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How to upgrade wireless networks: Small cells or massive MIMO?

机译:如何升级无线网络:小型蜂窝或大规模MIMO?

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Radio network deployment and coverage optimization are critical to next-generation wireless networks. In this paper, the problem of optimally deciding on whether to install additional small cells or to upgrade current macrocell base stations (BSs) with massive antenna arrays is studied. This integrated deployment problem is cast as a general integer optimization model by using the facility location framework. The capacity limits of both the radio access link and the backhaul link are considered. The problem is shown to be an extension of the modular capacitated location problem (MCLP) which is known to be NP-hard. To solve the problem, a novel deployment algorithm that uses Lagrangian relaxation and tabu local search is proposed. The developed tabu search is shown to have a two-level structure and to be able to search the solution space thoroughly. Simulation results show how the proposed, optimal approach to upgrading an existing wireless network infrastructure can make use of a combination of both small cells and BSs with massive antennas. The results also show that the proposed algorithm can find the optimal solution effectively while having a computational time that is up to 30% lower than that of conventional algorithms.
机译:无线电网络的部署和覆盖范围的优化对于下一代无线网络至关重要。在本文中,研究了最佳决定是安装额外的小型小区还是升级具有大型天线阵列的当前宏小区基站(BS)的问题。通过使用设施位置框架,将此集成部署问题转换为通用整数优化模型。考虑无线接入链路和回程链路的容量限制。该问题显示为已知为NP困难的模块化电容位置问题(MCLP)的扩展。为了解决该问题,提出了一种使用拉格朗日松弛和禁忌局部搜索的新型部署算法。所开发的禁忌搜索显示为具有两级结构,并且能够彻底搜索解决方案空间。仿真结果表明,提出的优化现有无线网络基础结构的最佳方法如何利用小型小区和带有大型天线的BS的组合。结果还表明,提出的算法可以有效地找到最优解,同时计算时间比传统算法减少了30%。

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