Frame-Aggregated Link Adaptation Algorithm for IEEE 802.11n Networks

Abstract

Channel condition is considered an important issue that affects the performance in wireless networks. Link Adaptation techniques have been proposed to improve the degraded network performance by adjusting the design parameters, e. g. the modulation and coding schemes, in order to adopt the dynamically changing channel conditions. Furthermore, due to the advancement of the IEEE 802.11n standard, the network goodput can be enhanced with the exploitation of its frame aggregation schemes. However, none of the existing link adaption algorithm is designed to consider the feasible aggregated frame length that should be adapted according to the changing environments. In this paper, A frame-aggregated link adaptation (FALA) algorithm is proposed to dynamically adjust system parameters in order to improve the network goodput under varying channel conditions. For the purpose of maximizing the network goodput, both the optimal frame payload size and the modulation and coding schemes are jointly acquired according to the signal-to-noise ratio under specific channel condition. Numerical results illustrate that the proposed FALA protocol can effectively increase the goodput performance comparing with other existing link adaptation schemes, especially under dynamically changing environments.