Coverage planning for outdoor wireless LAN systems

Max Kamenetskyt, Matthias Unbehaud
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引用次数: 128

Abstract

Wireless LANs (WLANs) are becoming increasingly popular for providing high data rate network access to mobile computers. Most of the currently deployed systems operate in the 2.4 GHz unlicensed frequency band. However, increasing demand for higher data rates and network capacities has led to new system standards for the 5 GHz band. We examine methods for obtaining a close-to-optimal positioning of WLAN access points (APs) and evaluate their performance in a typical downtown or campus environment. The system performance is evaluated using an objective function which aims to maximize both the coverage area and the overall signal quality. The optimization algorithms evaluate this objective function over a discrete search space, thereby considerably reducing the inherent complexity of the problem, while at the same time providing a reasonable approximation to the continuous optimization problem. Numerical results show that random search algorithms, such as simulated annealing, can yield very good solutions. However, the convergence speed of simulated annealing strongly depends on the fine-tuning of simulation parameters and a good choice of the initial set of transmitter positions. Successive removal algorithms, such as pruning, though usually producing sub-optimal solutions, converge in polynomial time. We therefore propose a combination of the two approaches - using pruning for obtaining an initial set of transmitter positions and refining these by using either neighborhood search or simulated annealing.
户外无线局域网系统的覆盖规划
无线局域网(wlan)为移动计算机提供高数据速率的网络接入而变得越来越流行。目前部署的大多数系统都在2.4 GHz未经许可的频段上运行。然而,对更高数据速率和网络容量的需求不断增长,导致了5ghz频段的新系统标准。我们研究了获得WLAN接入点(ap)接近最佳定位的方法,并评估了它们在典型的市中心或校园环境中的性能。系统性能是用一个目标函数来评估的,该目标函数的目的是最大化覆盖面积和整体信号质量。优化算法在一个离散的搜索空间中评估这个目标函数,从而大大降低了问题的固有复杂性,同时为连续优化问题提供了一个合理的近似。数值结果表明,随机搜索算法,如模拟退火,可以得到很好的解。然而,模拟退火的收敛速度很大程度上取决于模拟参数的微调和发射机初始位置的选择。连续去除算法,例如剪枝,虽然通常产生次优解,但在多项式时间内收敛。因此,我们提出了两种方法的结合-使用剪枝来获得一组初始的发射机位置,并通过邻域搜索或模拟退火来改进这些位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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