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The number of commercial and civilian vehicles equipped with automotive radars is expected to rise rapidly in the forthcoming years and with that comes the problem of increased mutual interference between the radar sensors, which can result in severely reduced radar sensitivity and increased false alarm rates. The difficulty and complexity of the problem increase with MIMO radar systems and multiply even further with a growing number of vehicles present on the scene. A system of connected vehicles can efficiently address this problem by sharing information amongst themselves. In this paper, we propose an efficient waveform design algorithm that seeks to minimize a collective cross-ambiguity function. Vehicles that can talk to each other, can perform the design online in a collaborative manner, or offline, in which case the radar codes can be designed and stored in a codebook for future use. The proposed coding scheme is computationally efficient for practical use and the incorporation of such schemes requires only a slight modification of the existing systems. Our numerical examples indicate that the proposed scheme can significantly reduce the interference power level in a desired area of the radar cross-ambiguity functions. [ABSTRACT FROM AUTHOR]

For large-scale antenna array multiple-input multiple-output (MIMO) systems, a typical solution often put forward for uplink detection consists in applying low-complexity linear receivers such as zero-forcing (ZF) and minimum mean-square error (MMSE) combiners. In this paper, the performance of uplink MMSE detection has been analyzed in the context of a multi-cell multiuser MIMO system. An approximate expression for the signal-to-interference-plus-noise ratio (SINR) is proposed, which is in simple form and becomes exact in the low SNR regime. This approximate SINR applies to systems where the base station (BS) has the statistical information of the out-of-cell interfering signals, and systems where the BS ignores the presence of such interfering signals. This approximate SINR is tight for arbitrary user powers, arbitrary number of antennas at the base station, and arbitrary channel correlation matrix associated with any particular user. Approximate expressions for capacity and bit-error rate/symbol-error rate have also been derived. Particularly, it can be proven that, when the MMSE receiver ignores the presence of out-of-cell interfering signals, the performance gap between ZF and MMSE vanishes in the high SNR regime. [ABSTRACT FROM AUTHOR]

This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works. [ABSTRACT FROM AUTHOR]

In this paper, we study the codebook size design strategies in the multiple-input–multiple-output (MIMO) broadcast channel (BC) systems. We adopt the nonlinear Tomlinson–Harashima precoder (THP), which is designed by the imperfect channel direction information (CDI) acquired from the random vector quantization (RVQ) feedback mechanism. Under the limitation of the total feedback rate, we flexibly allocate the size of each user's codebook so that the overall channel capacity is maximized. Since the design problem is not convex, directly finding out the optimum allocation of codebook size is not attainable. However, by sophisticatedly using the discrete majorization theory, we can derive the codebook size allocation strategies for the high- and the low-signal-to-noise-ratio (SNR) regions. Interestingly, the results show that the equal size codebook is preferable in the low-SNR region, whereas the codebook allocates the whole available codebook size to a single user in the high-SNR region. Simulations certify the theoretical result of our design. [ABSTRACT FROM PUBLISHER]

Linear decoding of space–frequency block codes (SFBCs) based on the Alamouti structure with orthogonal frequency-division multiplexing (OFDM) requires the channel to be constant across two consecutive tones. However, time-dispersive multipath fading channels exhibit frequency-selective behavior wherein the channel across two tones will vary. This paper provides analytical tools for evaluating the performance of SFBCs with OFDM in frequency-selective channels. The analysis uses the average signal-to-interference-plus-noise ratio (SINR) as a sufficient statistic to describe the performance of SFBCs in frequency-selective channels. A unified formula is derived to characterize the channel correlation between two consecutive tones for various frequency-selective channels. A closed-form solution of the average SINR is obtained, which takes into account imperfect channel estimation and frequency selectivity. An interpolation method of the channel estimate is proposed, which is shown to improve the bit-error-rate performance by 3 dB at a high SNR. The accuracy of the theoretical analyses is verified by numerical simulations under multipath channels such as the International Telecommunications Union (ITU) pedestrian and vehicular models. [ABSTRACT FROM PUBLISHER]

We consider the uplink transmission in multiuser wireless systems with multiple single-antenna transmitting users and a multiantenna receiver. We address two problems in this paper. The first problem is user admission, i.e., given a large number of users, how to admit the maximum number of users that can simultaneously satisfy quality of service (QoS) and power constraints. The second problem is how to distribute the data among the users when they are allowed to share data before transmission. The aim is to minimize the total data exchange cost. Such a problem is called user clustering. We formulate those problems into sparsity-maximization problems, which are NP-hard. Inspired by compressive sensing techniques, we propose a common framework to tackle those problems by first applying the \ell1 -norm relaxation and then solving them with convex optimization methods. Simulations show that the proposed algorithms achieve excellent performance. For user admission, the numbers of admitted users by the proposed algorithms are close to the optimum numbers of admitted users obtained by exhaustive search (ES) . For user clustering, the total data exchange cost is reduced by more than 10% after only a few iterations. When the QoS requirement is low, the user data exchange can be avoided using the proposed method, which achieves the optimum result obtained by ES. [ABSTRACT FROM PUBLISHER]

Physical layer security has drawn significant attention in recent years because of its advancement in preventing confidential information leakage to eavesdroppers. In this paper, we focus on secure beamformer designs in multiuser multi-input multi-output (MU-MIMO) systems with a multi-antenna eavesdropper attempting to overhear the confidential information of a particular user. Unlike the existing work, we aim to exploit the inherent multi-user interference to disrupt the reception of the eavesdropper and enhance the security of wireless communications. Particularly, utilizing practical signal-to-interference-noise metrics, the objective of the secure beamformer design is to minimize the eavesdropper's SINR, while providing legitimate users with required prespecified SINRs to guarantee the qualify of service. We propose secure beamformer designs for both downlink and uplink transmissions, under the conditions of known and unknown eavesdropper's channels, respectively. With the proposed secure beamformers, the multiuser signal behaves like the artificial noise or distributed friendly jamming, which can further degrade the reception of the eavesdropper. Extensive simulation studies confirm our analytical performance predictions and illustrate the advantages of proposed beamformer designs for secure MU-MIMO transmissions. [ABSTRACT FROM AUTHOR]

