blockage reduces the diversity gain, our numerical results show that blockage may decrease the outage probability at finite SNR. [ABSTRACT FROM AUTHOR]

The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due to 1-bit quantization fundamentally changes the optimal communication strategy and also imposes a capacity penalty to the system. In this paper, the capacity of a Gaussian MIMO channel in which the antenna outputs are processed by an analog linear combiner and then quantized by a set of zero threshold ADCs is studied. A new capacity upper bound for the zero threshold case is established that is tighter than the bounds available in the literature. In addition, we propose an achievability scheme which configures the analog combiner to create parallel Gaussian channels with phase quantization at the output. Under this class of analog combiners, an algorithm is presented that identifies the analog combiner and input distribution that maximize the achievable rate. Numerical results are provided showing that the rate of the achievability scheme is tight in the low signal-to-noise ratio (SNR) regime. Finally, a new 1-bit MIMO receiver architecture which employs analog temporal and spatial processing is proposed. The proposed receiver attains the capacity in the high SNR regime. [ABSTRACT FROM AUTHOR]

The existing relay-assisted terahertz (THz) wireless system is limited to dual-hop transmission with pointing errors and short-term fading without considering the shadowing effect. This paper analyzes the performance of a multihop-assisted backhaul communication mixed with an access link under the shadowed fading with antenna misalignment errors. We derive novel probability density and distribution functions of the signal-to-noise ratio (SNR) of the multihop link employing channel-assisted (CA) and fixed-gain (FG) amplify-and-forward (AF) relaying for each hop by considering independent but not identically distributed (i.ni.d) $\alpha $ - $\mu $ fading channel with pointing errors. We present analytical expressions for the outage probability and average bit-error-rate (ABER) and develop asymptotic analysis in high SNR regime to derive the diversity order for both CA-multihop and FG-multihop backhaul links. We use the derived results of the multihop systems to analyze the statistical performance of the integrated backhaul-access relaying for both uplink and downlink transmission considering the generalized- $K$ shadowed fading model in the access link. We also present exact and asymptotic expressions of the outage probability for the considered mixed system. We perform computer simulations to provide design and deployment aspects of employing multiple relays to enhance THz wireless transmissions. [ABSTRACT FROM AUTHOR]

In massive multiple-input multiple-output (MIMO) systems, it may not be power efficient to have a pair of high-resolution analog-to-digital converters (ADCs) for each antenna element. In this paper, a near maximum likelihood (nML) detector for uplink multiuser massive MIMO systems is proposed where each antenna is connected to a pair of one-bit ADCs, i.e., one for each real and imaginary component of the baseband signal. The exhaustive search over all the possible transmitted vectors required in the original maximum likelihood (ML) detection problem is relaxed to formulate an ML estimation problem. Then, the ML estimation problem is converted into a convex optimization problem which can be efficiently solved. Using the solution, the base station can perform simple symbol-by-symbol detection for the transmitted signals from multiple users. To further improve detection performance, we also develop a two-stage nML detector that exploits the structures of both the original ML and the proposed (one-stage) nML detectors. Numerical results show that the proposed nML detectors are efficient enough to simultaneously support multiple uplink users adopting higher-order constellations, e.g., 16 quadrature amplitude modulation. Since our detectors exploit the channel state information as part of the detection, an ML channel estimation technique with one-bit ADCs that shares the same structure with our proposed nML detector is also developed. The proposed detectors and channel estimator provide a complete low power solution for the uplink of a massive MIMO system. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate optimal downlink power allocation in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays (DAAs) under correlated and uncorrelated channel fading. In DAA massive MIMO, a base station (BS) consists of multiple antenna sub-arrays. Notably, the antenna sub-arrays are deployed in arbitrary locations within a DAA massive MIMO cell. Consequently, the distance-dependent large-scale propagation coefficients are different from a user to these different antenna sub-arrays, which makes power control a challenging problem. We assume that the network operates in time-division duplex mode, where each BS obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum-ratio transmission in the downlink. We then derive a closed-form signal-to-interference-plus-noise ratio (SINR) expression, where the channels are subject to correlated fading. Based on the SINR expression, we propose a network-wide max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate the performance advantages offered by DAA massive MIMO. For some specific scenarios, DAA massive MIMO can improve the average per-user throughput up to 55%. Furthermore, we demonstrate that channel fading covariance is an important factor in determining the performance of DAA massive MIMO. [ABSTRACT FROM AUTHOR]

