The time-reversal division multiple access (TRDMA) system employs multipath channels to realize multi-user transmission via time-reversal filtering. The performance of TRDMA is affected by the correlation among users’ channels. When the correlation is high, inter-user interference (IUI) in the TRDMA system will be serious and the system capacity will be severely restricted. In this paper, we propose an uplink multiple access scheme time-reversal non-orthogonal multiple access (TR-NOMA), wherein TRDMA and power-domain non-orthogonal multiple access are combined. The base station employs a TR filter for each user to suppress IUI and applies successive interference cancellations in the detection process of users’ signals. Users’ transmit power and TR filters are jointly optimized to promote system capacity. The original optimization problem is non-convex. We decompose the optimization problem into two sub-problems: the design of TR filters and the allocation of users’ transmit power, which is solved by utilizing generalized eigenvalue decomposition and successive lower bound convex approximation, respectively. The solution to the original optimization problem is obtained by the iterative solution between the two sub-problems. Simulation results demonstrate that the sum rate of the optimized TR-NOMA system is significantly higher than that of the TRDMA system.

Millimeter-wave (mmWave) communication has attracted considerable attention from academia and industry, providing multi-gigabits per second rates due to the substantial bandwidth. Rate splitting multiple access (RSMA) is an effective technology that provides a generalized multiple access framework. Regarding the new propagation characteristics of the mmWave, we investigate the outage performance of the mmWave RSMA multiple-input-single-output system with a fixed-located user and a randomly-located user. Based on the spatial correlation of the paired users, the user’s paths are divided into overlapped and non-overlapped paths. Two beamforming schemes are proposed to improve the reliability of the mmWave RSMA system. The common stream is transmitted on the overlapped paths or all the paths. By utilizing stochastic geometry theory, the closed-form expressions of the outage probability (OP) with proposed schemes are derived. To obtain more insights, the expressions for the asymptotic OP are derived. Monte Carlo simulation results are presented to validate the analysis and the effects of the system parameters, such as power allocation coefficients and the number of resolvable paths, on the outage performance are investigated.

Abstract Ultra‐reliable low‐latency communication (URLLC) has the most stringent end‐to‐end communication performance requirements among the three major 5G scenarios. The URLLC enhancement research on 5G‐advanced and 6G needs to be explored continuously. First, through the analysis of the mmWave downlink channel model with finite block length, the CRC detection error feedback mechanism is introduced, and a variable code rate CRC‐AFC cascaded coding scheme is designed. The re‐encoding process of the proposed scheme can effectively improve the system reliability in a wide SNR range. Then, a URLLC dynamic spectrum optimisation algorithm based on CRC‐AFC cascade coding is proposed by analysing the relationship between the latency constraint range of URLLC data, the SNR, and the coding error rate. While ensuring the quality of non‐URLLC communication, the proposed algorithm can dynamically allocate unlicensed spectrum based on the code rate and URLLC traffic, so as to improve reliability within a wide SNR range and improve latency performance under a large number of URLLC users.

In this paper, we investigate the optimal transmit antenna placement for short-range indoor line-of-sight (LOS) 2 × 2 multiple-input multiple-output (MIMO) channels in three-dimensional (3D) space. The corresponding channel with arbitrary antenna orientations in 3D space is first established by using the spherical-wave model (SWM). On this basis, we propose a scheme of the transmit antenna placement optimization based on the ant colony algorithm (ACA) with the mobile station (MS) moving in a certain area. Simulation results demonstrate that the proposed scheme effectively improves the average channel capacity in a region.