Master of Engineering Science
Electrical and Computer Engineering
IEEE 802.11ax, which is one emerging WLAN standard, aims at providing highly efficient communication in ultra-dense wireless networks. However, due to a large number of stations (STAs) in dense deployment scenarios and diverse services to be supported, there are many technical challenges to be overcome. Firstly, the potential high packet collision rate significantly degrades the network efficiency of WLAN. In this thesis, we propose an adaptive station (STA) grouping scheme to overcome this challenge in IEEE 802.11ax using Uplink OFDMA Random Access (UORA). In order to achieve optimal utilization efficiency of resource units (RUs), we first analyze the relationship between group size and RU efficiency. Based on this result, an adaptive STA grouping algorithm is proposed to cope with the performance fluctuation of 802.11ax due to remainder stations after grouping. The analysis and simulation results demonstrate that our adaptive grouping algorithm dramatically improves the performance of both the overall system and each STA in the ultra-dense wireless network.
Meanwhile, due to the limited RU efficiency of UORA, we adopt the proposed grouping scheme in the Buffer State Report (BSR) based two-stage mechanism (BTM) to enhance the Uplink (UL) Multi-user (MU) access in 802.11ax. Then we propose an adaptive BTM grouping scheme. The analysis results of average RU for each STA, average throughput of the whole system and each STA are derived. The numerical results show that the proposed adaptive grouping scheme provides 2.55, 413.02 and 3712.04 times gains in throughput compared with the UORA grouping, conventional BTM, and conventional UORA, respectively.
Furthermore, in order to provide better QoS experience in the ultra-dense network with diverse IoT services, we propose a Hybrid BTM Grouping algorithm to guarantee the QoS requirement from high priority STAs. The concept of ``QoS Utility" is introduced to evaluate the satisfaction of transmission. The numerical results demonstrate that the proposed Hybrid BTM grouping scheme has better performance in BSR delivery rate as well as QoS utility than the conventional BTM grouping.
Bai, Jiyang, "Performance Enhancement of IEEE 802.11AX in Ultra-Dense Wireless Networks" (2018). Electronic Thesis and Dissertation Repository. 5938.