This paper studies the asymptotic performance of a multiple-input multiple-output (MIMO) multiple-access (MA) wireless network where spatial correlations at both the transmitters (i.e., mobile stations) and the central receiver (i.e., base station) exist, and more than one multiantenna sets are employed at the receiver to provide macrodiversity. The sense of asymptotic behavior we consider is the large-system limit in which the numbers of antennas at each mobile station and antenna set go to infinity with their ratios fixed. Using the replica method, we derive analytical solutions to the asymptotic spectral efficiency (SE) of the MIMO-MA systems for any given input distributions (not necessarily Gaussian) from the mobile transmitters. Our results can be regarded as the generalization of many previously known results for degenerate cases. Another contribution of this paper is an efficient algorithm to determine the asymptotic optimum transmit-signal covariance matrices that can maximize the SE of the MIMO-MA network within the period in which the spatial channel covariance information (CCI) can be considered static, and assuming that only CCI is available at the transmitters. [ABSTRACT FROM AUTHOR]

In this paper, an optimization problem to maximize the energy efficiency of a hybrid automatic repeat request with incremental redundancy (HARQ-IR) is considered for massive multiple-input multiple-output (MIMO) systems. Because a sum rate for multiple HARQ-IR rounds is approximated by a Gaussian distribution, a problem maximizing energy efficiency becomes tractable. In particular, a simplified form of energy efficiency for massive MIMO transmissions with an HARQ-IR protocol is derived using an outage probability, which is given by a tail probability of the Gaussian distribution. By exploiting the proposed simplified form, we show that the energy efficiency of the system is approximated by a piecewise quasi-concave function. Using these properties, an algorithm finding the optimal transmission power and number of transmission rounds for maximizing energy efficiency is proposed. Moreover, we show that the optimal number of HARQ transmission rounds can be less than the maximum allowable retransmissions when considering the constant power consumption of the massive MIMO system with an HARQ-IR protocol. Simulation results verify the theoretical analysis and show the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we examine the secrecy performance of two-way relaying between a large-scale multiple antenna base station (BS) and a single antenna mobile user (MU) in the presence of a multiple antenna external jammer. We consider the untrusted relaying scenario, where an amplify-and-forward relay is both a necessary helper and a potential eavesdropper to the BS and MU transmissions. With the aim of maximizing the instantaneous secrecy sum rate, we derive new closed-form solutions for the optimal power allocation (OPA) under the following three scenarios: 1) without jamming (WoJ) where the jammer is not activated; 2) friendly jamming (FJ) where the jamming signal is known a priori at the BS and MU; and 3) Gaussian noise jamming (GNJ) where the jamming signal is unknown at the BS and MU. Based on our OPA solutions, new closed-form expressions are derived for the ergodic secrecy sum rate (ESSR) with Rayleigh fading channels. Furthermore, we characterize the high signal-to-noise ratio slope and power offset of the ESSR to provide a fundamental comparison of the WoJ, FJ, and GNJ scenarios. Based on our analysis, we propose a simple relay selection criterion for the scenario when the BS and MU are assisted by multiple untrusted relays. Numerical examples are presented to demonstrate the impact of the jammer’s location, number of antennas and the advantage of the proposed relay selection criterion on the secrecy performance. Our findings highlight that similar to the trusted relaying scenario, the ESSR of all three secure transmission scenarios improve as the number of untrusted relays increases. Moreover, we highlight an interesting insight that the OPA for the GNJ scenario results in the same ESSR performance as the OPA for the WoJ scenario. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is widely regarded as a promising interference management technique in wireless networks. Despite its rapid advances in cellular networks, most results of IA are limited to information-theoretic exploration or physical-layer signal design. Little progress has been made so far to advance IA in cellular networks from a networking perspective. In this paper, we aim to fill this gap by studying IA in large-scale cellular networks. For the uplink, we propose an OFDM-based IA scheme and prove its feasibility at the physical layer by showing that all data streams in the IA scheme can be transported free of interference. Based on the IA scheme, we develop a cross-layer IA optimization framework that can fully translate the benefits of IA to throughput gain in cellular networks. Furthermore, we show that the IA optimization problem in the downlink can be solved in the exactly same way as that in the uplink. Simulation results show that our OFDM-based IA scheme can significantly increase the user throughput and the throughput gain increases with user density in the network. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the secrecy characteristics of random wireless networks using stochastic geometric tools. The locations of the source and eavesdropper nodes are modeled as independent 2-D Poisson point processes. We investigate the secrecy outage probability of such networks from the perspective of the $k$ th best source, which has still not been well characterized. In particular, we derive the received path gain distributions of the typical destination and the eavesdropper from the $k$ th best source. Furthermore, we introduce a novel concept of security-region based on the $k$ th best source index. This is pragmatic in creating a protected communication zone for the typical destination and also to bind the number of sources that can coordinate in a coordinated multi-point transmission (CoMP) network. We further derive the secrecy outage probability for these CoMP sources based on the security-region. We also provide a closed-form expression for the maximum number of eavesdroppers for a given secrecy outage constraint, which can effect the secure communication. Tractable numerical, and simulation results are presented under various assumptions of densities, path loss exponents, and antenna figures. [ABSTRACT FROM AUTHOR]

