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Optimal Link Scheduling in Millimeter Wave Multi-hop Networks with MU-MIMO radios.
IEEE Transactions on Wireless Communications ( IF 8.9 ) Pub Date : 2020-03-01 , DOI: 10.1109/twc.2019.2959295
Felipe Gomez-Cuba , Michele Zorzi

This paper studies the maximum throughput achievable with optimal scheduling in multi-hop mmWave picocellular networks with Multi-user Multiple-Input Multiple-Output (MU-MIMO) radios. MU-MIMO enables simultaneous transmission to multiple receivers (Space Division Multiplexing) and simultaneous reception from multiple transmitters (Space Division Multiple Access). The main contribution is the extension to MU-MIMO of the Network Utility Maximization (NUM) scheduling framework for multi-hop networks. We generalize to MU-MIMO the classic proof that Maximum Back Pressure (MBP) scheduling is NUM optimal. MBP requires the solution of an optimization that becomes harder with MU-MIMO radios. In prior models with one-to-one transmission and reception, each valid schedule was a matching over a graph. However, with MU-MIMO each valid schedule is, instead, a Directed Bipartite SubGraph (DBSG). In the general case this prevents finding efficient algorithms to solve the scheduler. We make MU-MIMO MBP scheduling tractable by assuming fixed power allocation, so the optimal scheduler is the Maximum Weighted DBSG. The MWDBSG problem can be solved using standard Mixed Integer Linear Programing. We simulate multi-hop mmWave picocellular networks and show that a MU-MIMO MBP scheduler enables a 160% increase in network throughput versus the classic one-to-one MBP scheduler, while fair rate allocation mechanisms are used in both cases.

中文翻译:

具有 MU-MIMO 无线电的毫米波多跳网络中的最佳链路调度。

本文研究了在具有多用户多输入多输出 (MU-MIMO) 无线电的多跳毫米波微微蜂窝网络中通过最佳调度可实现的最大吞吐量。MU-MIMO 支持同时传输到多个接收器(空分复用)和同时从多个发射器接收(空分多址)。主要贡献是对多跳网络的网络效用最大化 (NUM) 调度框架的 MU-MIMO 的扩展。我们将最大背压 (MBP) 调度是 NUM 最优的经典证明推广到 MU-MIMO。MBP 需要优化的解决方案,这对于 MU-MIMO 无线电变得更加困难。在具有一对一传输和接收的先前模型中,每个有效时间表都是图上的匹配。然而,对于 MU-MIMO,每个有效的调度是,有向二部子图 (DBSG)。在一般情况下,这会阻止找到解决调度程序的有效算法。我们通过假设固定功率分配使 MU-MIMO MBP 调度易于处理,因此最佳调度器是最大加权 DBSG。MWDBSG 问题可以使用标准混合整数线性规划解决。我们模拟了多跳毫米波微微蜂窝网络,并表明与经典的一对一 MBP 调度器相比,MU-MIMO MBP 调度器使网络吞吐量提高了 160%,同时在这两种情况下都使用了公平的速率分配机制。MWDBSG 问题可以使用标准混合整数线性规划解决。我们模拟了多跳毫米波微微蜂窝网络,并表明与经典的一对一 MBP 调度器相比,MU-MIMO MBP 调度器使网络吞吐量提高了 160%,同时在这两种情况下都使用了公平的速率分配机制。MWDBSG 问题可以使用标准混合整数线性规划解决。我们模拟了多跳毫米波微微蜂窝网络,并表明与经典的一对一 MBP 调度器相比,MU-MIMO MBP 调度器使网络吞吐量提高了 160%,同时在这两种情况下都使用了公平的速率分配机制。
更新日期:2020-03-01
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