Achieving a good tradeoff between spectral efficiency (SE) and energy efficiency (EE) is important for the emerging wireless communication systems. Motivated by this, we study multiuser downlink beamforming in massive multiple-input multiple-output systems for maximizing a new metric of resource efficiency (RE), which is defined as a weighted combination of EE and SE. The new measure has more flexibility in striking the balance between SE and EE, but brings enormous difficulties in solving the resulting problem. To this end, we first investigate an uplink–downlink duality for the RE maximization. The conventional uplink–downlink duality only applies in the SE or the capacity region, and has yet not been explicitly established for the EE or the RE. In this paper, we prove with rigorous derivation that the duality has a more general form, which can be directly used to tackle the EE or RE beamforming optimization problem. Based on the duality, we then develop an optimization algorithm to realize spectral and energy efficient multiuser beamforming with either instantaneous or statistical channel state information (CSI). Numerical results finally verify that the design based on statistical CSI is able to asymptotically achieve the performance obtained with instantaneous CSI, but with much lower complexity. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sum-rate maximization problem in multiple-input multiple-output interference channels. We design the transmit covariance matrix, associated with each transmitter to maximize the sum-rate of the network when the number of data symbols is unknown. The design problem is nonconvex and then hard to be solved. We devise a semidistributed design methodology according to majorization–minimization technique to deal with the optimization problem. This leads us to a convex quadratically constrained quadratic program at each iteration with a semiclosed form solution. The proposed method is computationally efficient and converges to stationary points of the problem. The fact that the method is based on a distributed processing framework along with relatively low computational burden ( $\mathcal{O}(\max \lbrace M,N\rbrace ^{2.3})$ per iteration with $M$ and $N$ being the number of antennas at the transmitter and receiver, respectively) for the user terminals can make it a potential candidate for practical implementations. Finally, we extend the proposed method for the case with channel estimation errors. Simulation results verify the efficiency of the proposed method, and in a typical scenario we have around 60 times lower run-time when compared to the counterparts of the method. [ABSTRACT FROM AUTHOR]

This paper considers a novel virtual pilot-assisted channel estimation algorithm for multiple input multiple output single carrier frequency domain equalization (MIMO-SCFDE) systems over fast time-varying multipath channels. Given that the fast time-varying channels can no longer support the assumption that the channel frequency-domain response remains invariant for the duration of one SC-FDE symbol, most of the channel estimation methods cannot be directly applied to MIMO-SCFDE systems. We put forward an iterative interfrequency interference cancellation method for the time-varying multipath channels over one SC-FDE symbol. The proposed method utilizes the virtual pilot-assisted channel estimation and partial minimum-mean-square-error equalization to improve the accuracy of the estimation. Simulation results validate the improved performance of the proposed method for MIMO-SCFDE systems over fast time-varying multipath channels. [ABSTRACT FROM AUTHOR]

Nonorthogonal multiple access (NOMA) can improve the spectrum efficiency through reusing the power-level space by different users. Although NOMA in single-input single-output channels has been thoroughly explored, it is still underexploited in multiple-input multiple-output (MIMO) channels. Precoding design in multiuser MIMO channels with nonorthogonal transmission is a multidimensional nesting problem, it is hard to compare two matrix channels if only their power levels are considered. In this paper, we first propose a method to compare the covariance matrices of two channel matrices, and then derive a channel condition under which the linear precoding scheme can achieve the sum capacity. Considering arbitrary realizations of multiuser channels, we provide a nested precoding algorithm that can work well in highly correlated multiuser channels. Based on this idea, a specialized superposition transmission scheme between signaling and data information is proposed, where plenty of resources beneath the signaling signal are utilized to transmit data information for dedicated users, and a large amount of extra rates are achieved. In addition, space-time coding is used for signaling information and spatial-division multiplexing is used for multiuser data information. Under the constraint that signaling information should be correctly decoded at any position in the cell, we seek to maximize the sum rate of the underneath multiuser data streams. To this end, the optimal and a low-complexity simplified precoding algorithms are developed. Finally, simulation results verify the throughput improvement and the correct decoding probability of the signaling information. [ABSTRACT FROM AUTHOR]

This paper investigates an outage-constrained secrecy rate maximization (OC-SRM) problem based on the statistical channel uncertainty assumption in an underlay multiple-input multiple-output (MIMO) cognitive radio network, where the secondary transmitter provides simultaneous wireless information and power transfer to receivers. Our objective is to design the transmit covariance matrix and artificial noise aided covariance matrix through maximizing the secrecy rate of the secondary user while satisfying the given outage probability requirements. The designed problem is nonconvex and challenging. We employ the existing theory to reformulate the original problem into two equivalent subproblems by introducing auxiliary variables in order to overcome the difficulty arising from the Shannon capacity expression. The Bernstein-type inequality approach is resorted to conservatively approximate the probabilistic constraints. The merit of the transformation and conversion is that the tractable solutions of the original OC-SRM problem can be easily obtained through solving two convex conic subproblems alternately. Furthermore, we extend the proposed algorithm to solve full uncertainty model design. Numerical results demonstrate the efficacy of the proposed designs. [ABSTRACT FROM AUTHOR]

We investigate the performance of multiuser multiple-input-single-output (MU-MISO) downlink in the presence of the mutual coupling effect at the transmitter. Contrary to traditional approaches that aim at eliminating this effect, in this paper we propose a joint analog–digital (AD) beamforming scheme that exploits this effect to further improve the system performance. A jointly optimal AD beamformer is first obtained by iteratively maximizing the minimum received signal-to-interference-plus-noise ratio in the digital domain, followed by an optimization on the load impedance of each antenna element in the analog domain. We further introduce a decoupled low-complexity approach, with which existing closed-form beamforming schemes can also be efficiently applied. For the consideration of hardware imperfections in practice, we study the case where the analog load values are quantized, and propose a sequential search scheme based on greedy algorithm to efficiently obtain the desired quantized load values. Moreover, we also investigate the imperfect channel state information (CSI) scenarios, where we prove the optimality for closed-form beamformers, and further propose the robust schemes for two typical CSI error models. Simulation results show that with the proposed schemes the mutual coupling effect can be exploited to further improve the performance for both perfect CSI and imperfect CSI. [ABSTRACT FROM PUBLISHER]