In this paper, we address the antenna selection (AS) problem in full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) systems, where a multi-antenna FD relay bridges the connection between the multi-antenna base station and NOMA far user. Specifically, two AS schemes, namely max-U1 and max-U2, are proposed to maximize the end-to-end signal-to-interference-plus-noise ratio at either or both near and far users, respectively. Moreover, a two-stage AS scheme, namely quality-of-service (QoS) provisioning scheme, is designed to realize a specific rate at the far user while improving the near user’s rate. To enhance the performance of the QoS provisioning AS scheme, the idea of dynamic antenna clustering is applied at the relay to adaptively partition the relay’s antennas into transmit and receive subsets. The proposed AS schemes’ exact outage probability and achievable rate expressions are derived. To provide more insight, closed-form asymptotic outage probability expressions for the max-U1 and max-U2 AS schemes are obtained. Our results show that while the QoS provisioning AS scheme can deliver a near-optimal performance for static antenna setup at the relay, it provides up to 12% average sum rate gain over the optimum AS selection with fixed antenna setup. [ABSTRACT FROM AUTHOR]

This paper develops an analytical framework for exploring the benefits of applying cluster-based multi-antenna non-orthogonal multiple access (NOMA) in dense wireless networks. Using the tools of stochastic geometry, a new explicit expression and a tight approximation for per-cluster average data rates are derived in terms of relevant system parameters. Moreover, simulation results are provided to validate the accuracy of our analytical results and draw some essential system design insights. Based on the tractable expressions, we further consider the analysis and optimization of area spectral efficiency (ASE). It is analytically demonstrated that: 1) In terms of the per-cluster average data rate, there exists a wide range for the power allocation coefficient within a cluster where NOMA outperforms orthogonal multiple access (OMA); 2) The per-cluster average data rate of NOMA benefits more from the additional deployment of antennas at base stations (BSs) than that of OMA when the accuracy of channel state information at transmitter (CSIT) is fixed; 3) Regarding to ASE, there exists an optimal combination of the number of clusters and power allocation coefficient to maximize ASE. The performance gain of NOMA relative to OMA becomes marginal when the requirement of user fairness is stringent; 4) As for a special case that the power allocation coefficient is fixed, the analytical results indicate that ASE scales linearly with the number of antennas when the number of clusters is set optimally. [ABSTRACT FROM AUTHOR]

