Intelligent Reflective Surface Aided Multi-Way Communications

A two-hop multiple-input multiple-output (MIMO) relay network which comprises a multiple antenna source, an amplify-and-forward MIMO relay and many potential users are studied in this paper. Consider the achievable sum rate as the performance metric, a joint design method for the processing units of the BS and relay node is proposed. The optimal structures are given, which decompose the multiuser MIMO relay channel into several parallel single-input single-output relay channels. With these structures, the signal-to-noise ratio at the destination users is derived; and the power allocation is proved to be a convex problem. We also show that high sum rate can be achieved by pairing each link according to its magnitude. The sum rate of three broadcast strategies, time division multiple access (TDMA) to the strongest user, dirty paper coding (DPC), and beamforming (BF) are investigated. The sum rate bounds of these strategies and the sum capacity (achieved by DPC) gain over TDMA and BF are given. With these results, it can be easily obtained that how far away TDMA and BF are from being optimal in terms of the achievable sum rate.

Multiple input multiple output (MIMO) relay networks are wireless communication systems comprising of multiple nodes, each of which is equipped with multiple antennas. Information theories have shown that using multiple nodes to simultaneously relay a message can improve the capacity of source-to-destination communications. In this paper, we propose new relaying schemes for MIMO relay networks. The major concept behind the proposed schemes is to transform each of the MIMO relay channels into an equivalent triangular channel with positive real diagonal entries. By doing so, the resultant MIMO relay channel can simultaneously offer both distributed array gain (diversity gain obtained among relay nodes) and intranode array gain (diversity gain realized by multiple antennas of individual relay node) while maintaining the maximum spatial multiplexing gain (number of parallel data pipes). Based on this concept, three relaying schemes are derived that perform QR decomposition and phase control. Numerical results confirm that at least one of the proposed schemes outperforms the amplify-and-forward and the zero-forcing relaying schemes under various conditions. Moreover, we show that ratios of noise power level at relay and destination node have a great impact on capacities.

A multiple-input multiple-output (MIMO) relay network is composed of source, relay, and destination nodes, each of which is equipped with multiple antennas. Network information theory has shown that the use of multiple relay nodes in source and destination (S-D) communication makes the capacity of the S-D system logarithmically increase with the number of relay nodes. In [13], we proposed a MIMO relay scheme for a relay network with single source and destination pair; each of the multiple relay nodes performs QR decomposition of backward and forward channels in conjunction with phase control (QR-P-QR). In this paper, we extend this scheme to the MIMO relay network with multiple source and destination pairs. For this aim, we use the group nulling approach to decompose the multiple S-D MIMO relay channel to parallel independent S-D MIMO relay channels, and apply the QR-P-QR scheme in each of the decomposed MIMO relay links. Numerical examples show that the proposed relay scheme offers higher capacity than the existing zero-forcing (ZF) relaying scheme

In this paper, the problem of security in multiple input multiple output (MIMO) system has been analysed in the presence of an eavesdropper in cognitive radio networks. Multiple primary and secondary users communicate with the primary and secondary receiver, respectively. The secrecy capacity at primary receiver (PR) and secondary receiver (SR) have been calculated. At first, we use zero-forcing (ZF) precoding at the relay which enhances the secrecy capacity of PR and SR by nullifying the impact of interference. Secondly, we use a scheme to improve the secrecy capacity of the PR and SR using the existing interference energy of the communication medium employing selective precoding (SP) at the relay. Finally, we employ phase alignment precoding (PAP) for further increase in the secrecy capacity for PR and SR by using the destructive part of interference. Our analysis shows that among the three precoding techniques, the best performance is achieved by using the PAP at the relay in terms of secrecy capacity, complementary cumulative distribution function (CCDF) and outage probability analysis.

