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arXiv 2209.09828cs.ITeess.SPmath.IT
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增强网络覆盖的联合基站与IRS部署:一种基于图的建模与优化方法

Joint Base Station and IRS Deployment for Enhancing Network Coverage: A Graph-Based Modeling and Optimization Approach

Weidong Mei, Rui Zhang

AI总结:

本文研究无线网络中基站与智能反射面的联合部署优化问题,基于图论建模并利用分支定界法与顺序更新算法求解,揭示了覆盖性能与部署成本间的权衡。

摘要:

智能反射面(IRS)可密集部署于复杂环境中,通过可调的IRS反射在多个基站(BSs)与用户之间创建级联视距(LoS)路径,从而显著增强无线网络的覆盖性能。为实现该目标,优化无线网络中BS与IRS的部署位置至关重要,本文对此进行了研究。具体而言,我们将网络覆盖区域划分为多个不重叠的单元,并在给定可用BS/IRS总数的情况下,决定是否在每个单元中部署BS/IRS。我们表明,为确保网络覆盖/通信性能,即每个单元与至少一个BS有直接/级联LoS路径,且此类LoS路径的平均IRS反射次数小于给定阈值,在部署成本或所需BS/IRS数量之间存在一种基本权衡。为最优地刻画此权衡,我们基于图论构建了联合BS与IRS部署问题,但由于涉及组合优化,该问题难以被最优求解。为克服此困难,我们首先考虑给定BS部署的简化问题,并分别通过应用分支定界法和从候选位置迭代移除IRS,为其提出最优及高效的次优IRS部署方案。接着,提出了一种高效的顺序更新算法来求解联合BS与IRS部署问题。提供的数值结果表明了所提设计方法和优化算法在联合BS与IRS部署上的有效性。同时,也揭示了在不同成本比例下网络覆盖性能与部署BS/IRS数量之间的权衡。

英文摘要:

Intelligent reflecting surface (IRS) can be densely deployed in complex environment to create cascaded line-of-sight (LoS) paths between multiple base stations (BSs) and users via tunable IRS reflections, thereby significantly enhancing the coverage performance of wireless networks. To achieve this goal, it is vital to optimize the deployed locations of BSs and IRSs in the wireless network, which is investigated in this paper. Specifically, we divide the coverage area of the network into multiple non-overlapping cells and decide whether to deploy a BS/IRS in each cell given a total number of BSs/IRSs available. We show that to ensure the network coverage/communication performance, i.e., each cell has a direct/cascaded LoS path with at least one BS, as well as such LoS paths have the average number of IRS reflections less than a given threshold, there is a fundamental trade-off with the deployment cost or the number of BSs/IRSs needed. To optimally characterize this trade-off, we formulate a joint BS and IRS deployment problem based on graph theory, which, however, is difficult to be optimally solved due to the combinatorial optimization involved. To circumvent this difficulty, we first consider a simplified problem with given BS deployment and propose the optimal as well as an efficient suboptimal IRS deployment solution to it, by applying the branch-and-bound method and iteratively removing IRSs from the candidate locations, respectively. Next, an efficient sequential update algorithm is proposed for solving the joint BS and IRS deployment problem. Numerical results are provided to show the efficacy of the proposed design approach and optimization algorithms for the joint BS and IRS deployment. The trade-off between the network coverage performance and the number of deployed BSs/IRSs with different cost ratios is also unveiled.

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