Utility Maximization of Capacity Entropy for Dense IEEE 802.11ax WLANs based on Interference Characteristics

Abstract

Internet of Things (IoT) is a kind of information carrier, which enables for all ordinary objects that can perform independent functions to realize interconnection. The standardization process of wireless local area networks (WLANs) which is an important network system of IoT is gradually advancing. IEEE 802.11ax will replace IEEE 802.11a/b/g/n/ac as the latest WLANs standard. The uplink transmission of IEEE 802.11ax adopts a hybrid access mode. The mode means that the stations (STAs) can access the network adopting either scheduling access mode or random access mode. Since the hybrid access mode supports both the scheduling and random access, how to allocate the resources among the STAs which adopt the two access modes is the first problem to be solved. In particular, IEEE 802.11ax focuses more on the network performance of the high-dense deployment scenarios. The characteristic of the interference of the overlapping basic service set (OBSS) situation is the key factor of the efficiency of resource allocation algorithm. Therefore, firstly, this paper combines capacity entropy multi-user access (CEM) with utility function, and defines a metric value to measure the utility of two kinds of users. Secondly, the simulation-assisted method is used to obtain the probability distribution characteristic of the interference power random variables from dense multi-cell scenarios of IEEE 802.11ax. Then, based on interference power random variables which generated by the probability density curve obtained by simulation, we propose an algorithm which can maximizetotal utility of scheduling and random access STAs, i.e., to maximize the total satisfaction of all STAs. The authors believe that the research can enhance the quality of experience (QoE) of users in dense multi-cell scenarios for the next generation WLANs.