Institutionen för systemteknik

The wide spread use of IEEE Wireless LAN 802.11 in battery operated mobile devices introduced the need of power consumption optimization while meeting Quality-of-Service (QoS) requirements of applications connected through the wireless network. The IEEE 802.11 standard specifies a baseline power saving mechanism, hereafter referred to as standard Power Save Mode (PSM), and the IEEE 802.11e standard specifies the Automatic Power Save Delivery (APSD) enhancement which provides support for real-time applications with QoS requirements. The latest amendment to the WLAN 802.11 standard is the IEEE 802.11n standard which enables the use of much higher data rates by including enhancements in the Physical and MAC Layer. In this thesis, different 802.11n MAC power saving and QoS optimization possibilities are analyzed comparing against existing power saving mechanisms. Initially, the performance of the existing power saving mechanisms PSM and UnscheduledAPSD (UAPSD) are evaluated using the 802.11n process model in the OPNET simulator and the impact of frame aggregation feature introduced in the MAC layer of 802.11n was analyzed on these power saving mechanisms. From the performance analysis it can be concluded that the frame aggregation will be efficient under congested network conditions. When the network congestion level increases, the signaling load in UAPSD saturates the channel capacity and hence results in poor performance compared to PSM. Since PSM cannot guarantee the minimum QoS requirements for delay sensitive applications, a better mechanism for performance enhancement of UAPSD under dynamic network conditions is proposed. The functionality and performance of the proposed algorithm is evaluated under different network conditions and using different contention settings. From the performance results it can be concluded that, by using the proposed algorithm the congestion level in the network is reduced dynamically thereby providing a better power saving and QoS by utilizing the frame aggregation feature efficiently.