This letter investigates the outage performance for simultaneous wireless information and power transfer (SWIPT) relaying systems in the presence of direct link between the source and the destination. For the SWIPT, we employ a power splitter (PS) at the relay, which splits the received signal into the information transmission and the energy harvesting parts. First, we provide an analysis of the outage probability as a closed-form based on a high signal-to-noise ratio approximation. From the analysis, it is recognized that the diversity order of the SWIPT relaying systems equals that of the non-SWIPT cases. The closed-form outage expression also enables us to obtain a simple expression for the PS factor which minimizes the outage probability. Simulation results demonstrate the accuracy of the derived analysis and the efficiency of the proposed PS scheme.

In this paper, we consider a proactive eavesdropping scenario, where a central monitor tries to intercept the information exchanged between a pair of suspicious entities through amplify-and-forward full-duplex relays and a cooperative jammer. Specifically, the eavesdropping relays simultaneously listen to the suspicious transmitter and forward the eavesdropped information to the central monitor. At the same time, the jammer broadcasts jamming signals to maintain the data rate of the suspicious users below the channel capacity of the central monitor so that the eavesdropped information can be successfully decoded by the central monitor. In this system, we jointly design the receive combining vector at the central monitor, the relay precoders at the eavesdropping relays and the transmit covariance matrix at the jammer to maximize the eavesdropping rate. First, we examine the case of a single eavesdropping relay equipped with a single antenna and provide some useful insights. Also, an effective two-layer optimization method is proposed to obtain the globally optimal solution. Then, we study a general case of multiple eavesdropping relays with multiple antennas, and solve a semi-definite relaxation problem. Numerical results verify the efficiency of our proposed solutions for both single and multiple relay cases and show considerable performance gains over conventional schemes.

In this paper, we consider a legitimate proactive eavesdropping scenario where a distant central monitor covertly wiretaps the communication between a pair of suspicious users via several multi-antenna full-duplex spoofing relays and a multi-antenna cooperative jammer. Assuming an adaptive transmission policy at the suspicious users, the spoofing relays not only intercept but also forward the manipulated information to control the data rate of the suspicious users in collaboration with the jammer. We provide a technique which jointly optimizes the receive combining vector at the central monitor, the precoders at the relays, and the transmit covariance matrix at the jammer for maximizing the eavesdropping rate. To reveal some fundamental properties of the optimal operation, we first study a single-relay system. It is shown that when the central monitor experiences a poor eavesdropping channel link, the spoofing relay and the jammer should transmit destructive signals and jamming signals, respectively. In this case, the suspicious users are forced to decrease their data rate, while the intercepted information can be successfully decoded by the central monitor. On the other hand, when the eavesdropping channel condition is favorable, the spoofing relay forwards constructive signals to further increase the data rate at the suspicious users in a way that more information can be intercepted from the suspicious users. We then formulate a general eavesdropping rate maximization problem for multiple relays and present a semi-definite relaxation approach. A low-complexity design is also proposed based on our analysis for the single-relay system. Simulation results verify the efficiency of the proposed solutions compared to other baseline schemes in various practical setups.

In this paper, we study a joint spatial division multiplexing (JSDM) beamforming scheme, which enables large-scale spatial multiplexing gains for massive multi-input multi-output downlink systems. In contrast to the conventional JSDM, which employs a block diagonalization method as a pre-beamformer, we aim to maximize sum-rate by applying minimum-mean-squared error (MMSE) approaches when designing a pre-beamformer and a multi-user precoder sequentially. First, to suppress inter-group interference, we design the pre-beamformer, which minimizes an upper bound of the sum mean-squared-error in the large-scale array regime. Then, to mitigate same-group interference, we present the multi-user precoder based on the weighted MMSE (WMMSE) optimization method, which requires the same channel state information overhead as the conventional JSDM. Also, in order to reduce the computational complexity, we compute deterministic equivalents of the WMMSE beamforming parameters to generate the beamformers by employing asymptotic results of large system analysis. Through simulation results, we confirm that the proposed two-step beamforming methods bring substantial performance gains in terms of sum-rate over the conventional JSDM schemes especially in a low and medium signal-to-noise ratio regime with comparable complexity.

In this paper, we study multi-user multi-input multi-output cognitive wireless powered communication networks (WPCN), in which a secondary WPCN shares spectrum with a primary wireless information transfer system. A typical WPCN consists of two different phases. In the first downlink phase, a hybrid access point (H-AP) transfers energy to charge users, and then in the subsequent uplink phase, the users send information by using the harvested energy to the H-AP. We consider two different cognitive WPCN protocols depending on the cooperation level between the primary transmitter and the secondary H-AP. For both cases, we formulate sum throughput maximization problems by taking the interference leakage to the primary network into consideration. The problems are generally non-convex due to coupled variables in the WPCN. To tackle this issue, we first convert the problems into equivalent convex forms, and then identify the global optimal solutions by applying the proposed iterative optimization algorithms. Finally, the simulation results demonstrate that the proposed algorithms outperform conventional schemes.

For a self-sustaining wireless communication system in Internet-of-Things (IoT) networks, energy harvesting (EH) can be implemented at each user node as a constant renewable power supply source. Hence, an investigation into the use of wireless powered communication network (WPCN) protocols to facilitate communication between an access point (AP) and multiple mobile users (MUs) is presented in this paper. The AP has multiple antennas and operates in the full-duplex (FD) mode. The MUs, on the other hand, have single antennas and works in the half-duplex (HD) mode. Each MU communicating with the FD-AP is assigned to one of two groups, based on the time allocation and channel access for either uplink (UL) or downlink (DL) communication. The channel assignment, time resource, and power resource allocations are optimized to maximize the UL weighted sum-rate. The sum-rate optimization problem is found to be non-convex. Therefore, an iterative algorithm is investigated to optimize the UL weighted sum-rate of the propose FD-WPCN system. Next, the proposed FD-WPCN algorithm is modified for a HD-WPCN enabled communication between the AP and multiple MUs. Extensive simulations are conducted to verify the proposed algorithm for FD-WPCN and compare its performance with the HD-WPCN counterpart. From the simulation results, FD-WPCN outperformed HD-WPCN at a low AP transmit signal-to-noise ratio (SNR) region. The opposite behavior is observed for high AP transmit SNR due to increasing residual self-interference at the FD-AP.