Massive Multiple Input Multiple Output (MIMO) system is regarded as an emerging technology to enhance the capacity (achievable rate) of wireless communication systems. In this paper, we present an iterative algorithm that adapts transmit signal vector and power of the user using game theory to enhance the physical-layer security (achievable secrecy rate) of massive MIMO system in the presence of eavesdropper and jammers. The proposed algorithm takes account of impact of jammers while meeting the target Signal-to-Interference-plus-Noise Ratio (SINR) and the impact of both eavesdropper and jammers while evaluating the secrecy rate of the users. Furthermore, we present the existence and uniqueness of Nash equilibrium of the game used in this paper. We evaluate the performance of the algorithm using numerical results obtained from simulations. When both eavesdropper and jammers are present close to the users, secrecy rate of legitimate users degrade significantly.

In this paper, capacity performance analysis is presented for multiple-input multiple-output (MIMO) relay channels with transmit antenna selection and maximal-ratio combining receive (TAS/MRC) in amplify-and-forward (AF) relay networks operating over flat Rayleigh fading channels. Assuming that the source and destination are equipped with Ns and Nd antennas, respectively, and communicate with each other with the help of a single-antenna relay, we derive the cumulative distribution function (CDF), probability density function (PDF) and moment generation function (MGF) for the system end-to-end SNR. Based on these, we then present closed-form analytical expressions for the calculation of the ergodic capacity and outage capacity for the AF MIMO relay channels with TAS/MRC. Numerical results show that all the derived analytical expressions are very tight and are valid for evaluations of the ergodic and outage capacity under various antenna configurations. The results also show how the number of transmit antennas and receives antennas affect the overall channel capacity under fading channel environments.

This paper investigates an unmanned aerial vehicle (UAV)-base station (BS) integrated network, where a UAV transmits downlink secrecy data to multiple ground cognitive users while a ground BS utilizes jamming beamforming to help the UAV counter the eavesdropping attack of a ground eavesdropper. In particular, we consider the imperfect eavesdropping and jamming channel state information (CSI) related to the eavesdropper. To maximize the minimum sum secrecy rate of the cognitive users, a robust secure transmission scheme is proposed. The UAV trajectory, UAV transmit power, BS beamforming, and user scheduling are jointly optimized with the constraints of the communication quality of the primary users served by the BS and the UAV available propulsion energy. We formulate a non-convex optimization problem which is challenging to be solved mathematically, and we utilize an alternating optimization technique to divide the original problem into three sub-problems, i.e., UAV trajectory sub-problem, transmit power sub-problem, and user scheduling sub-problem. Besides, they can be solved by the successive convex approximation, semi-definite relaxation and S-procedure, and bivariate relaxation methods, respectively. Moreover, we explore the impact of different parameters of the proposed transmission scheme on the minimum sum secrecy rate of the cognitive users, and verify the superiority of the proposed robust secure transmission scheme design.

We consider a K-user multiple-input multiple-output (MIMO) relay channel, where each user sends independent messages to the other K-1 users via a common relay in two time slots. All users and the relay are equipped with multiple antennas. In contrast to existing work, we consider systems with both multiplexing and diversity, where each user message contains multiple data streams and there are extra degrees of freedom to optimize the transmit beamforming matrices. We propose a novel iterative beamforming optimization algorithm based on orthogonal projection optimization with the signal subspace alignment. An optimal power allocation is also considered to maximize the system sum rate. The sum rate performance of the proposed scheme in various channel configurations is verified by simulations, which shows that the proposed scheme produces significant improvement over existing one.

In this paper, we consider decode-and-forward (DF) relay beamforming for secrecy with cooperative jamming (CJ) in the presence of multiple eavesdroppers. The communication between a source-destination pair is aided by a multiple-input multiple-output (MIMO) relay. The source has one transmit antenna and the destination and eavesdroppers have one receive antenna each. The source and the MIMO relay are constrained with powers P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> and P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> , respectively. We relax the rank-1 constraint on the signal beamforming matrix and transform the secrecy rate max-min optimization problem to a single maximization problem, which is solved by semidefinite programming techniques. We obtain the optimum source power, signal relay weights, and jamming covariance matrix. We show that the solution of the rank-relaxed optimization problem has rank-1. Numerical results show that CJ can improve the secrecy rate.

