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This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate joint retrospective interference alignment (RIA) and caching schemes for multiple-input single-output (MISO) broadcast channels (BC) with delayed channel state information at the transmitter (CSIT). By exploiting the cached content, we propose one sophisticated cache-aided RIA scheme to cancel the interference. Importantly, our scheme takes the number of symbols in a packet into account, as different number of symbols in a packet result in different system configuration, which may have significant impact on the design of the transmission scheme and achievable degrees of freedom (DoF). Furthermore, we present two theorems to quantify the achievable sum DoF of the proposed cached-aided RIA scheme for different system configuration. Moreover, the system configuration of the existing cache-aided RIA scheme with mixed CSIT can be treated as a special case in our paper. And also our scheme can simultaneously support more users than the existing cache-aided RIA scheme with mixed CSIT to invoke zero forcing (ZF) precoding, which limits the number of users simultaneously supported. [ABSTRACT FROM AUTHOR]

In Multiple-input multiple-output (MIMO) broadcast channels (BCs), the transmitter simultaneously broadcasts signals to multiple receivers at same frequency band, resulting in that the communication capacity is affected by both interference, channel fading and random noise. Although channel fading can be mitigated by transceivers, the signal-to-noise-ratio (SNR) of the practical communication system is still dynamically changing due to the randomly changing noise. Traditional MIMO transceiver optimization algorithms can not flexibly adapt to the dynamic changes of SNR, resulting in large performance degradation. In this paper, we comprehensively consider signal power and signal space dimensions of the received signal in MIMO BCs, and propose two transceiver optimization algorithms which can dynamically adapt to the variance of SNRs. In the proposed algorithms, SNR is adopted to be an adjustment factor to cope with its variance. When SNR is low, i.e, large noise, the algorithm parameters are automatically adjusted so that the signal power is preserved as much as possible to combat the loss of communication capacity caused by large random noise. Correspondingly, under the condition of high SNR environment, the algorithm parameters are adjusted automatically to effectively compress the inter-user-interference (IUI) and intra-user-inter-stream-interference (ISI) by optimizing signal space dimensions. Simulation results show that in different SNR environments, the proposed algorithms can automatically adjust the focus of optimization, so that the optimization of signal power and signal space dimensions can automatically adapt to different SNRs. Compared with traditional transceiver optimization algorithms, the proposed algorithms can improve the communication capacity within a large dynamic range of SNR. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of weighted sum-rate maximization and mean squared error (MSE) minimization for the multiple-input multiple-output (MIMO) interference channel. Specifically, we consider a weighted minimum MSE architecture where each receiver employs successive interference cancellation (SIC) to separate the various received data streams and derive a hybrid beamforming scheme, where the transmitters operate with a number of radio frequency chains smaller than the number of antennas, particularly suited for millimeter-wave channels and 5G applications. To derive our proposed schemes, we first study the relationship between sum-rate maximization and weighted MSE minimization when using SIC receivers, assuming fully digital beamforming. Next, we consider the important—and, as it turns out, highly non-trivial—case where the transmitters employ hybrid digital/analog beamforming, developing a distributed joint hybrid precoding and SIC-based combining algorithm. Moreover, for practical implementation, we propose a signaling scheme that utilizes a common broadcast channel and facilitates the acquisition of channel state information, assuming minimal assistance from a central node such as a cellular base station. Numerical results show that both the proposed weighted MMSE-SIC schemes exhibit great advantages with respect to their linear counterparts in terms of complexity, feedback information, and performance. [ABSTRACT FROM AUTHOR]

In cell-free large-scale distributed antenna systems (L-DASs), the antennas are distributed over the intended coverage area. Introducing cooperation among the antennas can significantly improve the system throughput. However, only finite-cluster-size (limited) cooperation with L-DAS antenna clusters is realistic due to practical limitations. In this paper, the impact of antenna cluster size on the downlink sum rate of frequency-division duplex (FDD) cell-free L-DASs is analyzed, considering imperfect channel state information (CSI) and intercluster interference (ICLI). We investigate the optimal cluster size in terms of maximizing the downlink sum rate with respect to the overhead of imperfect channel training and feedback. When the number of users is sufficiently large, closed-form lower bounds of the ergodic sum capacity, which are leveraged to analyze the system performance, are derived by constructing different rate-achieving user-scheduling schemes. Both analog and digital feedback schemes are considered to evaluate the imperfect channel feedback. Based on these, closed-form expressions of the optimal cluster size for 1-D antenna topology systems and the corresponding achievable rates are derived. The scaling law of the optimal cluster size for 2-D antenna topology systems is also given. Numerical results demonstrate the impact of the signal-to-noise ratio (SNR) and the block length on the achievable rates and the optimal cluster size, which agree with our analytical results. [ABSTRACT FROM PUBLISHER]

