Citation: Kassa, L.; Deng, J.; Davis, M.; Cai, J. Performance of WLAN in Downlink MU-MIMO Channel with the Least Cost in Terms of Increased Delay. Electronics 2022, 11, 2851. https://doi.org/10.3390/ electronics11182851 Academic Editors: Andrey Lyakhov and Raed A. Abd-Alhameed Received: 13 June 2022 Accepted: 26 August 2022 Published: 9 September 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). electronics Article Performance of WLAN in Downlink MU-MIMO Channel with the Least Cost in Terms of Increased Delay Lemlem Kassa 1, * , Jianhua Deng 1 , Mark Davis 2 and Jingye Cai 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 Dublin, Ireland * Correspondence: lemlem.kassa@aastu.edu.et Abstract: To improve the performance of IEEE 802.11 wireless local area (WLAN) networks, different frame-aggregation algorithms are proposed by IEEE 802.11n/ac standards to improve the throughput performance of WLANs. However, this improvement will also have a related cost in terms of increasing delay. The traffic load generated by mixed types of applications in current modern networks demands different network performance requirements in terms of maintaining some form of an optimal trade-off between maximizing throughput and minimizing delay. However, the majority of existing researchers have only attempted to optimize either one (to maximize throughput or minimize the delay). Both the performance of throughput and delay can be affected by several factors such as a heterogeneous traffic pattern, target aggregate frame size, channel condition, competing stations, etc. However, under the effect of uncertain conditions of heterogeneous traffic patterns and channel conditions in a network, determining the optimal target aggregate frame size is a significant approach that can be controlled to manage both throughput and delay. The main contribution of this study was to propose an adaptive aggregation algorithm that allows an adaptive optimal trade-off between maximizing system throughput and minimizing system delay in the WLAN downlink MU-MIMO channel. The proposed approach adopted different aggregation policies to adaptively select the optimal aggregation policy that allowed for achieving maximum system throughput by minimizing delay. Both queue delay and transmission delay, which have a significant impact when frame-aggregation algorithms are adopted, were considered. Different test case scenarios were considered such as channel error, traffic pattern, and number of competing stations. Through system- level simulation, the performance of the proposed approach was validated over the FIFO aggregation algorithm and earlier adaptive aggregation approaches, which only focused on achieving maximum throughput at the expense of delay. The performance of the proposed approach was evaluated under the effects of heterogenous traffic patterns for VoIP and video traffic applications, channel conditions, and number of STAs for WLAN downlink MU-MIMO channels. Keywords: adaptive frame aggregation; downlink MU-MIMO; wireless local area network (WLAN); network traffic; queue delay; throughput; transmission delay 1. Introduction Due to the advancement of wireless technologies, IEEE 802.11-based networks are be- coming more popular and different technologies have been introduced to improve through- put performance. Multiuser, multiple-input, multiple-output (MU-MIMO) is among the technologies at the physical layer introduced in the IEEE 802.11ac standard to accommo- date the increasing demand for high data-transmission rates by allowing a single access point (AP) that supports simultaneous transmission for up to a maximum of eight users at a time [1,2]. This is one of the most crucial technologies that has driven wireless lo- cal area networks (WLANs) into the gigabit era. Moreover, the wireless medium has a Electronics 2022, 11, 2851. https://doi.org/10.3390/electronics11182851 https://www.mdpi.com/journal/electronics