Wi-Fi was originally designed to provide broadband wireless Internet access for devices which generate rather heavy streams. And Wi-Fi succeeded. The coming revolution of the Internet of Things with myriads of autonomous devices and machine type communications (MTC) traffic raises a question: can the Wi-Fi success story be repeated in the area of MTC? Started in 2010, IEEE 802.11 Task Group ah (TGah) has developed a draft amendment to the IEEE 802.11 standard, adapting Wi-Fi for MTC requirements. The performance of novel channel access enhancements in MTC scenarios can hardly be studied with models from Bianchi's clan, which typically assume that traffic load does not change with time. This paper contributes with a pioneer analytical approach to study Wi-Fi-based MTC, which can be used to investigate and customize many mechanisms developed by TGah.
In IEEE 802.11 networks, how to improve the efficiency of contention-based media access is an important, challenging issue. Recently, the grouping strategy is introduced in the IEEE 802.11ah standard to alleviate the channel contention. In IEEE 802.11ah networks, stations can be divided into groups and each group is only allowed to access wireless channel during the designated channel access period. By limiting the number of stations participating in the channel contention, it is anticipated that such a grouping strategy could substantially improve the communication efficiency. However, how to allocate the channel among different groups and how to adjust the number and sizes of groups are still open issues. In this paper, we first study the impact of the grouping strategy on the network performance, and then propose an analytical model to track the performance under saturated traffic. The accuracy of our model has been validated by simulation results. Our analytical model and results also provide important guidelines in optimizing grouping parameters.