In this paper, we present novel precoding methods for multiuser Rayleigh fading multiple-input–multiple-output (MIMO) systems when channel state information (CSI) is available at the transmitter (CSIT) but not at the receiver (CSIR). Such a scenario is relevant, for example, in time-division duplex (TDD) MIMO communications, where, due to channel reciprocity, CSIT can be directly acquired by sending a training sequence from the receiver to the transmitter(s). We propose three transmit precoding schemes that convert the fading MIMO channel into a fixed-gain additive white Gaussian noise (AWGN) channel while satisfying an average power constraint. We also extend one of the precoding schemes to the multiuser Rayleigh fading multiple-access channel (MAC), broadcast channel (BC), and interference channel (IC). The proposed schemes convert the fading MIMO channel into fixed-gain parallel AWGN channels in all three cases. Hence, they achieve an infinite diversity order, which is in sharp contrast to schemes based on perfect CSIR and no CSIT, which, at best, achieve a finite diversity order. Further, we show that a polynomial diversity order is retained, even in the presence of channel estimation errors at the transmitter. Monte Carlo simulations illustrate the bit error rate (BER) performance obtainable from the proposed precoding scheme compared with existing transmit precoding schemes. [ABSTRACT FROM PUBLISHER]

Massive deployment of low data rate Internet of things and eHealth devices that require high reliability motivates the development of practical precoding and user selection techniques. In this paper, we show that throughput and communications reliability can be improved by incorporating knowledge of modulation type in the design of the multiuser transmit precoder. The transmission of low data rate one-dimensionally modulated signals in a broadcast channel is considered. The transmit precoding matrix is determined by minimizing the weighted sum of error probabilities of users. Although the proposed minimum probability of error (MPE) precoding problem is nonconvex and highly nonlinear, it is solved by the alternating minimization of two convex subproblems. A reduced-complexity version of convex MPE precoding is then introduced, which exponentially reduces the complexity of the problem. Numerical results show that the proposed precoding techniques significantly improve system performance in broadcast channels. A user selection algorithm, compatible with MPE precoding, is also proposed that selects users if their error probabilities can approach zero. Based on line packing principles in Grassmannian manifolds, it is shown that the number of selected users could potentially be more than the number of transmit antennas, which translates to supporting more simultaneous users in the shared channel compared to existing user selection methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider spectrum sharing between cognitive radio (CR) users and a licensed primary user (PU) to enhance the spectrum efficiency. In the considered scenario, the PU is not able to successfully transmit data to the intended receiver. In this case, the cognitive base station (CBS) in the vicinity of the primary network offers its help to transmit the primary data. In return, the CR system shares the spectrum with the primary system. In particular, we formulate an opportunistic spectrum sharing approach that determines the optimal beamforming weights at the CBS to maximize the overall worst throughput of the CRs while guaranteeing a certain quality of service (QoS) for the PU. Various formulations of beamforming are proposed, which consider different relaying scenarios, including robust designs that are applicable with imperfect channel state information (CSI) at the PU. The original optimization problems are nonconvex and do not have any closed-form solutions. However, using a convex optimization approach, we transform them into convex forms and find approximate solutions using semidefinite programming (SDP) along with randomization techniques. We consider different examples that demonstrate the efficiency of the proposed approach. [ABSTRACT FROM PUBLISHER]

