Optimizing Coverage with Intelligent Surfaces for Indoor mmWave Networks
Optimizing Coverage with Intelligent Surfaces for Indoor mmWave Networks
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DOI：
10.1109/infocom48880.2022.9796762
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Jingyuan Zhang;D. Blough
中科院分区：
文献类型：
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作者：
Jingyuan Zhang;D. Blough
可重构智能表面（RISs）已经被提出来通过在视线（LoS）路径被阻挡时提供从发射器到接收器的间接路径来增加毫米波网络中的覆盖。在本文中，多个RISs的位置和方向的优化问题被认为是第一次。针对存在障碍物的室内场景，提出了一种基于梯度下降的迭代覆盖扩展算法。该算法的目标是最大化阴影区域内的覆盖，其中没有到接入点的LoS路径。该算法保证收敛到局部覆盖最大值，并结合智能初始化过程，以提高该方法的性能和效率。数值结果表明，在密集的障碍物环境中，所提出的算法相比，没有RIS的解决方案的覆盖率增加了一倍，并提供了约10%的覆盖率增加相比，蛮力顺序RIS布局方法。
Reconfigurable intelligent surfaces (RISs) have been proposed to increase coverage in millimeter-wave networks by providing an indirect path from transmitter to receiver when the line-of-sight (LoS) path is blocked. In this paper, the problem of optimizing the locations and orientations of multiple RISs is considered for the first time. An iterative coverage expansion algorithm based on gradient descent is proposed for indoor scenarios where obstacles are present. The goal of this algorithm is to maximize coverage within the shadowed regions where there is no LoS path to the access point. The algorithm is guaranteed to converge to a local coverage maximum and is combined with an intelligent initialization procedure to improve the performance and efficiency of the approach. Numerical results demonstrate that, in dense obstacle environments, the proposed algorithm doubles coverage compared to a solution without RISs and provides about a 10% coverage increase compared to a brute force sequential RIS placement approach.