# IEEE 802.11 ax OFDMA Resource Allocation with Frequency-Selective Fading
## 3 Related Work
In [22], the authors investigate the performance achievable in 802.11 ax WLANs, including the usage of MU-MIMO and OFDMA transmissions. The authors develop an analytical model to find the saturated throughput and consider such aspects as the sounding procedure and the aggregation. The authors demonstrate that single-user transmissions are less efficient than multiuser ones. At the same time, the aspects of resource scheduling for OFDMA transmissions considering the channel state variability at different STAs are not taken into account and left for further research. In our previous work [8], we have studied several OFDMA schedulers which split the entire channel between several STAs. We have shown that using the ability of multiple STAs to transfer simultaneously reduces the flow transfer latency and significantly increases the throughput compared to the case when only one STA transmits at a time. However, this study is conducted without considering the channel frequency selectivity, and the schedulers from in [8] cannot utilize the frequency-selective fading to improve the spectral efficiency. In contrast, in the present work, we eliminate this limitation. In [23], the authors design a resource scheduling solution for OFDMA transmissions in 802.11 ax. The authors focus on algorithms that can efficiently split the RUs and allocate them to STAs to minimize a cost function. As a cost function, the authors consider either the transmission duration or the maximal padding length. Note that as in [8], the designed algorithms do not take into account the frequency selectivity of the channel and do not consider the power allocation problem. In [24], a resource scheduler for 802.11 ax uplink OFDMA transmissions is designed. The authors develop a closed-loop controller that considers the amount of buffered data for different STAs and the QoS priority of different traffic flows to determine the weighting coefficients of the proportional-based scheduler. In this solution, the authors also leave out of consideration the issues of transmission power management at the STAs and do not consider frequency-selective fading: all the RUs with the same size are equal, which limits the applicability of this solution in realistic scenarios. In [25], the authors develop a scheduler that solves an optimization problem to maximize the throughput for both uplink and downlink 802.11 ax OFDMA transmissions. To avoid starvation of some STAs that have unfavorable channel conditions, the authors introduce an aging mechanism. The authors evaluate the performance of their solution using the ns-3 [26] simulator in scenarios where UDP and TCP traffic is transmitted and show a significant improvement in throughput and average delay compared with the non-OFDMA transmissions. However, also the proposed solution does not consider the frequency selectivity of the channel and does not control the STA transmission power. In [27], the author proposes a mechanism to estimate the channel for downlink MU-MIMO using the uplink OFDMA transmissions. The usage of MU-MIMO requires knowledge of CSI in an entire channel, so it is proposed to add a number of slots in the end of uplink OFDMA frame during which specific STAs will transmit channel estimation signals, one at a time. This scheme is proposed together with a scheduler of resources for data transmission in uplink OFDMA, channel estimation with OFDMA, and user selection in downlink MU-MIMO. However, the optimization problem considered in the paper does not take into account the fact that the RUs should not overlap: in case when the scheduler allocates two overlapping RUs, the author proposes to rearrange the RUs in a non-overlapping way, but does not specify how to do it. Furthermore, note that the proposed scheme does not comply with the standard. In [28], the authors study the performance of OFDMA in 802.11 ax networks with extensive simulation in ns-3.