Deep learning driven physical layer security for a simultaneously wireless information and power transfer network

In multi-hop wireless networks where links are prone to be broken or degraded, it is important to guarantee the network connectivity as well as satisfy the performance requirements. Observing the promising features of Multiple-Input Multiple-Output (MIMO) techniques for improving the transmission capacity and reliability, in this paper, we make the very first attempt to deploy MIMO nodes as relays to assist weak links in wireless networks, with the aim of reducing the number of relay nodes and providing performance provisioning. We identify the specific constraints of MIMO relay nodes for assisting weak links, and take advantage of the MIMO ability to flexibly select among different transmission strategies. The constrains and flexibility, however, make the MIMO deployment problem different from conventional single-antenna deployment schemes and much more challenging. Based on the constraints, we formulate the MIMO relay deployment problem, and provide a polynomial-time approximation scheme (PTAS) algorithm, as well as a distributed heuristic algorithm. The performance of the proposed algorithms is evaluated through simulations and demonstrated to be very effective.

We present an interesting and powerful new framework connecting the achievable sum rate of multiple-input multiple-output (MIMO) wireless systems employing linear minimum mean-squared error (MMSE) receivers, and the ergodic MIMO mutual information. This allows the vast literature on ergodic MIMO mutual information to be directly applied to the analysis of MMSE receivers. As an example, the framework is particularized to spatially-correlated Rayleigh fading to yield new exact closed-form expressions for the achievable sum rate, as well as simplified expressions for high and low signal to noise ratios.

In this paper, we consider a general K-user Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). We assume that the channel state is deterministic and known to all the nodes. While the private-message capacity region is well known to be achievable with dirty paper coding (DPC), we are interested in the simpler linearly precoded transmission schemes. In particular, we focus on linear precoding schemes combined with rate-splitting (RS). First, we derive an achievable rate region with minimum mean square error (MMSE) precoding at the transmitter and joint decoding of the sub-messages at the receivers. Then, we study the achievable sum rate of this scheme and obtain two findings: 1) an analytically tractable upper bound on the sum rate that is shown numerically to be a close approximation, and 2) how to reduce the number of active streams -- crucial to the overall complexity -- while preserving the sum rate to within a constant loss. The latter results in two practical algorithms: a stream elimination algorithm and a stream ordering algorithm. Finally, we investigate the constant-gap optimality of linearly precoded RS with respect to the capacity. Our result reveals that, while the achievable rate of linear precoding alone can be arbitrarily far from the capacity, the introduction of RS can help achieve the capacity region to within a constant gap in the two-user case. Nevertheless, we prove that the RS scheme's constant-gap optimality does not extend to the three-user case. Specifically, we show, through a pathological example, that the gap between the sum rate and the sum capacity can be unbounded.

Energy efficiency is an important design criterion for wireless\ncommunications. When parallel frequency channels are used for multiuser\ntransmission, the channel bandwidths and user power are adjusted to maximize\nthe sum information rate with the bandwidth budget, the transmit power budget,\nand the user-specific rate requirements. The maximum sum rate is used in\nmeasuring the energy efficiency. With fixed or flexible bandwidths of the\nfrequency channels, practical methods are developed to find the total transmit\npower with the unique optimal resource (bandwidth and power) allocation for\nmaximum energy efficiency. This resource allocation ensures that, while each\nuser's minimum rate requirement is satisfied, all the excess resource of the\nspectrum and transmit power is dedicated to the one user with the best channel\nquality. Simulation results validate the optimal solutions of total transmit\npower and resource allocation that support the energy-efficient multiuser\ntransmission.\n

DHT-based GFDM and STC-GFDM systems for beyond 5G wireless networks