In this paper, we examine techniques for improving the throughput of unlicensed radio systems such as wireless LANs (WLANs) to take advantage of multi-radio access to mobile broadband, which will be important in 5G evolution and beyond. In WLANs, throughput is reduced due to mixed standards and the degraded quality of certain frequency channels, and thus control techniques and an architecture that provide efficient control over WLANs are needed to solve the problem. We have proposed a technique to control the terminal connection dynamically by using the multi-radio of the AP. Furthermore, we have proposed a new control architecture called WiSMA for efficient control of WLANs. Experiments show that the proposed method can solve those problems and improve the WLAN throughput.

In this paper, we propose a novel centralized control method to handle multi-radio and terminal connections in an 802.11ax wireless LAN (802.11ax) mixed environment. The proposed control method can improve the throughput by applying 802.11ax Spatial Reuse in an environment hosting different terminal standards and mixed terminal communication quality. We evaluate the proposed control method by computer simulations assuming environments with mixed terminal standards, mixed communication quality, and both.

Distributed channel selection schemes are proposed in this paper to mitigate the flow-in-the-middle (FIM) starvation in dense wireless local area networks (WLANs). The FIM starvation occurs when the middle transmitter is within the carrier sense range of two exterior transmitters, while the two exterior transmitters are not within the carrier sense range of each other. Since an exterior transmitter sends a frame regardless of the other, the middle transmitter has a high probability of detecting the channel being occupied. Under heavy traffic conditions, the middle transmitter suffers from extremely low transmission opportunities, i.e., throughput starvation. The basic idea of the proposed schemes is to let each access point (AP) select the channel which has less three-node-chain topologies within its two-hop neighborhood. The proposed schemes are formulated in strategic form games. Payoff functions are designed so that they are proved to be potential games. Therefore, the convergence is guaranteed when the proposed schemes are conducted in a distributed manner by using unilateral improvement dynamics. Moreover, we conduct evaluations through graph-based simulations and the ns-3 simulator. Simulations confirm that the FIM starvation has been mitigated since the number of three-node-chain topologies has been significantly reduced. The 5th percentile throughput has been improved.

Dense deployments of wireless local area network (WLAN) access points (APs) are accelerating to accommodate the massive wireless traffic from various mobile devices. The AP densification improves the received power at mobile devices; however, total throughput in a target area is saturated by inter-cell interference (ICI) because of the limited number of frequency channels available for WLANs. To substantially mitigate ICI, we developed and described a distributed smart antenna system (D-SAS) proposed for dense WLAN AP deployment in this paper. We also describe a system configuration based on our D-SAS approach. In this approach, the distributed antennas externally attached to each AP can be switched so as to make the transmit power match the mobile device's conditions (received power and packet type). The gains obtained by the antenna switching effectively minimize the transmission power required of each AP. We also describe experimental measurements taken in a stadium using a system prototype, the results show that D-SAS offers double the total throughput attained by a centralized smart antenna system (C-SAS).

Efficient use of heterogeneous wireless access networks is necessary to maximize the capacity of the 5G mobile communications system. The wireless local area networks (WLANs) are considered to be one of the key wireless access networks because of the proliferation of WLAN-capable mobile devices. However, throughput starvation can occur due to the well-known exposed/hidden terminal problem in carrier sense multiple access with collision avoidance (CSMA/CA) based channel access mechanism, and this problem is a critical issue with wireless LAN systems. This paper proposes two novel schemes to identify starved access points (APs) and user equipments (UEs) which throughputs are relatively low. One scheme identifies starved APs by observing the transmission delay of beacon signals periodically transmitted by APs. The other identifies starved UEs by using the miscaptured beacon signals ratio at UEs. Numerous computer simulations verify that that the schemes can identify starved APs and UEs having quite low throughput and are superior to the conventional graph-based identification scheme. In addition, AP and UE management with the proposed schemes has the potential to improve system throughput and reduce the number of low throughput UEs.

In this paper, a stochasic geometry analysis of the inversely proportional setting (IPS) of carrier sense threshold (CST) and transmission power for densely deployed wireless local area networks (WLANs) is presented. In densely deployed WLANs, CST adjustment is a crucial technology to enhance spatial reuse, but it can starve surrounding transmitters due to an asymmetric carrier sensing relationship. In order for the carrier sensing relationship to be symmetric, the IPS of the CST and transmission power is a promising approach, i.e., each transmitter jointly adjusts its CST and transmission power in order for their product to be equal to those of others. This setting is used for spatial reuse in IEEE 802.11ax. By assuming that the set of potential transmitters follows a Poisson point process, the impact of the IPS on throughput is formulated based on stochastic geometry in two scenarios: an adjustment at a single transmitter and an identical adjustment at all transmitters. The asymptotic expression of the throughput in dense WLANs is derived and an explicit solution of the optimal CST is achieved as a function of the number of neighboring potential transmitters and signal-to-interference power ratio using approximations. This solution was confirmed through numerical results, where the explicit solution achieved throughput penalties of less than 8% relative to the numerically evaluated optimal solution.