Online Learning-Based Energy-Efficient Frame Aggregation in High Throughput WLANs
Raja Karmakar · IEEE Communications Letters · 2019
In high throughput wireless local area network (HT-WLAN) standards, such as the IEEE 802.11ac, a key enhancement in medium access control (MAC) layer is frame aggregation. However, different lengths of aggregated frames demand a variety of energy-budgets. Moreover, the carrier sense multiple access with collision avoidance is an energy-consuming channel access scheme in WLAN. In this letter, we propose an online learning-based frame aggregation, Intelligent Energy-Efficient Frame Aggregation (IE2FA), to design an energy-efficient MAC for HT-WLAN. The simulation analysis of IE2FA shows that it can improve network performance significantly compared to the other related works mentioned in the literature.