In this paper, we investigate and reveal the ergodic sum-rate gain (ESG) of non-orthogonal multiple access (NOMA) over orthogonal multiple access (OMA) in uplink cellular communication systems. A base station equipped with a single-antenna, with multiple antennas, and with massive antenna arrays is considered both in single-cell and multi-cell deployments. In particular, in single-antenna systems, we identify two types of gains brought about by NOMA: 1) a large-scale near-far gain arising from the distance discrepancy between the base station and users; 2) a small-scale fading gain originating from the multipath channel fading. Furthermore, we reveal that the large-scale near-far gain increases with the normalized cell size, while the small-scale fading gain is a constant, given by $\gamma = 0.57721$ nat/s/Hz, in Rayleigh fading channels. When extending single-antenna NOMA to M-antenna NOMA, we prove that both the large-scale near-far gain and small-scale fading gain achieved by single-antenna NOMA can be increased by a factor of M for a large number of users. Moreover, given a massive antenna array at the base station and considering a fixed ratio between the number of antennas, M, and the number of users, K, the ESG of NOMA over OMA increases linearly with both M and K. We then further extend the analysis to a multi-cell scenario. Compared to the single-cell case, the ESG in multi-cell systems degrades as NOMA faces more severe inter-cell interference due to the non-orthogonal transmissions. Besides, we unveil that a large cell size is always beneficial to the ergodic sum-rate performance of NOMA in both single-cell and multi-cell systems. Numerical results verify the accuracy of the analytical results derived and confirm the insights revealed about the ESG of NOMA over OMA in different scenarios. [ABSTRACT FROM AUTHOR]

Ambient backscatter devices (tags and readers) use existing radio frequency (RF) signals to transmit data. Most prior works consider single-antenna tags, but this paper investigates the case of multiple-antenna tags, which are capable of simultaneous energy harvesting and data transmission. However, the multi-antenna channel between the tag and the reader, and the unpredictable nature of RF signals due to uncontrollable RF sources (e.g., location and transmit power), make signal detection highly challenging. Thus, the detection process becomes a hypothesis testing problem with unknown parameters. Consequently, we design a blind detector based on the generalized likelihood ratio test (GLRT) without using channel state information (CSI), signal power and noise variance. The decision threshold and detection probability of it are also analyzed in detail. Furthermore, to maximize its detection performance, we develop the optimal backscatter antenna selection scheme. Interestingly, we show that the detector performs best when only two backscatter antennas are selected. Finally, extensive simulation results validate the analysis and illustrate the effectiveness of the proposed detector. [ABSTRACT FROM AUTHOR]

Massive multiple-input–multiple-output (MIMO) communications are the focus of considerable interest in recent years. While the theoretical gains of massive MIMO have been established, implementing MIMO systems with large-scale antenna arrays in practice is challenging. Among the practical challenges associated with massive MIMO systems are increased cost, power consumption, and physical size. In this paper, we study the implementation of massive MIMO antenna arrays using dynamic metasurface antennas (DMAs), an emerging technology which inherently handles the aforementioned challenges. Specifically, DMAs realize large-scale planar antenna arrays and can adaptively incorporate signal processing methods such as compression and analog combining in the physical antenna structure, thus reducing the cost and power consumption. First, we propose a mathematical model for massive MIMO systems with DMAs and discuss their constraints compared to ideal antenna arrays. Then, we characterize the fundamental limits of uplink communications with the resulting systems and propose two algorithms for designing practical DMAs for approaching these limits. Our numerical results indicate that the proposed approaches result in practical massive MIMO systems whose performance is comparable to that achievable with ideal antenna arrays. [ABSTRACT FROM AUTHOR]