On the multiantenna broadcast channel, the spatial degrees of freedom support simultaneous transmission to multiple users. The optimal multiuser transmission, which is known as dirty paper coding, is not directly realizable. Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are sensitive to channel state information (CSI) inaccuracy. This paper considers a more practical design called per user unitary and rate control (PU2RC), which has been proposed for emerging cellular standards. PU2RC supports multiuser simultaneous transmission, enables limited feedback, and is capable of exploiting multiuser diversity. Its key feature is an orthogonal beamforming (or precoding) constraint, where each user selects a beamformer (or precoder) from a codebook of multiple orthonormal bases. In this paper, the asymptotic throughput scaling laws for PU2RC with a large user pool are derived for different regimes of the signal-to-noise ratio (SNR). In the multiuser interference-limited regime, the throughput of PU2RC is shown to logarithmically scale with the number of users. In the normal SNR and noise-limited regimes, the throughput is found to scale double logarithmically with the number of users and linearly with the number of antennas at the base station. In addition, numerical results show that PU2RC achieves higher throughput and is more robust against CSI quantization errors than the popular alternative of zeroforcing beamforming if the number of users is sufficiently large. [ABSTRACT FROM AUTHOR]

The secure degrees of freedom (SDoF) of two-user rank-deficient multiple-input multiple-output (MIMO) broadcast channel with confidential messages (BCCM) and two-user rank- deficient MIMO interference channel with confidential messages (ICCM) are studied respectively in this paper. In the systems, each transmitter has $M$ antennas, and each receiver has $N$ antennas. We consider that each transmitter intends to send secure messages to the corresponding receiver, and another receiver can receive the messages but cannot decode them, which ensures that the messages are confidential. Comparing with previous studies on two-user broadcast channel and interference channel, we explore the case that channel matrices are rank-deficient, and the rank of channel matrices can take arbitrary value, $D \leq \text{min} (M,N)$. For the two rank-deficient channels, BCCM and ICCM, we divide the problem into several regimes according to the different configurations of the rank of channel matrices and the number of antennas at each node. The outer bound of rank-deficient BCCM is inferred from information theoretic methods and the achievable schemes are given by zero forcing techniques. We derive the outer bound of rank-deficient ICCM by taking the minimum region of the three outer bounds, where the first outer bound is the result of rank-deficient interference channel model without secrecy constraints, the second outer bound is obtained by considering secrecy constraints, and the third outer bound is achieved by transmitters cooperation. Then we present the achievable schemes by combining zero-forcing, real interference alignment, and spatial alignment. Finally, we determine the exact SDoF of the rank-deficient BCCM and the rank-deficient ICCM. [ABSTRACT FROM AUTHOR]

In this paper, we study the secrecy performance of a $K$ -user multi-input single-output (MISO) broadcast channel with random beamforming (RB), where the transmitter is equipped with $N$ antennas, and the eavesdropper has $N_e$ antennas. We first propose a signal-splitting random beamforming (SSRB) scheme for a single-user MISO wiretap channel, and then improve the SSRB scheme with power-minimizing (PM), which is called a PM-SSRB scheme. To improve the spectral efficiency of a multiuser network, we combine PM with non-orthogonal multiple access (NOMA), and propose a hybrid NOMA (H-NOMA) scheme and a signal-splitting NOMA (SS-NOMA) scheme for the $K$ -user MISO wiretap channel, respectively. The sum ergodic secrecy rate of the $K$ -user scenario is analyzed comprehensively, and a closed-form expression for the lower bound on the ergodic secrecy rate is also derived for the single-user case. Simulation results show that, compared with the traditional hybrid artificial fast-fading scheme (AFF) and artificial noise (AN) scheme, the proposed SSRB scheme and PM-SSRB scheme perform much better in terms of the ergodic secrecy rate in all power regimes. More importantly, when the eavesdropper has more antennas than the transmitter, our schemes always outperform the AFF and AN schemes. The PM-SSRB scheme is also shown to be superior to the secret-key AFF scheme. For the multiuser case, the SS-NOMA scheme can achieve higher ergodic secrecy rate than the H-NOMA scheme. [ABSTRACT FROM AUTHOR]

This paper considers the $K$-user multiple-input–single-output (MISO) broadcast channel with delayed channel state information at the transmitter (CSIT) where the base station has only two antennas. Based on the MAT

Named after M. A. Maddah-Ali and D. Tse [1]. [ABSTRACT FROM PUBLISHER]

