The simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that optimal energy splitting coefficients of STAR-RISs exist to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located on different sides; 2) STAR-RISs with appropriate energy splitting coefficients outperform conventional RISs in the coverage and the rate performance.

Performance analysis is carried out in a near-field multiple-input multiple-output (MIMO) system for both discrete and continuous aperture antennas. The effective degrees of freedom (EDoF) is first derived. It is shown that near-field MIMO systems have a higher EDoF than free-space far-field ones. Additionally, the near-field EDoF further depends on the communication distance. Based on the derived EDoF, closed-form expressions of channel capacity with a fixed distance are obtained. As a further advance, with randomly deployed receivers, ergodic capacity is derived. Simulation results reveal that near-field MIMO has an enhanced multiplexing gain even under line-of-sight transmissions. In addition, the performance of discrete MIMO converges to that of continuous aperture MIMO.

In modern transportation systems, the road intersections where multiple roads merge usually become the traffic bottleneck. Existing coordination solutions such as the traffic signs tend to be ineffective. In order to exploit the full potential of the road infrastructure, we try to address the optimal vehicle coordination problem, by which the traffic throughput can be maximized. We first formulate it as a general centralized collision-free traffic scheduling framework. The involved vehicles could cooperate via instructions from the coordination center, by solving the essential non-convex coordination problem. Aiming at the dynamic arrival of vehicles, a corresponding coordination strategy is thus proposed to achieve better quality of service (QoS), including the traffic throughput and delay. The queue stability on each road can be guaranteed using the Rate Stability Theorem and Lyapunov Theorem. We then try to extend the proposed intelligent coordination framework to the multi-collision-set one, by which the traffic throughput can be significantly improved. A spatial domain based solution is given to solve the multi-collision-set coordination problem. Due to the essential non-convex formulation, high accuracy linearization approximate algorithms are also provided. In the numerical results, we show the vehicle maneuvers and statistical coordination time as the performance evaluation. They validate our analysis and show the performance advantages achieved by the proposed framework.

This letter proposes an analytical framework for multi-reconfigurable intelligent surface (RIS) aided networks with limited backhaul capacity, where a simple symmetric structure is considered to explore the characteristics of multi-RIS systems with coherent transmissions. By using the Gamma distribution to model the composite RIS-aided channels, closed-form expressions in terms of the outage probability and the ergodic rate are derived. The theoretical results provide two design guidelines: 1) the minimum outage can be achieved by deploying the assisted RISs at certain locations; 2) the rate performance is bounded, and an optimal number of assisted RISs exists for rate maximization. Simulations verify our analysis and demonstrate the backhaul capacity is the bottleneck for multi-RIS systems. Compared with single-RIS systems, multi-RIS systems require a minimal backhaul capacity to ensure the performance gain.

In this paper, a stochastic geometry based analytical framework is proposed for secure simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) transmissions, where legitimate users (LUs) and eavesdroppers are randomly distributed. Both the time-switching protocol (TS) and energy splitting (ES) protocol are considered for the STAR-RIS. To characterize system performance, the channel statistics are first provided, and the Gamma approximation is adopted for general cascaded κ-μ fading. Afterward, the closed-form expressions for both the secrecy outage probability (SOP) and average secrecy capacity (ASC) are derived. To obtain further insights, the asymptotic performance for the secrecy diversity order and the secrecy slope are deduced. The theoretical results show that 1) the secrecy diversity orders of the strong LU and the weak LU depend on the path loss exponent and the distribution of the received signal-to-noise ratio, respectively; 2) the secrecy slope of the ES protocol achieves the value of one, higher than the slope of the TS protocol which is the mode operation parameter of TS. The numerical results demonstrate that: 1) there is an optimal STAR-RIS mode operation parameter to maximize the secrecy performance; 2) the STAR-RIS-NOMA significantly outperforms the STAR-RIS-orthogonal multiple access.

As a conventional metric, spectrum efficiency has been investigated widely in communication systems due to the limited bandwidth resources and increasing subscriber density. Beamforming technology is used in TD-LTE-A and 5G downlink to improve the spectrum efficiency and system capacity, and a proper resource allocation algorithm can also be used to improve the spectrum efficiency on the premise of satisfying user equipment (UE) requirements. In recent years, the energy efficiency has attracted more and more attention since the power consumption on the communication systems increases rapidly, which lays a heavy burden on the environment. In this paper, we propose a joint resource allocation and power allocation algorithm in multi-user beamforming mode, which aims at maximizing the energy efficiency, and also takes UE requirements and spectrum efficiency into consideration. The proposed algorithm firstly calculates the user priorities and gives a UE grouping method to allocate resource blocks (RBs) to different UEs under the assumption that the power is equally allocated among UEs on the same RB. After that, on each RB, it calculates the power allocation among different UEs to realize the improvement of energy efficiency. In addition, the satisfaction of UE requirements is added in the algorithm as a constraint. Simulation results demonstrate that the proposed algorithm shows an excellent performance on system capacity, i.e. spectrum efficiency, and also provides higher energy efficiency than existing algorithms. Moreover, the UE requirements can be better satisfied and system fairness can also be improved.