Transmission Power Optimization of Concurrently Communicating Two Access Points in Wireless Local Area Network

Briantoro, Hendy; Funabiki, Nobuo; Kuribayashi, Minoru; Munene, Kwenga Ismael; Sudibyo, Rahardhita Widyatra; Islam, Md. Manowarul; Kao, Wen-Chung

doi:10.4018/ijmcmc.2020100101

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…(1) RSS-based strategy [41] [42], we adopt SOGA (single-objective genetic algorithm) to realize the handover strategy (4) Weighted-based handover strategy [43]: the weight of the received signal strength, the handover times, and the conflict times are set as by w 1 = 1/3, w 2 = 1 /3, and w 3 = 1/3. Then, we exploit single-objective optimization to get the optimal solution based on geatpy…”

Section: Unilateral Performance With Differentmentioning

confidence: 99%

A LEO Satellite Handover Strategy Based on Graph and Multiobjective Multiagent Path Finding

Zhiyun

Wang

et al. 2023

International Journal of Aerospace Engineering

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Low earth orbit (LEO) satellite network can provide services to users anywhere on the earth. However, the high-speed mobility of satellites leads to a dynamic environment, which brings challenges for handover and network performance optimization, especially in the scenario of multiuser using the networks meanwhile. In this paper, we exploit multiple directed graphs to model the handover process for multiuser. The nodes in a graph represent the satellites that the corresponding user may choose to access. The edges represent the possible handovers between adjacent timestamps. The path from the start node to the end node in each graph is the handover strategy of the corresponding user, and the path length is the reward that the user can get. Therefore, the handover strategy problem is transformed into a path planning problem. To minimize the average handover times, maximize the average received power, and minimize the average number of conflicts, we propose a novel handover strategy based on multiobjective multiagent path finding (MOMAPF). The simulated handover experiment on Starlink successfully derives the Pareto-optimal solution set, which corroborates the effectiveness of the proposed handover strategy. The results also show that the proposed strategy has better comprehensive performance than other strategies.

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Section: Unilateral Performance With Differentmentioning

confidence: 99%

A LEO Satellite Handover Strategy Based on Graph and Multiobjective Multiagent Path Finding

Zhiyun

Wang

et al. 2023

International Journal of Aerospace Engineering

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“…The proposed method only considers either the minimum or maximum transmission power of an AP, although a modern AP supports a wide range of transmission power levels. However, our limitation of the power selection comes from our prior work reported in [ 22 ]. In this study, we measured the throughput using the testbed system when the AP transmission power was gradually changed from the minimum to the maximum, including medium values in various topologies.…”

Section: Review Of Previous Studiesmentioning

confidence: 99%

An Interface Setup Optimization Method Using a Throughput Estimation Model for Concurrently Communicating Access Points in a Wireless Local Area Network

Akhter

Funabiki

Htet

et al. 2023

Sensors

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The IEEE 802.11 wireless local-area network (WLAN) has been deployed around the globe as a major Internet access medium due to its low cost and high flexibility and capacity. Unfortunately, dense wireless networks can suffer from poor performance due to high levels of radio interference resulting from adjoining access points (APs). To address this problem, we studied the AP transmission power optimization method, which selects the maximum or minimum power supplied to each AP so that the average signal-to-interference ratio (SIR) among the concurrently communicating APs is maximized.However, this method requires measurements of receiving signal strength (RSS) under all the possible combinations of powers. It may need intolerable loads and time as the number of APs increases. It also only considers the use of channel bonding (CB), although non-CB sometimes achieves higher performance under high levels of interference. In this paper, we present an AP interface setup optimization method using the throughput estimation model for concurrently communicating APs. The proposed method selects CB or non-CB in addition to the maximum or minimum power for each AP. This model approach avoids expensive costs of RSS measurements under a number of combinations. To estimate the RSS at an AP from another AP or a host, the model needs the distance and the obstacles between them, such as walls. Then, by calculating the estimated RSS with the model and calculating the SIR from them, the AP interface setups for a lot of APs in a large-scale wireless network can be optimized on a computer in a very short time. For evaluation, we conducted extensive experiments using Raspberry Pi for APs and Linux PCs for hosts under 12 network topologies in three buildings at Okayama University, Japan, and Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. The results confirm that the proposed method selects the best AP interface setup with the highest total throughput in any topology.

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“…In this paper, the proposed method selects only the minimum transmission power or the maximum transmission power of the device for any AP. This comes from the results of our previous study in [20] on how the overall throughput performance of the WLAN is effected when the transmission power of each AP is gradually increased from the minimum to the maximum in various topologies. Here, it was shown that the overall throughput performance of the WLAN is maximized when either the maximum power or the minimum power is assigned at each AP in any topology.…”

Section: Ideamentioning

confidence: 99%

“…Previously, we have studied the transmission power optimization method for two concurrently communicating APs in WLAN [7]. This method selects either the maximum or minimum transmission power for each AP such that the SNR is highest among the possible ones.…”

Section: Introductionmentioning

confidence: 99%

Joint Optimization Method of Channel Assignment and Transmission Power for Concurrently Communicating Multiple Access-Points in Wireless Local-Area Network

Briantoro

Funabiki

Rahman

et al. 2021

IJNC

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Currently, IEEE 802.11n wireless local-area network (WLAN) is popular for the Internet access due to mobility, flexibility, and scalability. Multiple access-points (APs) are often allocated in WLAN to cover the wide area, which may cause interferences and reduce the performances. Previously, we have studied the transmission power optimization method for two concurrently communicating APs to reduce interferences. It selects either the maximum or minimum power for each AP such that signal-to-noise ratio (SNR) is highest. However, it was found that the channel assignment is also important when multiple APs are closely allocated in dense WLAN. In this paper, we propose a joint optimization method of channel assignment and transmission power for concurrently communicating multiple APs in WLAN. First, the same channel is assigned to the nearby APs where the CSMA/CA protocol works well, and the most distant channels are to the other APs. Second, the transmission power is optimized by selecting the highest measured SNR. To reduce the SNR measurement load, 1) the maximum power is assigned to every AP, 2) the initial RSS from the associated host is measured, 3) the minimum power is assigned to one AP in descending order of the initial RSS, and the SNR is measured, and 4) the power combination for the highest SNR is selected. For evaluations, we conduct extensive experiments under various network topologies using up to four Raspberry Pi APs. The results show that the proposal always selects the best channel and transmission power for each AP that offers the highest throughput performance.

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Transmission Power Optimization of Concurrently Communicating Two Access Points in Wireless Local Area Network

Cited by 5 publications

References 14 publications

A LEO Satellite Handover Strategy Based on Graph and Multiobjective Multiagent Path Finding

A LEO Satellite Handover Strategy Based on Graph and Multiobjective Multiagent Path Finding

An Interface Setup Optimization Method Using a Throughput Estimation Model for Concurrently Communicating Access Points in a Wireless Local Area Network

Joint Optimization Method of Channel Assignment and Transmission Power for Concurrently Communicating Multiple Access-Points in Wireless Local-Area Network

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