This paper investigates simultaneous wireless information and power transfer (SWIPT) in the ad hoc network, where access points (APs) with multiple antennas can transfer energy as well as information using a common spectrum resource. The receiving nodes decode the incoming information data (information decoding, ID) and/or harvest the RF energy (energy harvesting, EH), where two different receiving node architectures—time switching (TS) and power splitting (PS)—are considered. By using a stochastic geometry approach, we aim to analyze the transmission capacity and the harvested energy per unit area as performance measures of the SWIPT in the ad hoc network. From the analytical results, we can derive the optimal node densities of ID nodes and EH nodes for TS architectures and, furthermore, optimize the power splitting ratio jointly with the node density for the PS architectures such that the harvested energy per unit area is maximized when the target transmission capacity is given. The proposed node density optimization gives us a useful insight into the design of SWIPT-based ad hoc network, where we can show how densely the APs/nodes can be deployed in a given area and furthermore, find that the ad hoc network with PS receiving nodes outperforms that with TS receiving nodes for a large target transmission capacity, and vice versa. [ABSTRACT FROM AUTHOR]

Combined with N-continuous (NC) precoding, the spatial modulation (SM) orthogonal frequency division multiplexing (OFDM) system offers considerable sidelobe suppression for the downlink transmission, at the cost of additional interference to the transmit signal. Therefore, this paper focuses on investigating the impact of the NC precoder on the bit error rate (BER) performance of the SM-OFDM system. The BER performance is analyzed over the frequency-selective Rayleigh fading channel under two distinct scenarios, i.e., perfect channel estimation and interference suppression based minimum mean square error (MMSE) channel estimation. First, we propose an approximate system model for the NC precoded SM-OFDM system along with an analysis on the introduced interference, and then derive the average BER performance of the system with perfect channel estimation. Based on the above proposed approximate system model, we further analyze the interference based upon MMSE channel estimation, and investigate the characteristics of channel estimation errors. Furthermore, we derive the average BER performance of the NC precoded SM-OFDM system with imperfect channel estimation. The numerical results show that the analytical BER closely matches its simulated counterpart under different system configurations, and demonstrate that the proposed approximate system model is in good agreement with the precise one. [ABSTRACT FROM PUBLISHER]

The evaluation of the coverage probability of multistream multiple-input multiple-output (MIMO) communications in HetNets subject to noise, fading, and intercell interference is undoubtedly intricate. Unfortunately, the current literature misses its comprehensive evaluation, as the effects of noise and cross-stream correlation are often overlooked. Furthermore, computationally friendly expressions of the coverage probability allowing engineering insights and adaptive system design are lacking. For multistream MIMO zero-forcing beamforming, in this paper we tackle these issues by considering scenarios where a receiver is in the coverage if all of its data-streams are successfully decoded. Assuming the max signal-to-interference-plus-noise ratio (SINR) cell association (CA), we adopt the stochastic geometry tools to provide an upper bound and an easy-to-compute closed-form lower bound on the coverage probability, while their accuracies are confirmed against extensive simulations. Our contributions are as follows. We prove that full correlation of data streams of a given link slightly reduces the coverage performance. We show that from a coverage probability perspective, the single stream communication is preferable. We exploit our analysis to explore several pertinent design issues, which have not fully discussed in the literature. Our results demonstrate tradeoffs between densification and multiplexing gains. We, further, see that by appropriately designating feedback channel with modest capacity 8 bits per frame per user, the spatial throughput grows by nearly 180 $\%$ over the conventional 1-bit feedback scenario. Finally, We present important extensions of our analysis to underlay spectrum sharing, practical aspects of the max-SINR CA, and a nonhomogeneous path loss environment. [ABSTRACT FROM PUBLISHER]

In this paper, a low-complexity detection scheme is proposed for an underdetermined multiple-input–multiple-output (UD-MIMO) wireless communication system that employs $N$ transmit antennas and M < N$ receive antennas. The proposed scheme combines a simplified parallel interference cancelation (S-PIC) with the block decision feedback equalization (BDFE) algorithm. To account for the extra (N - M)$-dimension in the transmitted signal, the UD-MIMO system is partitioned into two subsystems: one with (N - M)$ transmit antennas and the other one with M sequences in the first subsystem, with $Q$ being the constellation size, the proposed scheme explores only a small number of candidate sequences in the first subsystem; thus, it achieves significant complexity reduction. Two new candidate sequence selection methods are proposed. In the first iteration, the candidate sequences used for PIC are selected by exploring the statistical properties of the received signals. In the second iteration and beyond, the set containing the candidate sequences is constructed by utilizing the soft information generated from the previous iteration. The proposed scheme provides a balanced tradeoff between computational complexity and bit error rate (BER) performance. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a novel low-complexity beamforming algorithm for multiuser successive maximum ratio transmission (MS-MRT) toward space-division multiplexing to achieve video quality maximization in the downlink of a multiuser (MU) multiple-input–multiple-output (MIMO) orthogonal frequency-division multiple-access (OFDMA)-based fourth-generation (4G) wireless network. We compare the performance of this algorithm in terms of system throughput and video quality with the two popular precoding techniques, namely, block diagonalization (BD) and successive optimization (SO). We also compare its performance with the generalized versions of these two algorithms termed coordinated transmit–receive processing (CTR)-BD and CTR-SO algorithms, respectively. Further, we propose an extension of the MS-MRT scheme to broadcast scenarios, termed broadcast successive maximum ratio transmission (BS-MRT), which computes the optimal broadcast beamforming vector to maximize the video quality at each of the broadcast group members while maintaining orthogonality to the previously scheduled user groups. We also demonstrate that the proposed MS-MRT and BS-MRT schemes can be naturally adapted to the context of various MU OFDMA scheduling algorithms such as proportional fairness (PF) and round robin (RR), to name a few, to maximize video quality through optimal scheduling in the presence of a large number of users. We discuss implementations of the proposed MS-MRT scheme in association with these scheduling algorithms for MU unicast and broadcast video transmission scenarios. The simulation results presented in this work rely on the rate models derived using the Joint Scalable Video Model (JSVM) software developed by the Joint Video Team (JVT) and are, thus, readily applicable in practice. The presented results clearly demonstrate the ability of the proposed algorithm to maximize the video quality in comparison with the other competing MU MIMO precoding techniques. Further, employing the proportional fair scheduling algorithm in conjunction with the MS-MRT results in an overall enhancement in the received video quality compared with the RR and max-rate algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, system design for a multiple-input–multiple-output (MIMO) relay broadcast channel with individual signal-to-interference-plus-noise ratio (SINR) constraints at mobile stations (MSs) is considered. By exploring the structure of downlink–uplink duality at either the base station (BS) or the relay station (RS), we propose two schemes of joint power allocation and beamforming design at the BS and the RS. The problem of the existence of feasible solutions under practical power constraints at the BS and the RS with given SINR targets is considered first. Then, the problem of sum power minimization is considered. Each design problem can be efficiently solved using optimal joint power allocation and beamforming under the framework of convex optimization. We also show that with subchannel pairing at the RS, the transmission power can be further reduced. Finally, a generalization to the multihop scenario is provided to further improve power efficiency. [ABSTRACT FROM PUBLISHER]

