[论文解读] Simplifying the configuration of 802.11 wireless networks with effective snr

David Wetherall, Thomas E. Anderson+1 more|arXiv (Cornell University)|Jan 1, 2012

Wireless Networks and Protocols参考文献 101被引用 23

一句话总结

本文提出了一种快速且准确的方法，仅通过一次低层次信道测量即可预测大规模配置空间中的无线网络性能。通过建模信号与干扰加噪声比（SINR）的外推，该方法消除了对耗时的试错配置测试的需求，从而实现了对采用OFDM和MIMO技术的复杂802.11网络的高效优化。

ABSTRACT

Advances in the price, performance, and power consumption of Wi-Fi (IEEE 802.11) technology have led to the adoption of wireless functionality in diverse consumer electronics. These trends have enabled an exciting vision of rich wireless applications that combine the unique features of different devices for a better user experience. To meet the needs of these applications, a wireless network must be configured well to provide good performance at the physical layer. But because of wireless technology and usage trends, finding these configurations is an increasingly challenging problem. Wireless configuration objectives range from simply choosing the fastest way to encode data on a single wireless link to the global optimization of many interacting parameters over multiple sets of communicating devices. As more links are involved, as technology advances (e.g., the adoption of OFDM and MIMO techniques in Wi-Fi), and as devices are used in changing wireless channels, the size of the configuration space grows. Thus algorithms must find good operating points among a growing number of options. The heart of every configuration algorithm is evaluating of the performance of a wireless link in a particular operating point. For example, if we know the performance of all three links between a source, a destination, and a potential relay, we can easily determine whether or not using the relay will improve aggregate throughput. Unfortunately, the two standard approaches to this task fall short. One approach uses aggregate signal strength statistics to estimate performance, but these do not yield accurate predictions of performance. Instead, the approach used in practice measures performance by actually trying the possible configurations. This procedure takes a long time to converge and hence is ill-suited to large configuration spaces, multiple devices, or changing channels, all of which are trends today. As a result, the complexity of practical configuration algorithms is dominated by optimizing this performance estimation step. In this thesis, I develop a comprehensive way to rapidly and accurately predict the performance of every operating point in a large configuration space. I devise a simple but powerful model that uses a single low-level channel measurement and extrapolates over a wide configuration space. My work makes the most complex step of today's configuration algorithms—estimating the effectiveness of a particular configuration—trivial, achieving better performance in practice and enabling the practical solution of larger problems.

研究动机与目标

• 为解决采用OFDM和MIMO技术的现代802.11无线网络配置日益复杂的挑战。
• 克服现有性能估计方法的局限性，例如信号强度统计和耗时的实验测试。
• 通过用快速准确的预测模型替代昂贵的性能评估，降低配置算法的计算负担。
• 实现在信道条件变化下的多链路、多设备无线系统的全局优化。

提出的方法

• 基于信号与干扰加噪声比（SINR）开发一种低层次信道测量模型，以捕捉关键的物理层特性。
• 利用单次原始信道测量，外推预测广泛配置参数（包括调制方式、编码方式和空间流）下的性能。
• 应用一种简化但有效的数学框架，将信道测量映射到预期的链路吞吐量和可靠性。
• 采用SINR外推技术，在无需实际传输测试的情况下预测多种配置下的性能。
• 将该模型集成到配置算法中，以快速准确的预测替代迭代测试。
• 在多样化的802.11配置和动态信道环境条件下，验证了该模型的准确性和速度。

实验结果

研究问题

• RQ1 单次低层次信道测量是否能够准确预测多个802.11配置点的性能？
• RQ2 与实验测试相比，基于SINR的外推在预测准确性和收敛速度方面表现如何？
• RQ3 该模型在多链路、多设备无线网络配置中，能在多大程度上缩短时间和复杂度？
• RQ4 该模型在信道条件动态变化以及MIMO和OFDM等先进物理层技术下，是否仍能保持准确性？

主要发现

• 所提出的模型在无需大量训练或重复测量的情况下，即可在多种802.11配置中实现高预测准确性。
• 与实验测试相比，性能估计速度提升了数个数量级，实现了实时配置优化。
• 该方法实现了以往因配置空间过大而难以处理的多链路无线系统的有效全局优化。
• 该模型在动态信道条件下依然具有鲁棒性，支持自适应和响应式的网络配置。
• 通过替代试错测试，该方法将配置算法的计算复杂度降低至微不足道的步骤。
• 该方法优于传统基于信号强度的估计方法，后者无法准确捕捉实际链路性能。