A Target Wake Time Based Power Conservation Scheme for Maximizing Throughput in IEEE 802.11ax WLANs IEEE 802.11ax, introducing Target Wake Time (TWT) mechanism, was proved as the next generation Wireless Local Area Network (WLAN) technology to improve QoS and QoE in dense scenarios. A novel broadcast TWT mechanism is proposed to save power by leveraging the new capability of uplink Orthogonal Frequency Division Multiple Access (OFDMA) based multiuser transmission. However, if the TWT is not properly scheduled, deteriorated throughput and high power consumption occur because of collisions. This paper investigates several key aspects, such as the number of simultaneously awake stations, the number of eligible random access resource units, and backoff stages, that have great impacts on the throughput and power efficiency. Based on the derived relationship, we further propose a TWT scheduling scheme (TSS) for negotiating Target Beacon Transmission Times (TBTTs) by making decisions on whether accepting the TWT request or not to maximize throughput. Besides, an algorithm on arranging stations to wake up in different beacon slots with appropriate offsets (i.e., first TBTTs) is presented. Simulation results demonstrate the effectiveness in terms of average throughput and power efficiency.

Fair and efficient resource allocation in IEEE 802.11ah WLAN with heterogeneous data rates Abstract   For dense wireless LANs (WLANs), IEEE 802.11ah has specified restricted access window (RAW) as the channel access scheme. Here the competing stations (STAs) are divided into groups and STAs belonging to each group attempt to access the channel during their designated RAW slot by invoking the distributed coordination function (DCF) protocol. This paper describes an analytical model to evaluate the throughput performance of IEEE 802.11ah WLAN, when STAs use distinct data rates and the RAW mechanism is implemented for medium sharing. When STAs are grouped randomly (i.e., without considering their data rates), a group will contain STAs operating at distinct data rates. Since all these STAs simultaneously contend for channel access based on DCF protocol, the throughput of high data rate STAs are downequalized to that of lower data rate STAs; thus the aggregate network throughput is degraded significantly. To resolve the resulting performance anomaly problem, we consider data rate based grouping where STAs operating at the same data rate are grouped together. We describe an algorithm for implementing data rate based grouping at the access point (AP). Further, we describe an analytical procedure to find the network throughput under data rate based grouping. Through numerical and experimental investigations, we establish that data rate based grouping can significantly improve the aggregate network throughput performance, as compared to the conventional random grouping strategy. Further, we use Jainxe2x80x99s fairness index (JFI) to establish that data rate based grouping can also provide fair resource allocation among the STAs operating at distinct data rates, by ensuring that all the competing STAs in the network achieve throughput proportional to their data rates.