This paper studies robust interference mitigation against the imperfectness of channel knowledge involved in the interference link of a multiple-input–multiple-output (MIMO) cognitive radio (CR) system that coexists with a primary radio (PR) system via opportunistic spectrum-sharing (OSS) scheme. The robust design leads to a seemingly complicated matrix-valued problem. Nevertheless, we show that it can be equivalently converted into two convex semidefinite programs (SDPs). One of them is identified as a null-forcing approach with closed-form power allocation, and the other can be reduced to a convex scalar power allocation subproblem by properly relaxing the interference constraint. Numerical results demonstrate significant performance gain of the robust design over previous nonrobust strategies. [ABSTRACT FROM PUBLISHER]

In multi-user downlink small cell networks, cooperative resource allocation (RA) within a small cell cluster is a key technique to enhance network capacity. However, capacity-maximizing RA in frequency-selective fading channels requires global channel state information (CSI) of users within a small cell cluster, which makes it infeasible in practical networks with limited direct link capacity. To circumvent this global CSI assumption, most of the existing studies on RA have been based on several CSI assumptions such as local CSI and local CSI at the transmitters (CSIT). Nevertheless, cost functions with local CSI or local CSIT in the literature rely on heuristic formulations, because the sum-rate cannot be computed if without global CSI. In this paper, we propose a deep reinforcement learning-based RA algorithm to maximize the sum-rate for any given limited information on instantaneous CSI or sum-rate at the previous period. The proposed scheme is not restricted to certain CSI assumptions, but attempts to find the best RA for any given information such as quantized local CSI and quantized local CSIT; thus, it is applicable to any given direct link capacity. The proposed algorithm is self-adaptive in time-varying channels, since it is not divided into training and test phases. We modify the target neural network (TNN) scheme to enhance the sum-rate and the convergence speed. Numerical simulations confirm that: i) the proposed algorithm outperforms the conventional algorithms even under the same CSI assumption such as local CSI and local CSIT; ii) a flexible trade-off between the amount of CSI and the sum-rate is realizable in practical systems. [ABSTRACT FROM AUTHOR]

Interrelay interference (IRI) is known to limit the performance of virtual full-duplex (VFD) relaying schemes. Available interference cancelation schemes are unable to simultaneously improve the diversity and maintain the multiplexing gain of VFD relaying schemes in multiple antennas scenarios. In this paper, we propose a technique to improve the reliability of multiantenna VFD relaying scheme, while maintaining the multiplexing gain in the presence of IRI. In the proposed scheme, the source and interrelay channels are concatenated and their signals are jointly decoded at the relay. A superposition of the decoded messages is forwarded to the destination. To reduce the effect of IRI on the receiving relay, two suboptimal relay transmit antenna selection schemes, namely, random antenna selection and maximum capacity antenna selection, are investigated. The system capacity and outage probability bounds of the proposed scheme are derived in closed form. The diversity and multiplexing tradeoff is also characterized. The analytical and numerical results show that the proposed scheme can achieve full diversity and maintain the multiplexing gain of the full-duplex relaying scheme. Also, the proposed scheme can outperform conventional VFD relaying scheme in terms of reliability even in the presence of IRI. [ABSTRACT FROM PUBLISHER]

In this paper, we study the uplink in a single-cell massive multiple-input–multiple-output system. The base station (BS) is equipped with three antenna arrays, each covering one third of the cell area. Each antenna array comprises a large yet finite number of antennas. The single-antenna users are randomly and uniformly distributed in the cell, transmitting to the BS utilizing full channel inversion power control. All users experience Rician fading. Receiver maximum-ratio-combining is performed at the BS. Under such a setting, we focus on one cell sector and analyze the intrasector interference in a realistic situation where the number of BS antennas is not extremely large compared with the user number. In particular, we show that, due to the line-of-sight (LoS) component of the channel, the interference is partially determined by the angles of arrival of the signals. We approximate the LoS component interference by a Beta mixture. The interference in Rician fading is then modeled as a noncentral chi-square distribution with a random noncentrality parameter, corresponding to the LoS component. The approximate interference distribution can be used to compute signal-to-interference-ratio-dependent metrics such as outage probability and average throughput. [ABSTRACT FROM AUTHOR]

A multicell massive multiple-input multiple-output (MIMO) system, which utilizes a large number of base-station antennas to simultaneously serve a set of users, suffers from pilot contamination (PC) due to unavoidable reuse of pilots in adjacent cells. In this paper, a weighted-graph-coloring-based pilot decontamination (WGC-PD) scheme is proposed to mitigate PC for multicell massive MIMO systems. Specifically, based on limited cooperation among cells, an edge-weighted interference graph (EWIG) is first constructed to depict the potential PC relationship among users, whereby two users in different cells are connected by a weighted edge, indicating the strength of potential PC when they reuse the same pilot. Then, inspired by classical graph coloring algorithms, we develop the WGC-PD scheme by denoting each color as a pilot and each vertex as a user in the EWIG, which is able to mitigate PC by assigning different pilots to connected users with a large weight in a greedy way with insufficient pilot resource. Compared with exhaustive search among numerous pilot assignment solutions, the proposed WGC-PD scheme is able to mitigate PC with significantly reduced complexity, which is verified by numerical results. [ABSTRACT FROM PUBLISHER]

Due to the unique physical-layer characteristics associated with multiple-input multiple-output (MIMO) and cognitive radio (CR), the network performance is tightly coupled with mechanisms at the physical, link, network, and transport layers. In this paper, we consider an energy-efficient cross-layer optimization problem in multihop MIMO CR networks (CRNs) and provide a new formulation to balance the weighted network utility and the weighted power consumption of secondary users (SUs), with the minimum transmission rate constraint of primary users (PUs) and the SU power consumption constraint. However, this formulation is highly challenging due to the nonconvexity of the PU rate constraint. We propose a solution that features a linearization-based alternative optimization method and a heuristic primal recovery method. We further develop a distributed algorithm to jointly optimize the covariance matrix of the transmitted signal vector at each SU node, bandwidth allocation at each SU link, rate control at each session source, and multihop/multipath routing. Extensive simulation results demonstrate that the performance of the proposed distributed algorithm is very close to that of the centralized algorithm, and the proposed formulation provides an efficient way to save power consumption significantly, while achieving the network utility very close to that achieved with full power consumption. [ABSTRACT FROM PUBLISHER]