In modern mobile communication networks, such as 3G and 4G networks, sectorized antennas have been widely used to divide each cell into multiple sectors in order to improve coverage, spectrum efficiency, and quality of service. Large-scale path loss from a transmitting antenna to a receiving antenna should include: 1) propagation attenuation that depends on transmission distance; 2) shadowing that depends on surrounding environment; and 3) antenna loss that depends on a sectorized antenna pattern and transmission angle. An in-depth analysis of statistical characteristics of large-scale path losses involving with these three factors is crucial for the design, operation, evaluation, and optimization of modern sectorized wireless networks. In this paper, a sectorized antenna pattern is, for the first time, considered in the derivation of a closed-form expression of a probability density function (pdf) of large-scale path losses. Specifically, we first discover that the normalized pdf of propagation attenuation plus shadowing, which can be approximated by the Gaussian mixture model (GMM) with all system parameters, is fully determined by our newly defined metric 10/\ln 10\beta /\sigma s , namely, the attenuation exponent $\beta$ to standard deviation of shadowing \sigma _{s} ratio (ASR). The convolution of GMM and antenna loss statistics is elaborately transformed to a series of differential equations. A closed-form pdf of large-scale path losses with sectorized antenna pattern can be obtained by solving these differential equations. To reduce the computational complexity, we further prove that the exciting sources of these differential equations can be tightly approximated by weighted Gaussian functions, and thus, the final solutions (i.e., pdf of path losses) can be derived in the form of Gaussian and Dawson functions. Our analytical results are verified by extensive numerical computation and Monte Carlo simulation results, e.g., the impact of ASR on the shape of pdf of propagation attenuation plus shadowing. Compared with traditional Gaussian-fitting approach, our newly derived pdf of large-scale path losses with sectorized antenna patterns is at least two orders of magnitude more accurate in terms of Kullback–Leibler divergence under typical propagation attenuation and shadowing conditions. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the quantization and the feedback of downlink spatial covariance matrix for massive multiple-input multiple-output (MIMO) systems with cascaded precoding. Massive MIMO has gained a lot of attention recently because of its ability to significantly improve the network performance. To reduce the overhead of downlink channel estimation and uplink feedback in frequency-division duplex massive MIMO systems, cascaded precoding has been used to convert high-dimensional physical channels into low-dimensional effective channels. For the cascaded precoding, the inner precoder is determined by the downlink spatial covariance matrix, which is unknown in the base station (BS). To address this issue, we propose a spatial spectrum-based approach for the quantization and the feedback of the spatial covariance matrix. In this manner, the BS can obtain partial information on the downlink spatial covariance matrix. Our result shows that the inner precoder based on the proposed approach can be viewed as modulated discrete prolate spheroidal sequences and thus achieves much smaller spatial leakage than the traditional discrete Fourier transform submatrix-based precoding. Practical issues for the application of the proposed approach are also addressed in this paper. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a wireless-powered communication network in which a multiple-antenna two-way AF relay transfers power to multi-pair of single antenna users. A harvest-then-transmit protocol is adopted where the relay first broadcasts wireless power to all the users during a power transfer phase. Multiple pairs of users then use the harvested energy to exchange information through the relay over two phases: up-link and down-link. In the up-link phase, all the users transmit their independent signals to the relay, whereas in the down-link phase, the relay amplifies and forwards the received signals to the intended users. In order to mitigate the interference, zero-forcing reception and transmission is applied at the relay. To characterize system performance, we consider ergodic spectral and energy efficiencies in three different cases based on the knowledge of the channel state information (CSI) at the relay in the power transfer phase, namely: 1) unknown CSI; 2) partially known CSI; and 3) perfectly known CSI. In light of this, new analytical expressions for the ergodic spectral and energy efficiencies are derived for the three cases and Monte Carlo simulations are provided throughout to validate our analysis. The impacts of some important system parameters, such as energy harvesting time, energy harvesting efficiency, number of user-pairs, and relay antennas, on the adopted performance metrics are investigated. [ABSTRACT FROM PUBLISHER]

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]

Orthogonal frequency division multiplexing (OFDM) signals with rectangularly windowed pulses exhibit low spectral confinement. Two approaches usually referred to as pulse-shaping and active interference cancellation are classically employed to reduce the out-of-band emission (OOBE) without affecting the receiver. This paper proposes a spectral shaping method that generalizes and unifies these two strategies. To this end, the OFDM carriers are shaped with novel pulses, referred to as generalized pulses, that consist of the ones used in conventional OFDM systems plus a series of cancellation terms aimed at reducing the OOBE of the former. Hence, each generalized pulse embeds all the terms required to reduce its spectrum in the desired bands. This leads to a data-independent optimization problem that notably simplifies the implementation complexity and allows the analytical calculation of the resulting power spectral density (PSD), which in most methods found in the literature can only be estimated by means of simulations. As an example of its performance, the proposed technique allows complying with the stringent PSD mask imposed by the EN 50561-1 with a data carrier loss lower than 4%. By contrasts, 28% of the data carriers have to be nulled when pulse-shaping is employed in this scenario. [ABSTRACT FROM AUTHOR]