IRS-assisted D2D system resource allocation and RCG beamforming optimization in H-CRAN

XU Xiaorong; XUE Jishou; WU Jun; BAO Jianrong

doi:10.11959/j.issn.1000-0801.2024191

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IRS-assisted D2D system resource allocation and RCG beamforming optimization in H-CRAN

Topic：Reconfigurable Intelligent Surface for 6G Network | 更新时间：2024-08-14

- IRS-assisted D2D system resource allocation and RCG beamforming optimization in H-CRAN
- Telecommunications Science Vol. 40, Issue 7, Pages: 76-87(2024)
- 作者机构：
  
  杭州电子科技大学通信工程学院，浙江杭州 310018
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62201186);The Natural Science Foundation of Zhejiang Province of China(LZ24F010005;LQ22F010013)
- DOI：10.11959/j.issn.1000-0801.2024191
  CLC： TN929
- Received：31 May 2024，
  
  Revised：2024-07-15，
  
  Published：20 July 2024
- 稿件说明：
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许晓荣,薛纪守,吴俊等.H-CRAN中IRS辅助的D2D系统资源分配与RCG波束成形优化[J].电信科学,2024,40(07):76-87.

XU Xiaorong,XUE Jishou,WU Jun,et al.IRS-assisted D2D system resource allocation and RCG beamforming optimization in H-CRAN[J].Telecommunications Science,2024,40(07):76-87.
许晓荣,薛纪守,吴俊等.H-CRAN中IRS辅助的D2D系统资源分配与RCG波束成形优化[J].电信科学,2024,40(07):76-87. DOI： 10.11959/j.issn.1000-0801.2024191.

XU Xiaorong,XUE Jishou,WU Jun,et al.IRS-assisted D2D system resource allocation and RCG beamforming optimization in H-CRAN[J].Telecommunications Science,2024,40(07):76-87. DOI： 10.11959/j.issn.1000-0801.2024191.

摘要

以异构云无线电接入网（heterogeneous cloud radio access network，H-CRAN）中智能反射面（intelligent reflecting surface，IRS）辅助的端到端（device-to-device，D2D）通信系统为背景，研究了该系统中以和速率最大化为目标的资源分配与黎曼共轭梯度（Riemannian conjugate gradient，RCG）波束成形优化方法。以最大化系统和速率为优化目标，构造子信道复用系数、发射功率门限以及IRS反射系数模约束等多约束优化问题。对于该非线性混合整数规划问题，提出了一种基于相对信道强度的延迟接受算法，以获得信道复用系数。随后将目标优化问题分解为两个子问题进行交替优化。对于发射功率优化子问题，使用逐次凸逼近（successive convex approximation，SCA）方法进行求解。对于IRS波束成形子问题，将IRS相移约束转化为复圆流形后，采用RCG算法进行求解。仿真结果表明，当IRS反射阵源数为50、基站最大发射功率为46 dBm时，与现有信道分配方案和随机信道分配方案相比，所提信道分配方案的和速率性能分别提高了5.2 bit/(s·Hz)和14.6 bit/(s·Hz)。与无IRS通信场景相比，部署IRS的和速率性能显著提高约31.2 bit/(s·Hz)。

Abstract

Intelligent reflecting surface (IRS)-assisted device-to-device (D2D) communications in heterogeneous cloud radio access network (H-CRAN) were investigated as research background. Resource allocation and Riemannian conjugate gradient (RCG) beamforming optimization were studied

with the objective of system sum rate maximization. System sum rate was formulated as the optimization objective

which was subject to several constraint conditions such as sub-channel reuse coefficient

transmit power threshold

as well as the modulus of the IRS reflection coefficient. To solve the formulated mixed-integer non-linear programming problem

a channel-strength-based deferred acceptance algorithm was proposed to obtain channel reuse indicators. The problem was then decomposed into two subproblems. For transmit power optimization subproblem

successive convex approximation (SCA) was used to solve it. For IRS beamforming optimization subproblem

the beamforming vector constraint was transformed into a complex circular manifold and Riemannian conjugate gradient (RCG) algorithm was implemented to solve it. Simulation results show that

when IRS reflecting elements is 50 and base station maximum transmit power is 46 dBm

compared with the existing channel allocation scheme and random channel allocation scheme

the proposed scheme enhances sum rate performance 5.2 bit/(s·Hz) and 14.6 bit/(s·Hz) respectively. Compared with the communication scenario without IRS

sum rate performance significantly promotes nearly 31.2 bit/(s·Hz) with the deployment of IRS.

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references

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