In this paper, resilient transmission in a multicell multiple-input multiple-output (MIMO) interference wiretap channel model is studied. Each base station (BS) transmits confidential messages to its intended legitimate user with multiple antennas in the presence of eavesdroppers that can overhear the transmission. We study the problem of finding the optimal transmit covariance matrices at the BSs to maximize the secrecy sum rate, which is typically nonconvex and intractable to obtain a globally optimal solution. A distributed iterative optimization algorithm based on a novel decomposition framework across all users is proposed. The decomposition framework preserves the convexity of the objective function and linearizes the nonconvex part. At each iteration, the BSs simultaneously solve a sequence of problems that are decoupled convex approximations of the original secrecy sum-rate function. Moreover, the complexity of the algorithm is analyzed. Numerical results are presented to validate the effectiveness of the proposed distributed algorithm. [ABSTRACT FROM PUBLISHER]

This paper studies the impact of a multiple-input–multiple-output (MIMO) relay on the $K$- user multiple-input–single-output (MISO) interference channel (IC) when the relay has delayed feedback (i.e., delayed channel state information (CSI) or delayed channel output feedback) from each receiver, yet each transmitter has no knowledge about CSI. We first develop a new relay-aided retrospective interference alignment (r-RIA) and characterize the optimal sum degrees of freedom (DoFs) for the $K$- user MISO IC with a MIMO relay by providing a new matching outer bound. It is shown that the sum DoF does not decrease, even in the absence of direct links between transmitters and receivers, as long as $K$ is sufficiently large. We next show that a MIMO relay can provide a sum-DoF gain in the $K$- user MISO IC with delayed feedback to the relay in the absence of CSI at transmitter (CSIT), whereas relaying is shown to be not useful with instantaneous CSIT from the DoF perspective. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of mode switching in multiple-input–multiple-output (MIMO) broadcast channels utilizing the Per-User Unitary Rate Control (PU2RC) transmission scheme is considered. Since there is no mathematical expression for the achievable rate of the PU2RC systems, it is proposed to approximate them using proper bounds. It is shown that certain simple feedback distributions will lead to tight bounds on the achievable rates of the PU2RC systems. The proposed bounds are used for the calculation of mode-switching points and maximization of the system rate under different multiplexing order conditions. The asymptotic behavior of the preferred modes is also studied under high-signal-to-noise-ratio (SNR) and low-SNR conditions, and it is shown that the single-user transmission mode is the preferred mode for both regimes. [ABSTRACT FROM PUBLISHER]

In this paper, we study the performance of space-shift keying (SSK) modulation for multiple-input–multiple-output (MIMO) wireless systems in the presence of multiple-access interference. More specifically, a synchronous multiuser scenario is considered. The main technical contributions of this paper are given as follows: Two receiver structures based on the maximum-likelihood (ML) criterion of optimality are developed and analytically studied, i.e., single- and multiuser detectors. Accurate frameworks for computing the average bit error probability (ABEP) over independent identically distributed (i.i.d.) Rayleigh fading channels are proposed. Furthermore, simple and easy-to-use lower and upper bounds for performance analysis and system design are introduced. The frameworks account for the near–far effect, which significantly affects the achievable performance in multiple-access environments. In addition, we extend the analysis to generalized SSK (GSSK) modulation, which foresees multiple active antennas at the transmitter. With respect to SSK modulation, GSSK modulation achieves higher data rates at the cost of increased complexity at the transmitter. The performance of SSK and GSSK modulations is compared with that of conventional phase-shift keying (PSK) and quadrature amplitude modulation (QAM) schemes, and it is shown that SSK and GSSK modulations can outperform conventional schemes for various system setups and channel conditions. In particular, the performance gain of SSK and GSSK modulations increases for increasing values of the target bit rate and of the number of antennas at the receiver. Finally, we put forth the concept of coordinated multipoint (or network MIMO) SSK (CoMP-SSK) modulation as a way of exploiting network cooperation and the spatial-constellation diagram to achieve high data rates. Analytical derivations and theoretical findings are substantiated through extensive Monte Carlo simulations for many setups. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate a novel relaying technique employing scheduling, precoding, beamforming, and power allocation for a multiuser multiple-input–multiple-output (MU-MIMO) relay network. In the proposed scheme, the interference is canceled by using a combination of transmit–receive weights and Tomlinson–Harashima precoding (THP). To achieve data rate fairness among different users and further improve the performance of MU-MIMO relay networks, we propose a low-complexity power allocation (LC-PA) to allocate power to each user. In addition, an algorithm to select a subset of users that has maximum sum rate performance is proposed. The performance of the proposed scheme is investigated by examining the sum rate of the system for different user selection algorithms and different power allocation schemes. [ABSTRACT FROM PUBLISHER]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been deemed a promising technology to achieve high spectral efficiency. This paper investigates transmit power optimization for a multi-user multiple-input single-output (MISO) NOMA downlink system endowed with energy harvesting and physical layer security. More specifically, the system is designed to satisfy the data-link security requirements of its legitimate users while charging energy harvesting devices. To achieve that goal, we investigate a joint design on beamforming vectors and artificial noise (AN) covariance matrix. Then, an iterative difference-of-two-convex-function (D.C.) algorithm is proposed by applying the successive convex approximation (SCA) approach. To further reduce the computational complexity, a sub-optimal alternating D.C. (ADC) algorithm is devised by decoupling beamforming and mapping the AN to the null space of legitimate users. In the ADC algorithm, optimal null space and beamforming vectors are alternately solved by convex programming. Furthermore, the convergence of the proposed D.C. and ADC algorithms is derived. Extensive simulation results show that the two proposed AN-aided algorithms significantly reduce the transmit power cost over OMA and NOMA scheme without AN, especially when there are more eavesdroppers. [ABSTRACT FROM AUTHOR]

