Handoff Algorithm Based on Location Prediction in Ultra-dense Heterogeneous Wireless Network
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摘要:
在密集异构蜂窝网络和无线局域网络构成的超密集异构无线网络中, 变速移动的车辆终端会面临更加频繁的切换，导致用户服务质量(QoS)变差。该文针对上述问题，首先，利用高斯马尔可夫移动模型，预测车辆下一时刻的位置，筛选出满足终端服务质量的候选网络集，与当前的候选网络集做交运算，其次，当前接入网络不在交集中，则使用变步长的萤火虫算法寻找最佳网络；再次，对因预测误差导致的切换失效，则把终端用户迁移到宏蜂窝，以保证通信的持续性。仿真结果表明，在超密集异构无线网络中，使用该文所提算法能够减少乒乓切换等频繁切换现象，同时，提升了用户的服务质量和网络吞吐量。
Abstract:In the ultra-dense heterogeneous wireless network composed of heterogeneous cellular networks and wireless local area networks, vehicle terminals with variable speeds will face more frequent handovers, resulting in the deterioration of user’s Quality of Service (QoS). For the above problems, firstly, the Gauss Markov mobility model is used to predict the position of the vehicle terminal at the next moment, and the candidate network set that meets the terminal service quality is selected to make the intersection with the current candidate network set. Secondly, if the current access network is not in the intersection, the variable-step firefly algorithm is used to find the best network. Thirdly, the terminal that fails to switch due to the prediction error is migrated to the macro cellular to ensure the continuity of communication. Simulation results show that the proposed algorithm can reduce the frequent handoff phenomenon, such as ping pong handoff in the ultra-dense heterogeneous wireless network. Meanwhile, it can improve the user service quality and network throughput.
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Key words:
- Ultra-heterogeneous network /
- Handoff /
- Quality of Service (QoS) /
- Location prediction
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表 1 仿真参数的设置
网络 覆盖半径(km) 发送功率(dBm) 路径损耗因(dBm) 最大终端接入(个) 5G1 1.00 46 25 15 5G2 1.30 46 25 15 WLAN 0.50 35 35 12 micro 0.35 30 32 10 
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GHOSH A, MAEDER A, BAKER M, et al. 5G evolution: A view on 5G cellular technology beyond 3GPP release 15[J]. IEEE Access, 2019, 7: 127639–127651. doi: 10.1109/access.2019.2939938 NESTEROVA M, NICOL S, and NESTEROVA Y. Evaluating power density for 5G applications[C]. 2018 IEEE 5G World Forum, Silicon Valley, USA, 2018: 247–350. doi: 10.1109/5GWF.2018.8517003. HASAN M M, KWON S, and OH S. Frequent-handover mitigation in ultra-dense heterogeneous networks[J]. IEEE Transactions on Vehicular Technology, 2019, 68(1): 1035–1040. doi: 10.1109/TVT.2018.2874692 WIDJAJA D and UTHANSAKUL P. Additional selective threshold for velocity-considered SINR based vertical handoff[C]. 2016 International Conference on Electronics, Information, and communications, Da Nang, Vietnam, 2016: 1–4. doi: 10.1109/ELINFOCOM.2016.7562979. XU Jie, ZHAO Yanan, and ZHU Xiaorong. Mobility model based handover algorithm in LTE-advanced[C]. 2014 IEEE International Conference on Natural Computation, Xiamen, China, 2014: 230–234. doi: 10.1109/ICNC.2014.6975840. LI Xiaobin. An adaptive vertical handover method based on prediction for heterogeneous wireless networks[C]. 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, Guilin, China, 2017: 2782–2787. doi: 10.1109/FSKD.2017.8393221. 孙蔚, 夏利. 基于效用的无线异构接入网络选择机制[J]. 计算机应用, 2018, 38(S1): 116–119, 123.SUN Wei and XIA Li. Selection mechanism for utility-based heterogeneous wireless access network[J]. Journal of Computer Applications, 2018, 38(S1): 116–119, 123. 尹生华, 唐伦, 沈海强, 等. 基于参考信号接收功率预测和负载的切换算法[J]. 电子技术应用, 2017, 43(9): 101–105, 110.YIN Shenghua, TANG Lun, SHEN Haiqiang, et al. A handoff algorithm based on reference signal received power prediction and load[J]. Application of Electronic Technique, 2017, 43(9): 101–105, 110. 马良玉, 曹鹏蕊. 几种改进的萤火虫算法性能比较及应用[J]. 软件导刊, 2017, 16(1): 21–25. doi: 10.11907/rjdk.162200MA Liangyu and CAO Pengrui. Performance comparison and application of several improved firefly algorithms[J].Software Guide, 2017, 16(1): 21–25. doi: 10.11907/rjdk.162200 HUO Yiming, DONG Xiaodai, XU Wei, et al. Cellular and WiFi co-design for 5G user equipment[C]. 2018 IEEE 5G World Forum, Silicon Valley, USA, 2018: 256–261. doi: 10.1109/5GWF.2018.8517059. 马彬, 李尚儒, 谢显中. 异构无线网络中基于模糊逻辑的分级垂直切换算法[J]. 电子与信息学报, 2020, 42(3): 629–636. doi: 10.11999/JEIT190190MA Bin, LI Shangru, and XIE Xianzhong. A hierarchical vertical handover algorithm based on fuzzy logic in heterogeneous wireless networks[J]. Journal of Electronics&Information Technology, 2020, 42(3): 629–636. doi: 10.11999/JEIT190190 席斌, 李帅, 侯媛媛. 基于多目标粒子群算法的异构网接入控制[J]. 无线电通信技术, 2012, 38(40): 42–44, 50. doi: 10.3969/j.issn.1003-3114.2012.04.013XI Bin, LI Shuai, and HOU Yuanyuan. Joint call admission control in heterogeneous wireless network based on multi-objective particle swarm optimization algorithm[J]. Radio Communications Technology, 2012, 38(40): 42–44, 50. doi: 10.3969/j.issn.1003-3114.2012.04.013 吕邦国, 杨健, 于涛. 5G标准进展及关键技术[J]. 电信工程技术与标准化, 2016, 29(8): 39–43. doi: 10.3969/j.issn.1008-5599.2016.08.010LV Bangguo, YANG Jian, and YU Tao. Brief introduction of 5G standard development and key technology[J]. Telecom Engineering Technics and Standardization, 2016, 29(8): 39–43. doi: 10.3969/j.issn.1008-5599.2016.08.010 陶洋, 刘小虎, 陶玲. 基于QoS的异构网络垂直切换算法[J]. 计算机工程, 2016, 42(12): 91–96. doi: 10.3969/j.issn.1000-3428.2016.12.016TAO Yang, LIU Xiaohu, and TAO Ling. Vertical handoff algorithm in heterogeneous network based on QoS[J]. Computer Engineering, 2016, 42(12): 91–96. doi: 10.3969/j.issn.1000-3428.2016.12.016 -
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