基于STARS 的安全认知无线电联合波束赋形优化算法

doi:10.11959/j.issn.2096-3750.2023.00347

摘要/Abstract

摘要： 基于可重构智能表面(RIS)的安全认知无线电(SCR)系统均假设次用户(SU)和主用户(PU)在基站(BS)的同一侧，仅能够实现通信区域的部分覆盖，限制了 RIS 部署的灵活性和有效性。为了解决上述问题，该文提出了一种新的基于同时透射和反射智能表面(STARS)的 SCR 系统。在该系统中，STARS 能够实现通信区域的全覆盖，利用透射波束赋形向量提高 SU 的接收信号强度，同时利用反射波束赋形向量降低 SU 对 PU 的干扰，为 SCR系统的设计提供了新的优化自由度(DoFs)。考虑 SU 保密率约束、PU 干扰功率约束(IPC)和 STARS 透射/反射参数约束，从降低系统总功耗角度出发，以最小化 BS 发射功率为目标，构建 BS 主动波束赋形向量和 STARS 透射/反射波束赋形向量联合优化问题。这一最小化问题是变量耦合非凸问题，很难直接求解。该文提出基于凸差松弛(DCR)方法和顺序秩一约束松弛(SROCR)方法的交替优化(AO)算法，联合设计 BS 主动波束赋形向量和 STARS透射/反射波束赋形向量。仿真结果表明，所提的算法具有良好的收敛性能，能够有效降低 SU 对 PU 的干扰，且与传统 RIS、随机相位、最大比传输(MRT)和等能量分裂(Equal ES)方案相比，BS 发射功率分别降低了 8.3%，15.4%，5.9%和 5.3%。

关键词: 可重构智能表面, 认知无线电, 波束赋形, 同时透射和反射

Abstract: Secure Cognitive Radio (SCR) system based on Reconfigurable Intelligent Surface (RIS) assumes that Secondary User (SU) and Primary User (PU) locate on the same side of the Base Station (BS), which can only cover part of the communication area and limits the deployment flexibility and effectiveness of the RIS. In order to solve the above problem, a new SCR system based on Simultaneously Transmitting And Reflecting Intelligent Surface (STARS) was proposed in this paper. In the system, STARS can achieve full coverage of communication area, improved the received signal strength of the SU with the transmission beamforming vector and reduced the interference of the SU to the PU with the reflection beamforming vector, which provided new optimization Degree of Freedoms (DoFs) for the design of the SCR system. Under conditions of the secrecy rate constraint of the SU, Interference Power Constraint (IPC) of the PU and transmission/reflection parameters constraint of the STARS, BS active beamforming vector and STARS transmission/reflection beamforming vectors were jointly optimized to minimize the BS’s transmit power from the perspective of reducing the total power consumption of the system. The minimization problem was a variable coupling non-convex problem, which was difficult to tackle directly. Then, an Alternating Optimization (AO) algorithm based on Difference-of-Convex Relaxation (DCR) method and Sequential Rank-One Constraint Relaxation (SROCR) method was proposed to jointly design the BS active beamforming vector and STARS transmission/reflection beamforming vectors. Simulation results show that the proposed algorithm has good convergence performance and effectively reduces the interference of SU on PU. Compared with the traditional RIS, random phase, Maximum-Ratio Transmission (MRT) and Equal Energy Splitting (Equal ES) schemes, the BS transmitting power is reduced by 8.3%, 15.4%, 5.9% and 5.3%, respectively.

温陈驰, 左加阔, 鲍楠, 赵鹏飞. 基于STARS 的安全认知无线电联合波束赋形优化算法[J]. 物联网学报, doi: 10.11959/j.issn.2096-3750.2023.00347.

WEN Chenchi, ZUO Jiakuo, BAO Nan, ZHAO Pengfei. Joint beamforming optimization for secure cognitive radio based on STARS[J]. Chinese Journal on Internet of Things, doi: 10.11959/j.issn.2096-3750.2023.00347.

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