Reinforcement Learning-Based Handover Scheme with Neighbor Beacon Frame Transmission  

作　　者：Youngjun Kim Taekook Kim Hyungoo Choi Jinwoo Park Yeunwoong Kyung 

机构地区：[1]School of Electrical Engineering,Korea University,Seoul,02841,Korea [2]School of Computer Engineering,Pukyong National University,Busan,48547,Korea [3]School of Computer Engineering,Hanshin University,Osan,18101,Korea

出　　处：《Intelligent Automation & Soft Computing》2023年第4期193-204,共12页智能自动化与软计算（英文）

基　　金：supported by the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)(No.2020R1G1A1100493).

摘　　要：Mobility support to change the connection from one access point(AP)to the next(i.e.,handover)becomes one of the important issues in IEEE 802.11 wireless local area networks(WLANs).During handover,the channel scanning procedure,which aims to collect neighbor AP(NAP)information on all available channels,accounts for most of the delay time.To reduce the channel scanning procedure,a neighbor beacon frame transmission scheme(N-BTS)was proposed for a seamless handover.N-BTS can provide a seamless handover by removing the channel scanning procedure.However,N-BTS always requires operating overhead even if there are few mobile stations(MSs)for the handover.Therefore,this paper proposes a reinforcement learning-based handover scheme with neighbor beacon frame transmission(MAN-BTS)to properly consider the use of N-BTS.The optimization equation is defined to maximize the expected reward tofind the optimal policy and is solved using Q-learning.Simulation results show that the proposed scheme outperforms the comparison schemes in terms of the expected reward.

关 键 词：Channel scanning HANDOVER handover delay IEEE 802.11 WLANS Q-LEARNING reinforcement learning 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]