User-centric ultra-dense network (UDN) has been considered a key enabler of high data rate and high reliable vehicle-to-infrastructure (V2I) communication. In this paper, an analytical framework is developed based on stochastic geometry to characterize the uplink V2I transmission performances, in terms of the outage probability, the average vehicle throughput and the average spatial throughput, particularly resolving two important but not well-understood factors in such networks: the spatial correlation in the interference powers among the cooperative roadside units (RSUs) as caused by the shared set of co-channel vehicles, and the combined vertical distance (CVD) owing to the lane width and the antenna height difference between the vehicle and the RSUs. Exact analytical expressions of the outage probability are derived for the general multiple association cases, a far-distance approximation method is introduced to reduce the computational complexity, and lower and upper bounds are obtained corresponding to two extreme assumptions of the spatial interference correlation. We show that the impacts of the spatial interference correlation can be significant and ignoring the correlation can lead to non-optimal system deployment, and that the far-distance approximation can approach well with the exact results. Meanwhile, although CVD diminishes the V2I uplink transmission performances, the diminution can be mitigated through RSU cooperation. [ABSTRACT FROM AUTHOR]

Deploying a large number of distributed access points (AP)s to serve a smaller number of users is one of the promising network architectures for future wireless communication systems. Such network architecture can be operated as a distributed massive multiple-input multiple-output (MIMO) system or as a small-cell (SC) system to satisfy the anticipated high rate requirements for beyond-5G networks. However, in a practical scenario with non-ideal hardware components and high-velocity users, the network experiences an inevitable performance degradation. This paper aims at analyzing the network performance under the operation of distributed massive MIMO and SC systems, taking into account the impairments of real and dynamic systems. Considering multiple-antennas APs, we derive novel closed-form expressions for the downlink (DL) spectral efficiency of both systems. We reveal that limiting the number of served users per AP in distributed massive MIMO systems leads to a corresponding loss in the performance, especially under max-min power control. Besides, despite the SC system provides the largest per-user average DL rate under the deployment of ideal APs, distributed massive MIMO systems become superior in the presence of non-ideal APs. Notably, while increasing the number of deployed non-ideal APs can reduce the introduced loss in distributed massive MIMO systems, this leads to an extra performance loss in SC systems. Finally, we show that the presence of high-velocity users is more harsh in SC systems. In addition, our results show that the SC system operation is more suitable for low-velocity users, however, it is better to operate networks with high velocities users under the distributed massive MIMO systems operation. [ABSTRACT FROM AUTHOR]

This paper investigates pilot design and allocation in multi-cell massive multiple-input multiple-output systems with two-tier receiving. As the length of pilot is limited, the pilots cannot be orthogonal and cause interference. The sum rate as well as the signal-to-interference-plus-noise ratio (SINR) of the system are firstly analyzed. The sum rate upper bound and the asymptotic SINR are derived. The analysis shows that the pilot correlation and the spatial correlation jointly affect the sum rate. Based on this observation, the discrete Fourier transform vectors are employed in designing pilots with various correlation values. Then, with the channel correlation information and the designed pilots, the pilots are allocated to the cells in a greedy way with the object of maximizing the sum rate upper bound. Moreover, the sum rate analysis, the pilot design, and the pilot allocation are extended to the scenario with grouped correlations. Simulation results show that the proposed pilot design and allocation performs better than other pilots and the derived upper bound is effective. [ABSTRACT FROM AUTHOR]

Different from the existing works, in this paper we investigate the pilot allocation in multi-cell massive multiple-input multiple-output (MIMO) systems, aiming to maximize the spectral efficiency (SE) subject to the constraint that the number of user equipments (UEs) satisfying the quality of service (QoS) is maximized. Since the considered bilevel optimization problem that is tough to handle, we resort to the greedy algorithms with low computational complexity. We propose a QoS constrained (QC) pilot allocation scheme, which sequentially allocates the pilot sequence having large interference power to the UE with small signal power so that the number of UEs satisfying QoS can be maximized and then the SE can also be maximized. Simulation results show that the propose QC scheme outperforms the conventional scheme and smart pilot allocation (SPA) scheme. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) is a key technology in fifth-generation (5G) networks. By using a large number of antenna elements placed in a 2-D array, an evolved Node B (eNB) can form multiple vertical beams in the elevation domain and adaptively track moving vehicles. Thus, the throughput and spatial multiplexing efficiency in vehicle-to-infrastructure (V2I) access can be significantly increased. However, multipath spatial propagation in wireless channels results in the angular spread of the power arrival profile, which causes intersector interference in massive-MIMO beamforming and becomes a limiting factor for the system capacity. In this paper, we investigate the channel propagation characteristics and the intervehicle interference in the elevation-domain spatial multiplexing for V2I mobile access and develop a packet-level channel model that can be used for system design and network protocol simulations. First, a measurement campaign for the urban macrocell street uplink channels was performed using a 3-D MIMO channel sounder, and the elevation power spectra (EPSs) on the eNB side were measured. Then, the intersector interference in the vertical beamforming is evaluated based on the antenna array pattern and channel EPS. Finally, a packet-level channel model in the form of a finite-state Markov chain (FSMC) is proposed for the V2I elevation multiplexing uplinks. The model describes the received signal-to-interference ratio (SIR) variation when a vehicle is moving toward an eNB. The steady-state distribution of the FSMC is analytically derived and verified by simulations. Based on the stochastic process of the SIR, the concepts of “large/small-scale multiplexing fading” are proposed. The field measurement results in this work have revealed the spatial power arrival profiles of the V2I street channels that are critical for the MIMO system design, and the proposed packet-level channel model provides an enabling tool for the analysis and simulation of the V2I elevation multiplexing links in the 5G networks. [ABSTRACT FROM PUBLISHER]

In this paper, we analyze the spectral efficiency of multicell massive multiple-input–multiple-output (MIMO) systems with downlink training and a new pilot contamination precoding (PCP) scheme. First, we analyze the spectral efficiency of the beamforming training (BT) scheme with maximum-ratio transmission (MRT) precoding. Then, we derive an approximate closed-form expression of the spectral efficiency to find the optimal lengths of uplink and downlink pilots. Simulation results show that the achieved spectral efficiency can be improved due to channel estimation at the user side, but in comparison with a single-cell scenario, the spectral efficiency per cell in multicell scenario degrades because of pilot contamination. We focus on the practical case where the number of base station (BS) antennas is large but still finite and propose the BT and PCP (BT-PCP) transmission scheme to mitigate the pilot contamination with limited cooperation between BSs. We confirm the effectiveness of the proposed BT-PCP scheme with simulation, and we show that the proposed BT-PCP scheme achieves higher spectral efficiency than the conventional PCP method and that the performance gap from the perfect channel state information (CSI) scenario without pilot contamination is small. [ABSTRACT FROM AUTHOR]

