Enhancements of minimax access-point setup optimisation approach for IEEE 802.11 WLAN

As a flexible and cost-efficient internet access network, the IEEE 802.11 wireless local-area network (WLAN) has been broadly deployed around the world. Previously, to improve the IEEE 802.11n WLAN performance, we proposed the four-step minimax access-point (AP) setup optimisation approach: 1) link throughputs between the AP and hosts in the network field are measured manually; 2) the throughput estimation model is tuned using the measurement results; 3) the bottleneck host suffering the least throughput is estimated using this model; 4) the AP setup is optimised to maximise the throughput of the bottleneck host. Unfortunately, this approach has drawbacks: 1) a lot of manual throughput measurements are necessary to tune the model; 2) the shift of the AP location is not considered; 3) IEEE 802.11ac devices at 5 GHz are not evaluated, although they can offer faster transmissions. In this paper, we present the three enhancements: 1) the number of measurement points is reduced while keeping the model accuracy; 2) the coordinate of the AP setup is newly adopted as the optimisation parameter; 3) the AP device with IEEE 802.11ac at 5 GHz is considered with slight modifications. The effectiveness is confirmed by extensive experiments in three network fields

A throughput drop estimation model and its application to joint optimization of transmission power, frequency channel, and channel bonding in IEEE 802.11n WLAN for large-scale IoT environments

The concept of Internet of Things (IoT) has been widely studied in smart home networks, smart city networks, smart grid systems, autonomous driving systems, and smart healthcare systems. In IoT, the IEEE 802.11n wireless local-area network (WLAN) is used as a common communication technology due to its exibility and low cost. Then, the high performance WLAN is required to enhance quality of service (QoS) of large-scale IoT applications connecting a number of devices or sensors allocated in wide areas. WLAN can use the limited number of partially overlapping channels (POCs) at 2.4 GHz band. The WLAN performance can be degraded by interfered signals from other WLANs. Then, to optimize the POC assignment by reducing interferences, we have proposed the throughput drop estimation model for concurrently communicating multiple links under interferences. Unfortunately, the 40 MHz channel bonding (CB) and the 20 MHz non-CB are considered separately, while the transmission power is always fixed to the maximum. In this paper, we study the throughput drop estimation model under coexistence of CB and non-CB while the transmission power is changed. Then, we present its application to the joint optimization of assigning the transmission power, the frequency channel, and the channel bonding to enhance the throughput performance of IEEE 802.11n WLAN. For evaluations, we compare estimated throughputs by the model with measured ones in various network topologies to verify the model accuracy. Then, we apply the model to the joint assignment optimization in them, and confirm the effectiveness through simulations and experiments using the testbed system

A Throughput Request Satisfaction Method for Concurrently Communicating Multiple Hosts in Wireless Local Area Network

Nowadays, the IEEE 802.11 wireless local area network (WLAN) has been widely used for Internet access services around the world. Then, the unfairness or insufficiency in meeting the throughput request can appear among concurrently communicating hosts with the same access point (AP), which should be solved by sacrificing advantageous hosts. Previously, we studied the fairness control method by adopting packet transmission delay at the AP. However, it suffers from slow convergence and may not satisfy different throughput requests among hosts. In this paper, we propose a throughput request satisfaction method for providing fair or different throughput requests when multiple hosts are concurrently communicating with a single AP. To meet the throughput request, the method (1) measures the single and concurrent throughput for each host, (2) calculates the channel occupying time from them, (3) derives the target throughput to achieve the given throughput request, and (4) controls the traffic by applying traffic shaping at the AP. For evaluations, we implemented the proposal in the WLAN testbed system with one Raspberry Pi AP and up to five hosts, and conducted extensive experiments in five scenarios with different throughput requests. The results confirmed the effectiveness of our proposal