Wireless Local Area Networks (WLANs) have become increasingly popular due to the recent availability of affordable devices providing multiple and high rate capabilities. Optimizing the performance of WLANs for emerging new Internet applications that demand High Throughput (HT) is an important and a highly challenging issue. In this book, we present a new practical Rate Adaptation (RA) algorithm, termed L3S, which extends legacy schemes with new MIMO features suitable for the forthcoming 802.11n high-speed MIMO-based WLAN products. We implement our rate adaptation algorithm in real hardware devices and evaluate its performance and compare it to the existing rate control mechanisms. Our experiments demonstrate that our scheme allows the current 802.11n devices to have a greater adaptability to a variety of wireless channel conditions and performs better than state-of-the-art rate adaptation algorithms.

The current generation of IEEE 802.11 Wireless Local Area Networks (WLANs) pro- vide multiple data rates from which the different physical (PHY) layers may choose. The rate adaptation algorithm (RAA) is an essential component of 802.11 WLANs which completely determines the data rate a device may use. Some of the key chal- lenges facing data rate selection are the constantly varying wireless channel, selecting the data rate that will result in the maximum throughput, assessing the conditions based on limited feedback and estimating the link conditions at the receiver. Current RAAs lack the ability to sense their environment and adapt accordingly. 802.11 WLANs are deployed in many locations and use the same technique to choose the data rate in all locations and situations. Therefore, these RAAs suffer from the inability to adapt the method they use to choose the data transmission rate. In this thesis, a new RAA for 802.11 WLANs is proposed which provides an answer to the many challenges faced by RAAs. The proposed RAA is termed SARA which stands for Situation-Aware Rate Adaptation, and combines the use of the received signal strength and packet error rate to enable situational awareness. SARA adapts to the current environmental situation experienced at the moment to rapidly take advantage of changing channel conditions. In addition to SARA, a method to optimize the transmission power for, but not limited to, IEEE 802.11 WLANs is proposed which can determine the minimum transmission power required by a station (STA) or base station (BS) for successful transmission of a data packet. The technique reduces the transmission power to the minimum level based on the current situation while maintaining QoS constraints. The method employs a Binary Search to quickly determine the minimum transmission power with low complexity and delay. Such a technique is useful to conserve battery life in mobile devices for 802.11 WLANs. Both algorithms are implemented on an Atheros device driver for the FreeBSD operating system. SARA is compared to the benchmark algorithm SampleRate while an estimate of the energy consumed as well as the energy saved is provided for the minimum transmission power determination.