Resource allocation algorithm for cognitive radio systems based on STAR-RIS with coupled phase shifts

LI Guoquan; XIONG Hao; XIE Zonglin; LIN Jinzhao

doi:10.11959/j.issn.1000-436x.2024263

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Resource allocation algorithm for cognitive radio systems based on STAR-RIS with coupled phase shifts

Papers | 更新时间：2024-12-24

- Resource allocation algorithm for cognitive radio systems based on STAR-RIS with coupled phase shifts
- Journal on Communications Vol. 45, Issue 11, Pages: 131-140(2024)
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，重庆 400065
  2.光电信息感测与微系统重庆市重点实验室，重庆 400065
- 作者简介：
- 基金信息：
  
  The Natural Science Foundation of Chongqing(cstc2020jcyj-cxttX0002;CSTB2023NSCQ-LZX0105)
- DOI：10.11959/j.issn.1000-436x.2024263
  CLC： TN92
- Received：10 July 2024，
  
  Revised：2024-10-29，
  
  Published：25 November 2024
- 稿件说明：
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李国权,熊豪,谢宗霖等.基于耦合相移STAR-RIS的认知无线电系统资源分配算法[J].通信学报,2024,45(11):131-140.

LI Guoquan,XIONG Hao,XIE Zonglin,et al.Resource allocation algorithm for cognitive radio systems based on STAR-RIS with coupled phase shifts[J].Journal on Communications,2024,45(11):131-140.
李国权,熊豪,谢宗霖等.基于耦合相移STAR-RIS的认知无线电系统资源分配算法[J].通信学报,2024,45(11):131-140. DOI： 10.11959/j.issn.1000-436x.2024263.

LI Guoquan,XIONG Hao,XIE Zonglin,et al.Resource allocation algorithm for cognitive radio systems based on STAR-RIS with coupled phase shifts[J].Journal on Communications,2024,45(11):131-140. DOI： 10.11959/j.issn.1000-436x.2024263.

摘要

针对频谱资源紧缺和通信质量受限等问题，建立了一种相移耦合的同时透射与反射可重构智能表面（STAR-RIS）辅助的多输入单输出（MISO）认知无线电系统并提出了一种认知基站发射功率最小化的资源分配算法。首先在满足次用户服务质量（QoS）以及主用户干扰约束的情况下，构建了认知基站波束成形向量和STAR-RIS系数联合优化问题来实现认知基站发射功率的最小化；然后通过块坐标下降（BCD）法将其转化为主动波束成形向量和STAR-RIS系数2个子问题进行变量解耦，并基于惩罚对偶分解（PDD）框架分别利用半正定松弛（SDR）和连续凸近似（SCA）算法交替优化求解。仿真结果表明，所提算法收敛性好，建立的系统方案可使认知基站具有更低的功率消耗。

Abstract

To address the issues of spectrum resource scarcity and limited communication quality

a scheme for a coupled phase-shift-based simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted multi-ple-input single-output (MISO) cognitive radio system was proposed. Additionally

a resource allocation algorithm aimed at minimizing the transmission power of the cognitive base station was introduced. First

under the constraints of the quality of service (QoS) for secondary users and interference limitation to primary users

a joint optimization problem was formulated to minimize the transmission power of the cognitive base station by jointly optimizing the beamforming vectors of the cognitive base station and the coefficients of the STAR-RIS. Then

it was transformed into two sub-optimization problems of active beamforming vectors and STAR RIS coefficients by the block coordinate descent (BCD) method to decoupling variables. Subsequently

based on the penalty dual decomposition (PDD) framework

the semidefinite relaxation (SDR) and the successive convex approximation (SCA) algorithms were used to optimize them alternately and seek the final solution. Simulation results show that the proposed algorithm converges well

and the proposed system scheme can achieve lower power consumption at the cognitive base station.

关键词

Keywords

references

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