SAMU: Design and Implementation of Frequency Selectivity-Aware Multi-User MIMO for WLANs

The traffic demand of wireless networks is expected to increase 1000-fold over the next decade. In anticipation of such increasing data demand for dense networks with a large number of stations, IEEE 802.11ax has introduced key technologies for capacity improvement including Orthogonal Frequency-Division Multiple Access (OFDMA), multi-user multi-input multi-output (MU-MIMO), and greater bandwidth. However, IEEE 802.11ax has yet to fully define a specific scheduling framework, on which the throughput improvement of networks significantly depends. Even within a 20 MHz of bandwidth, users experience heterogeneous channel orthogonality characteristics across sub-carriers, which prevents access points (APs) from achieving the ideal multi-user gain. Moreover, frequency selectivity increases as bandwidth scales and correspondingly severely deteriorates multi-user MIMO performance. In this work, we develop a novel channel adaptation scheme, named selectivity-aware multi-user MIMO (SAMU), to combat the issue of frequency selectivity and support coexistence among users in the network by jointly assigning subsets of sub-carriers to selected users and implementing downlink MU-MIMO. To do so, we first investigate the channel characteristics of an indoor environment. We then consider the frequency selectivity of current and emerging WiFi channel bandwidths to optimize multi-user MIMO by dividing the occupied sub-carrier resources into equally sized sub-channels according to the level of frequency selectivity. In our design, each sub-channel is allocated according to the largest bandwidth that can be considered frequency-flat, and an optimal subset of users is chosen to serve in each sub-channel according to spatial orthogonality. As a result, we support more simultaneous users than current 802.11 designs and achieve a significant performance improvement for all users in the network. Additionally, we propose a selectivity-aware high efficiency (SA-HE) mode, which is based on and fully backward compatible with the existing IEEE 802.11ax standard. Finally, over emulated and real indoor channels, we show that SAMU can achieve as much as 84.8% throughput improvement compared to existing multi-user MIMO schemes in IEEE 802.11a