We consider a signal detection problem by using deep learning techniques in a multiple-input multiple-output (MIMO) decode-forward (DF) relay channel. There exist some suboptimal detectors such as the near maximum likelihood (NML) detector and the NML with two-level pair-wise error probability (NMLw2PEP) detector in the channel. However, the NML detectors require an exponentially increasing complexity as the number of transmit antennas increases. More seriously, without the channel state information (CSI) of the source-relay (SR) link, there is no detector that can achieve good performance even at high complexity. In this paper, we propose a deep learning approach to the NML (DL-NML) detector that achieves good performance with low complexity regardless of whether the CSI of the SR link is known or not at the destination. The DL-NML detector can detect signals in changing channels after a single training by using randomly generated channels. Furthermore, we propose a linear detector and a semidefinite relaxation approach to the NML detector to compare with the DL-NML detector in performance and complexity. The complexity analysis and simulation results validate the superiority of the proposed DL-NML detector.

This work studies the role of inter-user device-to-device (D2D) cooperation for improving physical-layer secret communication in multi-user downlink systems. It is assumed that there are out-of-band D2D channels, on each of which a selected legitimate user transmits an amplified version of the received downlink signal to other legitimate users. A key technical challenge for designing such systems is that eavesdroppers can overhear downlink as well as D2D cooperation signals. We tackle the problem of jointly optimizing the downlink precoding, artificial noise covariance, and amplification coefficients that maximize the minimum rate. An iterative alternating optimization algorithm is proposed based on the matrix fractional programming. Numerical results confirm the performance gains of the proposed D2D cooperation scheme compared to benchmark secret communication schemes.

In this paper, a decode-forward relay system with a source, a relay, and a destination is considered. A new switching superposition-coded (NSSC) relay scheme is proposed to improve error performance by increasing the equivalent squared minimum distance. On the receiver side, a low-complexity linear-combining successive-interference-cancellation decoder is proposed for the NSSC scheme. The theoretical and simulation results show that the NSSC scheme achieves better performance compared to the existing superposition-coded relay schemes.

This work considers quantize–forward (QF) relay channels with $M$ -ary phase shift keying at the source and $q$ -bit uniform phase quantization at the relay. A cooperative linear combining (CLC) detection which linearly combines the received signals at the destination is proposed in the QF relay channel by deriving an equivalent signal-to-noise ratio for the source-relay-destination link. Furthermore, the proposed detection is simplified by approximating $Q$ function in two directions: small $q$ and large $q$ . The CLC detection and its simplified version are also extended to multi-relay channels. Simulation results verify that the CLC and simplified CLC detections achieve reasonable performance with less complexity than the maximum-likelihood detection. It demonstrates that applying $(\log _{2} M+2)$ -bit uniform phase quantization at the relay and the simplified CLC detection at the destination can be an appropriate choice in terms of performance, complexity, and memory.

This paper considers an amplify–quantize–forward (AQF) relay channel with $M$ -ary quadrature amplitude modulation, where the relay implements a uniform quantization for the amplified received signal and forwards it to the destination. Two step-size determinant methods for the uniform quantization at the relay are proposed by deriving the power and the mean square error for the quantized signal. Given the step size, the maximum-likelihood detection is presented, and a linear combining detection called equivalent maximum ratio combining is proposed to reduce the detection complexity at the destination in the AQF relay channel. The simulation results confirm the superiority of the proposed quantization methods and detection algorithms.