Downlink cooperative beamforming for MIMO cellular systems

In downlink cellular multiple users in multiple cells systems using beams, the should cooperate to generate beams to improve the spectrum efficiency. A mathematical model for the multi-cell multi-user downlink transmission is established, and the gradients of the variables including beamfonning filters, receiving filters and transmitting power are calculated. Then, a gradient-project-based cooperative beamforming scheme is proposed in which each user iteratively adjusts bearnforming variables in the direction of the gradients and projects onto feasible spaces. The information exchange protocol needed to support the scheme is also described. Simulation results show that the proposed scheme can achieve an average spectral efficiency of about 5 bit/（ s · Hz · cell）. The results show that cooperative beamforming can improve the spectrum efficiency of the cellular systems.

Cooperative Distributed Beamforming Design for Multi-RIS Aided Cell-Free Systems

Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.

Joint cooperative beamforming and artificial noise design for secure AF relay networks with energy-harvesting eavesdroppers

In this paper, we investigate physical layer security for simultaneous wireless information and power transfer in amplify-and-forward relay networks. We propose a joint robust cooperative beamforming and artificial noise scheme for secure communication and efficient wireless energy transfer. Specifically, by treating the energy receiver as a potential eavesdropper and assuming that only imperfect channel state information can be obtained, we formulate an optimization problem to maximize the worst-case secrecy rate between the source and the legitimate information receiver under both the power constraint at the relays and the wireless power harvest constraint at the energy receiver. Since such a problem is non-convex and hard to tackle, we propose a two-level optimization approach which involves a one-dimensional search and semidefinite relaxation. Simulation results show that the proposed robust scheme achieves better worst-case secrecy rate performance than other schemes.

How to Deploy Intelligent Reflecting Surfaces in Wireless Network:BS-side,User-side, or Both Sides?

The performance of wireless communication systems is fundamentally constrained by the random and uncontrollable wireless channel. By leveraging the recent advances in digitally-controlled metasurface, intelligent reflecting surface (IRS) has emerged as a promising solution to enhance the wireless network performance by smartly reconfiguring the radio propagation environment. Despite the substantial research on IRS-aided communications, this article addresses the important issue of how to deploy IRSs in a wireless network to achieve its optimum performance. We first compare the two conventional strategies of deploying IRS at the side of base station or users in terms of various communication performance metrics,and then propose a new hybrid IRS deployment strategy by combining their complementary advantages. Moreover,the main challenges in optimizing IRS deployment as well as their promising solutions are discussed. Numerical results are also presented to compare the performance of different IRS deployment strategies and draw useful insights for practical design.