A significant issue in vehicular ad hoc networks (VANETs) is the design of an effective broadcast scheme that can facilitate the fast and reliable dissemination of emergency warning messages in the vicinity of an unexpected event, such as a traffic accident. In this paper, we propose a novel solution to this problem, which we refer to as speed adaptive probabilistic flooding. The scheme employs probabilistic flooding to mitigate the effects of the broadcast storm problem, which is typical when using blind flooding, and its unique feature is that the rebroadcast probability is adaptively regulated based on the vehicle speed to account for varying traffic densities within the transportation network. The motivation behind this choice is the identification of the existence of phase transition phenomena in probabilistic flooding in VANETs, which dictate a critical probability being affected by the varying vehicle traffic density and are shown to be linearly related to the vehicle speed (a locally measurable quantity). The scheme is evaluated using simulations on different sections of the freeway system in the City of Los Angeles, CA, USA. Simulation results indicate that the proposed scheme fulfills its design objectives, as it achieves high reachability and low latency of message delivery with low overhead in a number of representative scenarios. The scheme is also shown to outperform existing solutions, including Global-Positioning-System-based, and exhibits robustness with respect to different road topologies and parameters such as the transmission range of vehicles and the number of hops. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a contention intensity based distributed coordination (CIDC) scheme for safety message broadcast. By exploiting the high-frequency and periodical features of the safety message broadcast, the application-layer design of the CIDC enables each vehicle to estimate the instantaneous channel contention intensity in a fully distributed manner. With the contention intensity information, the media access control layer design of CIDC allows vehicles to adopt a better channel access strategy compared to the 802.11p. This is because CIDC selects the initial back-off counter for each new packet deterministically, i.e., based on the contention intensity, rather than randomly. The proposed CIDC is modeled, and key performance indicators in terms of the packet collision probability and average contention delay, are derived. It is shown that the proposed change in the initial counter selection leads to a system model completely different from the classic Markov chain based model. Moreover, the proposed CIDC, fully distributed and compatible with the 802.11p, can achieve both a much lower collision probability and a smaller contention delay compared with 802.11p at the cost of a small communication and computation overhead. Extensive simulation results demonstrate the effectiveness of the CIDC in both of the accurate and the erroneous contention intensity estimation scenarios. [ABSTRACT FROM AUTHOR]

Emergence of ultradense networks in 5G communications, Internet of things, and eHealth devices prompts us to develop new communication techniques that can support a large number of low data rate devices. In particular, it has been shown that when the data are real-valued and the observation is complex-valued, widely linear (WL) estimation can be employed in lieu of linear estimation to improve the performance. With these motivations, we study user selection and transmit precoding in multiuser communication systems assuming transmitted signals are one-dimensionally modulated. A closed-form solution for widely linear maximum signal-to-leakage-and-noise ratio precoding is obtained. We also investigate the design of WL maximum ratio transmission, WL zero-forcing, and WL minimum mean square error precoding techniques. Furthermore, to enable an increased number of communication devices, a user selection algorithm compatible with widely linear processing of one-dimensionally modulated signals is proposed. The proposed user selection algorithm can potentially double the number of simultaneously selected users compared to that of conventional user selection methods. [ABSTRACT FROM AUTHOR]

The most important application of vehicular networks is the dissemination of safety information via broadcasting protocols. How to reduce the redundant retransmission of the same information to avoid excessive channel collisions while ensure low latency and high reliability of the dissemination over the network has become the most challenging problem for multi-hop broadcasting protocols. The existing solutions use either probability-based multi-hop broadcasting for low latency or time-based deterministic approaches for high reliability. In this work, we propose a new probability-based multi-hop broadcast protocol to overcome the reliability and latency issues. First, we propose to assign a higher forwarding probability to the nodes that are farther from the source node by using a node's index number and other parameters, which is different from the existing probability-based approaches. The parameters can be adjusted for a higher forwarding success probability and maintain the required reliability of the message delivery. Second, we propose a clustering architecture so that redundancy and latency issues can be significantly reduced. Third, we analyze the protocol performance, such as the forwarding success probability, the average number of copies, and the average one-hop delay. The effectiveness of the proposed protocol has been demonstrated by extensive simulation results with significantly improved network performance. [ABSTRACT FROM AUTHOR]

An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI). [ABSTRACT FROM AUTHOR]