In this paper, we examine orthogonal space–time block coding with receiver maximal ratio combining (OSTBC/MRC) and selection combining (OSTBC/SC) in multiple-input–multiple-output (MIMO) decode-and-forward (DF) relay networks with underlay spectrum sharing, considering optimal and suboptimal cases. The secondary network under consideration is equipped with multiple correlated antennas at the source, the relay, and the destination. On the other hand, the primary network is composed of $L$ primary users (PUs), each of which is equipped with multiple correlated antennas. For the considered underlay spectrum sharing, the transmit power condition is related by an interference limit on the primary network and the maximum transmission power in the secondary network. In particular, new exact expressions for the outage probability of the adopted system models are obtained. Moreover, simple asymptotic expressions for the outage probability are provided to enable the characterization of the achievable diversity orders and coding gains. To enhance the secondary network performance, optimal power allocation (PA) between the secondary source and the secondary relay is obtained based on the asymptotic outage probability under the constraints of total allowable transmit power at the secondary user (SU) and maximum allowable interference power limit at the PU. The derived analytical formulas herein are supported by numerical results to clarify the main contributions. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in $K$-user multiple-input–multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMO-OFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is significantly increased by antenna selection in real-world scenarios. [ABSTRACT FROM AUTHOR]

Multiuser orthogonal frequency-division multiplexing (OFDM) and multiple-output multiple-output (MIMO) have been widely adopted to enhance the system throughput and combat the detrimental effects of wireless channels. Interference alignment has been proposed to exploit interference to enable concurrent transmissions of multiple signals. In this paper, we investigate how to combine these techniques to further enhance the system throughput. We first reveal the unique characteristics and challenges brought about by using interference alignment in diagonal channels. We then derive a performance bound for the multiuser (MIMO) OFDM interference alignment system under practical constraints and show how to achieve this bound with a decomposition approach. The superior performance of the proposed scheme is validated with simulations. [ABSTRACT FROM PUBLISHER]

Massive multiple-input–multiple-output (MIMO) antenna system implies the use of a large number of base station (BS) antennas to serve a relatively small number of user terminals (UTs) for extraordinary spectral efficiency. However, its performance is limited by pilot contamination due to unavoidable reuse of pilot sequences from UTs in different cells. In this paper, we analyze the performance of massive MIMO zero-forcing (ZF) systems using the time-shifted pilot scheme, which was known to combat pilot contamination effectively using conjugate beamforming if there is a very large number of antennas. We derive expressions for achievable sum rates and the signal-to-interference-plus-noise ratios (SINRs) of forward and reverse links if the number of BS antennas is finite. Then, the impact of system parameters, such as cell radius, transmit power, group number (a parameter related to the time-shifted pilot scheme), BS antenna number, etc., on the system performance are revealed. Our model embraces a series of previous works as special cases. Moreover, we compare the performance of conjugate and ZF precoders, from which a simple but effective large-scale fading-based UT scheduling scheme is proposed to enhance the system throughput. [ABSTRACT FROM PUBLISHER]

In this paper, we consider unicast/multicast multicell cooperative transmission with interference among users/user groups. In this context, we derive the optimal minimum variance distortionless response (MVDR)-based successive minimum variance beamforming (SMVB) scheme that achieves a superior sum-rate performance compared with the block diagonalization scheme. Subsequently, we derive an optimal joint power allocation and broadcast beamforming scheme for multicell cooperative broadcast transmission for a pooled power constraint at the base stations. This scheme is extended to include per base station power constraints by formulating it as a relaxed semi-definite program (SDP). We also consider the multicell cooperative uplink scenario and derive a successive multiuser (MU) uplink beamforming (SMUB) scheme that maximizes the signal-to-interference-plus-noise ratio (SINR) of each user. Next, we consider imperfect channel state information (CSI) and derive a robust beamforming scheme for the downlink, based on minimizing the worst-case interference by formulating it as a second-order cone program. It is demonstrated that the corresponding robust beamformer for the uplink transmission can be derived by employing the multidimensional covariance fitting approach. Simulation results are presented to demonstrate the superior sum-rate performance of the proposed multicell transmission schemes. The performance is also compared with several bounds for cooperative multicell scenarios. [ABSTRACT FROM AUTHOR]

This paper investigates the precoding design for multicast transmission in multicell massive multiple-input multiple-output (MIMO) systems with finite-alphabet inputs. The users within each cell are interested in common information, and different cells provide distinct information. Focusing on the weighted max–min fairness (MMF) problem with only statistical channel state information at the base station, we provide the necessary conditions of the optimal precoding vectors to maximize the minimum weighted achievable ergodic rate, and an iterative algorithm is proposed to optimize the precoding vectors. To achieve lower computational complexity, we then derive a lower bound on the achievable ergodic rate for finite-alphabet inputs. Considering the problem of the minimum weighted rate lower bound maximization, we utilize the concave–convex procedure (CCCP) to develop a CCCP-based algorithm, which is proven to converge to a local optimum. Furthermore, exploiting the channel characteristic in massive MIMO systems, we prove that the optimal precoding vectors, maximizing the minimum weighted rate lower bound, are linear combinations of eigenvectors of transmit correlation matrices, and the original problem can be shifted into a lower dimensional space. Motivated by this insight, a relation-based algorithm is devised to obtain the optimal solution of the weighted MMF problem by using the duality between the MMF problem and the quality of service problem. Numerical results illustrate the tightness of the achievable ergodic rate lower bound and the significant performance of the devised algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we propose two groups of recursive codes, namely the Hadamard recursive carrier interferometry (HRCI) codes and diagonal recursive carrier interferometry (DRCI) codes, to simultaneously reduce the peak-to-average power ratio (PAPR) and suppress the phase noises and residual carrier frequency offset (RCFO) for high-speed orthogonal frequency division multiplexing (OFDM) systems. We exploit the recursion property of the Hadamard and diagonal matrices to constitute the proposed HRCI code and DRCI code using the carrier interferometry (CI) code, and present the system model in details to spread OFDM symbols in the frequency domain. Then, we prove that both HRCI and DRCI generation matrices keep their invertibility during the recursions. As a direct result of the new code design, the phase intervals are enlarged and the signals are shifted in the time domain, thus both the PAPR and the phase noises are reduced, and the RCFO can be mitigated. Moreover, the enlarged phase intervals enable the transceiver blocks including the channel estimator, which estimate the phase noise based on the received signals, to improve the performance. Furthermore, we present the expressions for the HRCI and DRCI embedded transmitted and received signals, and derive the analytical signal-to-interference-plus-noise ratio (SINR) expressions for bit error rate (BER) performance analysis. Then, we analyze the effects of presented codes on the phase differences and provide the computational complexity analysis. Numerical simulations verify the effectiveness of our theoretical analysis of SINR. Additionally, under different parameter settings, which consider the working conditions of practical systems, we demonstrate that the presented robust HRCI and DRCI coded OFDM systems can suppress the PAPR satisfactorily and better BER performances can be achieved by the recursive CI-aided spread OFDM systems with phase noise rejection and RCFO compensation when compared with counterpart systems. [ABSTRACT FROM AUTHOR]

