异构无线网络中基于人工神经网络的自适应垂直切换算法
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摘要
针对当前基于人工神经网络的垂直切换算法(ANN-VHO),存在业务自适应性差和计算复杂度高的问题,该文提出一种基于人工神经网络的自适应垂直切换算法。首先,根据终端获取到的接收信号强度(RSS),采用阈值判断的方法,遴选出候选网络集;其次,根据该文划分的不同业务类型,对参数进行自适应选择和归一化;再次,把选择的参数输入人工神经网络,判决出候选网络集中最佳的接入网络。最后,实验结果表明,该算法能根据用户的业务类型合理地选择切换网络,降低切换阻塞率,同时降低算法的时间复杂度。
Current research on Vertical HandOver algorithm based on Artificial Neural Network(ANN-VHO)has a poor service adaptability and high computational complexity. Considering this problem, an adaptive vertical handover algorithm based on artificial neural network is proposed. Firstly, according to the Received Signal Strength(RSS) obtained by the terminal, a method of thresholding is used to select a candidate network set. Secondly, in terms of the different types of services classified in this paper, the parameters are normalized and adaptively selected; Thirdly, the selected parameters are input into the artificial neural network to choose the best access network from the candidate network. Finally, the experimental results show that the algorithm can reasonably select the handover network according to the user's service type, reduce the handover blocking rate and lower the time complexity of the algorithm.
Current research on Vertical HandOver algorithm based on Artificial Neural Network(ANN-VHO)has a poor service adaptability and high computational complexity. Considering this problem, an adaptive vertical handover algorithm based on artificial neural network is proposed. Firstly, according to the Received Signal Strength(RSS) obtained by the terminal, a method of thresholding is used to select a candidate network set. Secondly, in terms of the different types of services classified in this paper, the parameters are normalized and adaptively selected; Thirdly, the selected parameters are input into the artificial neural network to choose the best access network from the candidate network. Finally, the experimental results show that the algorithm can reasonably select the handover network according to the user's service type, reduce the handover blocking rate and lower the time complexity of the algorithm.
引文
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[11]LI Limin,MA Lin,XU Yubin,et al.Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network[J].The Scientific World Journal,2014,2014:341038.doi:10.1155/2014/341038.
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[13]?ALHAN A and?EKEN C.Artificial neural network based vertical handoff algorithm for reducing handoff latency[J].Wireless Personal Communications,2013,71(4):2399-2415.doi:10.1007/s11277-012-0944-4.
[14]NURJAHAN,RAHMAN S,SHARMA T,et al.PSO-NFbased vertical handoff decision for ubiquitous heterogeneous wireless network(UHWN)[C].Proceedings of the 2016International Workshop on Computational Intelligence,Dhaka,Bangladesh,2017:153-158.doi:10.1109/IWCI.2016.7860357.
[15]ALSAMHI S H and RAJPUT N S.An intelligent hand-off algorithm to enhance quality of service in high altitude platforms using neural network[J].Wireless Personal Communications,2015,82(4):2059-2073.doi:10.1007/s11277-015-2333-2..
[16]ZINEB A B,AYADI M,and TABBANE S.QoE-based vertical handover decision management for cognitive networks using ANN[C].Proceedings of the 2017 Sixth International Conference on Communications and Networking,Hammamet,Tunisia,2017:1-7.doi:10.1109/COMNET.2017.8285600.
[2]HAIDER A,GONDAL I,and KAMRUZZAMAN J.Dynamic dwell timer for hybrid vertical handover in 4Gcoupled networks[C].Proceedings of the 2011 IEEE 73rd Vehicular Technology Conference,Yokohama,Japan,2011:1-5.doi:10.1109/VETECS.2011.5956636.
[3]LEE S K,SRIRAM K,KIM K,et al.Vertical handoff decision algorithms for providing optimized performance in heterogeneous wireless networks[J].IEEE Transactions on Vehicular Technology,2009,58(2):865-881.doi:10.1109/TVT.2008.925301..
[4]SINGH N P and SINGH B.Vertical handoff decision in 4Gwireless networks using multi attribute decision making approach[J].Wireless Networks,2014,20(5):1203-1211.doi:10.1007/s11276-013-0670-1..
[5]BHOSALE S and DARUWALA R.Multi-criteria vertical handoff decision algorithm using hierarchy modeling and additive weighting in an integrated WLAN/WiMAX/UMTSenvironment-A case study[J].KSII Transactions on Internet and Information Systems,2014,8(1):35-57.doi:10.3837/tiis.2014.01.003.
[6]LAHBY M and SEKKAKI A.Optimal vertical handover based on TOPSIS algorithm and utility function in heterogeneous wireless networks[C].Proceedings of the 2017International Symposium on Networks,Computers and Communications,Marrakech,Morocco,2017:1-6.doi:10 .1109/ISNCC.2017.8072023.
[7]YU Chenghai,MA Dawei,WANG Feng,et al.A novel vertical handoff algorithm based on differential pre-decision and improved utility-function method[J].International Journal of Future Generation Communication and Networking,2016,9(3):87-96.doi:10.14257/ijfgcn.2016.9.3.09.
[8]TSAI K L,LIU Hanyun,and LIU Yuwei.Using fuzzy logic to reduce ping-pong handover effects in LTE networks[J].Soft Computing,2016,20(5):1683-1694.doi:10.1007/s00500-015-1655-z..
[9]KUSTIAWAN I,LIU Chunyi,and HSU D F.Vertical handoff decision using fuzzification and combinatorial fusion[J].IEEE Communications Letters,2017,21(9):2089-2092.doi:10.1109/LCOMM.2017.2709750.
[10]马彬,张文静,谢显中.面向终端个性化服务的模糊垂直切换算法[J].电子与信息学报,2017,39(6):1284-1290.doi:10.11999/JEIT160839.MA Bin,ZHANG Wenjing,and XIE Xianzhong.Individualization service oriented fuzzy vertical handover algorithm[J].Journal of Electronics&Information Technology,2017,39(6):1284-1290.doi:10.11999/JEIT160839.
[11]LI Limin,MA Lin,XU Yubin,et al.Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network[J].The Scientific World Journal,2014,2014:341038.doi:10.1155/2014/341038.
[12]NASSER N,GUIZANI S,and Al-MASRI E.Middleware vertical handoff manager:A neural network-based solution[C].Proceedings of the 2007 IEEE International Conference on Communications,Glasgow,UK,2007:5671-5676.doi:10.1109/ICC.2007.940.
[13]?ALHAN A and?EKEN C.Artificial neural network based vertical handoff algorithm for reducing handoff latency[J].Wireless Personal Communications,2013,71(4):2399-2415.doi:10.1007/s11277-012-0944-4.
[14]NURJAHAN,RAHMAN S,SHARMA T,et al.PSO-NFbased vertical handoff decision for ubiquitous heterogeneous wireless network(UHWN)[C].Proceedings of the 2016International Workshop on Computational Intelligence,Dhaka,Bangladesh,2017:153-158.doi:10.1109/IWCI.2016.7860357.
[15]ALSAMHI S H and RAJPUT N S.An intelligent hand-off algorithm to enhance quality of service in high altitude platforms using neural network[J].Wireless Personal Communications,2015,82(4):2059-2073.doi:10.1007/s11277-015-2333-2..
[16]ZINEB A B,AYADI M,and TABBANE S.QoE-based vertical handover decision management for cognitive networks using ANN[C].Proceedings of the 2017 Sixth International Conference on Communications and Networking,Hammamet,Tunisia,2017:1-7.doi:10.1109/COMNET.2017.8285600.