Home > Published Issues > 2021 > Volume 16, No. 8, August 2021 >

A New Adaptive Frame Aggregation Method for Downlink WLAN MU-MIMO Channels

Lemlem Kassa 1, Mark Davis 2, Jingye Cai 1, and Jianhua Deng 1
1. School of Information and Software Engineering, University of Electronic Science and Technology China (UESTC), Chengdu, 610054, China
2. Communication Network Research Institute (CNRI), Technological University Dublin, D08 NF82, Ireland

Abstract—Accommodating the heterogeneous traffic demand among streams in the downlink MU-MIMO channel is among the challenges that affect the transmission efficiency since users in the channel do not always have the same traffic demand. Consequently, it is feasible to adjust the frame size to maximize the system throughput. The existing adaptive aggregation solutions do not consider the effects of different traffic scenarios and they use a Poison traffic model which is inadequate to represent the real network traffic scenarios, thus leading to suboptimal solutions. In this study, we propose some adaptive aggregation strategies which employ a novel dynamic adaptive aggregation policy selection algorithm in addressing the challenges of heterogenous traffic demand in the downlink MU-MIMO channel. Different traffic models are proposed to emulate real world traffic scenarios in the network and to analyze the proposed aggregation polices with respect to various traffic models. Finally, through simulation, we demonstrate the performance of our adaptive algorithm over the baseline FIFO aggregation approach in terms of system throughput performance and channel utilization in achieving the optimal frame size of the system.
Index Terms—Channel utilization, downlink MU-MIMO, heterogeneous traffic, frame aggregation, frame size optimization, transmission efficiency, WLAN.

Cite: Lemlem Kassa, Mark Davis, Jingye Cai, and Jianhua Deng, "A New Adaptive Frame Aggregation Method for Downlink WLAN MU-MIMO Channels," Journal of Communications vol. 16, no. 8, pp. 311-322, August 2021. Doi: 10.12720/jcm.16.8.311-322

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.