Edge caching is emerging as the most promising solution to reduce the content retrieval delay and relieve the huge burden on the backhaul links in the ultra-dense networks by proactive caching popular contents in the small base station (SBS). However, constraint cache resource of individual SBSs significantly throttles the performance of edge caching. In this paper, we propose a device-to-device (D2D) assisted cooperative edge caching (DCEC) policy for millimeter (mmWave) dense networks, which cooperatively utilizes the cache resource of users and SBSs in proximity. In the proposed DCEC policy, a content can be cached in either users’ devices or SBSs according to the content popularity, and a user can retrieve the requested content from neighboring users via D2D links or the neighboring SBSs via cellular links to efficiently exploit the cache diversity. Unlike existing cooperative caching policies in the lower frequency bands that require complex interference management techniques to suppress interference, we take advantage of directional antenna in mmWave systems to ensure high transmission rate whereas mitigating interference footprint. Taking the practical directional antenna model and the network density into consideration, we derive closed-form expressions of the backhaul offloading performance and content retrieval delay based on the stochastic information of network topology. In addition, analytical results indicate that, with the increase of the network density, the content retrieval delay via D2D links increases significantly while that via cellular links increases slightly. Comprehensive simulations validate our theoretical analysis and demonstrate that the proposed policy can achieve higher performance in offloading the backhaul traffic and reducing the content retrieval delay compared with the state-of-the-art most popular caching policy. [ABSTRACT FROM AUTHOR]

The challenges of millimeter-wave (mmWave) radio propagation in dense crowded environments require dynamic re-associations between the available access points (APs) to reduce the chances of losing the line-of-sight path. However, the antenna beamsearching functionality in the mmWave systems may introduce significant delays in the course of AP re-association. In this paper, we analyze user performance in dense urban mmWave deployments that are susceptible to blockage by the dynamically moving crowd. Our approach relies on the ergodic capacity as the key parameter of interest. We conduct a detailed evaluation with respect to the impact of various system parameters on the ergodic capacity, such as AP density and height, blocker density and speed, number of antenna array elements, array switching time, degree of multiconnectivity, and employed connectivity strategies. Particularly, we demonstrate that dual connectivity delivers the desired performance out of all possible degrees of multiconnectivity, and there is an optimal density of mmWave APs that maximizes the capacity of cell-edge users. We also show that the use of low complexity “reactive” multiconnectivity design, where the beamtracking is only performed when the currently active connection is lost, together with the utilization of iterative beamsearching algorithms, does not significantly deteriorate the ergodic capacity. [ABSTRACT FROM AUTHOR]

In this paper, we consider a signal-level maximum likelihood detection for multiple-input multiple-output filter-bank multicarrier-quadrature amplitude modulation (MIMO FBMC-QAM) system with two prototype filters. Under high-frequency selective channels, the conventional symbol-level maximum likelihood detection suffers from degraded bit error rate performances because it cannot utilize the oversampling characteristics of the signal-level. However, due to intrinsic interference and high computational complexity, a maximum likelihood detection cannot be applied directly to the signal-level. To solve this problem, we propose a signal-level maximum likelihood detection based on partial candidates. Utilizing the diagonal dominant characteristics of effective channels, the proposed signal-level maximum likelihood detection can reduce the effect of intrinsic interference with practical computational complexity. Moreover, a region ordering algorithm based on Euclidean distance can improve the efficiency of the proposed signal-level maximum likelihood detection. Simulation results show that the proposed signal-level maximum likelihood detection can outperform the bit error rate performance of the conventional symbol-level maximum likelihood detection. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new constellation design for a non-coherent massive single input multiple output (m-SIMO) uplink system based on M-DPSK suitable for Rician channels. Under Rician propagation, the non-coherent systems proposed until now cannot completely remove the interference. This new design takes into account the inter user and inter symbol interferences in order to convert them into useful terms that help us in the non-coherent detection. We propose an algorithm to non coherently detect the joint symbol with the information from all users leveraging the characteristics of the new constellation. In addition, the signal-to-interference-plus-noise ratio is derived and is used to present analytical bounds for the symbol error rate. It is shown that the analytical results tightly match the numerical simulation. We show that with the proposed constellation and detection algorithm we are able to leverage the line-of-sight component of the Rician propagation, obtaining a better performance than with Rayleigh channels. [ABSTRACT FROM AUTHOR]

This paper proposes a widely linear processing framework for multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) downlink systems. In the framework, a widely linear MIMO-NOMA (WL-MIMO-NOMA) model is derived by assuming that the base station transmits real-valued downlink signals. WL-MIMO-NOMA adopts complex-valued power allocation coefficients to stagger the user signals in phase. The main features of WL-MIMO-NOMA are the following: first, in general case, WL-MIMO-NOMA can remove all the inter-cluster interference and at least half of the intra-cluster interference; and second, in user pairing case, both interferences can be completely eliminated. This is distinct from the existing work where real power coefficients are used, which cannot guarantee the complete separation of the paired user signals because the signals transmitted to the paired users are overlapped in phase. In addition, the closed-form expressions of outage probabilities are derived. The phase difference of the complex power coefficients is optimized to minimize the outage probability. It is proven that, with the optimal phase difference, successive interference cancellation is unnecessary in user pairing case. Finally, the framework is extended to the mixed case of real/complex circular signals. Simulation results show that the proposed framework outperforms the existing work, and the numerical results agree well with the analytical analysis. [ABSTRACT FROM AUTHOR]