[1] Liu Chengyi, Xing Song, Shen Lianfeng,. A long-term-based handover decision algorithmfor dense macro-femto coexistence networks [J]. Journal of Southeast University (English Edition), 2017, 33 (2): 127-133. [doi:10.3969/j.issn.1003-7985.2017.02.001]
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A long-term-based handover decision algorithmfor dense macro-femto coexistence networks(
)
密集macro-femto融合网络中基于长期逗留的切换决策算法
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 33
- Issue:
- 2017 2
- Page:
- 127-133
- Research Field:
- Information and Communication Engineering
- Publishing date:
- 2017-06-30
Info
- Title:
- A long-term-based handover decision algorithmfor dense macro-femto coexistence networks
- 密集macro-femto融合网络中基于长期逗留的切换决策算法
- Author(s):
- Liu Chengyi1; Xing Song2; Shen Lianfeng1
-
1National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
2Department of Information Systems, California State University, Los Angeles 90001, USA
- Keywords:
- handover decision algorithm; angle of handover; time-to-stay; dense macro-femto coexistence networks; mobile base station
- PACS:
- TN915
- DOI:
- 10.3969/j.issn.1003-7985.2017.02.001
- Abstract:
- For the dense macro-femto coexistence networks scenario, a long-term-based handover(LTBH)algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover(AHO)and the time-to-stay(TTS)to reduce the unnecessary handover numbers. First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations(CBSs)scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.
- 针对密集macro-femto融合网络, 提出一种基于长期稳定的切换(long-term-based handover, LTBH)决策算法.该算法由切换角(angle of handover, AHO)和逗留时间(time-to-stay, TTS)2种参数联合进行切换判决, 从而有效减小冗余切换次数.首先, 在大量候选基站(candidate base stations, CBSs)场景中提出了AHO参数, 从而降低算法的计算复杂度.其次, 针对固定基站和移动基站2种基站模型, 分别提出了2种TTS参数用于切换用户的切换决策.仿真结果显示, 所提的LTBH算法能够在密集macro-femto网络中保证移动用户一定传输速率的基础上有效地降低网络中的切换次数.
References:
[1] Gambini J, Spagnolini U. Wireless over cable for femtocell systems [J]. IEEE Communications Magazine, 2013, 51(5): 178-185. DOI:10.1109/mcom.2013.6515063.
[2] Li L, Chu X, Zhang J. A hierarchical MADM-based network selection scheme for system performance enhancement [C]//2014 IEEE International Conference on Communication Systems. Macau, China, 2014: 122-126. DOI:10.1109/mcom.2013.6515063.
[3] Mansouri M, Leghris C, Bekkhoucha A. Towards a better combination of the MADM algorithms for the vertical handover optimization in a mobile network multi-access environment [C]//2015 10th International Conference on Intelligent Systems: Theories and Applications. Rabat, Morocco, 2015: 15678139-1-15678139-5. DOI:10.1109/sita.2015.7358421.
[4] Choi H. An optimal handover decision for throughput enhancement [J]. IEEE Communications Letters, 2010, 14(9): 851-853. DOI:10.1109/lcomm.2010.09.092356.
[5] Tamea G, Biagi M, Cusani R. Soft multi-criteria decision algorithm for vertical handover in heterogeneous networks [J]. IEEE Communications Letters, 2011, 15(11): 1215-1217. DOI:10.1109/lcomm.2011.090911.111537.
[6] Xenakis D, Passas N, Verikoukis C. A novel handover decision policy for reducing power transmissions in the two-tier LTE network [C]//2012 IEEE International Conference on Communications. Ottawa, Canada, 2012: 1352-1356. DOI:10.1109/icc.2012.6363941.
[7] Simsek M, Bennis M, Güvenc I. Context-aware mobility management in HetNets: A reinforcement learning approach [C]//2015 IEEE Wireless Communications and Networking Conference. New Orleans, USA, 2015: 1536-1541. DOI:10.1109/wcnc.2015.7127696.
[8] Xenakis D, Passas N, Merakos L, et al. Energy-efficient and interference-aware handover decision for the LTE-advanced femtocell network [C]//2013 IEEE International Conference on Communications. Budapest, Hungary, 2013: 2464-2468. DOI:10.1109/icc.2013.6654902.
[9] Balakrishnan R, Akyildiz I. Local anchor schemes for seamless and low-cost handover in coordinated small cells [J]. IEEE Transactions on Mobile Computing, 2015, 15(5): 1182-1196.
[10] Chen Y, Zhang J, Zhang Q. Utility-aware refunding framework for hybrid access femtocell network [J]. IEEE Transactions on Wireless Communications, 2012, 11(5): 1688-1697. DOI:10.1109/twc.2012.031212.110002.
[11] Chen G, Zheng J, Shen L. A preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tierfemtocell networks [C]//2013 IEEE Globecom. Atlanta, USA, 2013: 4717-4722.
[12] Liu C, Xia W, Chen G, et al. Location-aware handover decision algorithm in multi-cell networks [C]//2013 International Conference on Wireless Communications and Signal Processing. Hangzhou, China, 2013: 1-6.
[13] Hashem K, Yousefi S, Shayesteh M. Adaptive handover algorithm in heterogeneous femto cellular networks based on received signal strength and signal-to-interference-plus-noise ratio prediction [J]. IET Communications, 2014, 8(17): 3061-3071. DOI:10.1049/iet-com.2014.0230.
[14] Liu C, Xing S, Shen L. Dynamic hybrid-access control in multi-user and multi-femtocell networks via stackelberg game competition [J]. IET Communications, 2016, 10(7): 862-872. DOI:10.1049/iet-com.2015.0684.
Memo
- Memo:
-
Biographies: Liu Chengyi(1986—), male, graduate; Shen Lianfeng(corresponding author), male, professor, lfshen@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.61471164), the Fundamental Research Funds for the Central Universities, the Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX-0133).
Citation: Liu Chengyi, Xing Song, Shen Lianfeng.A long-term-based handover decision algorithm for dense macro-femto coexistence networks[J].Journal of Southeast University(English Edition), 2017, 33(2):127-133.DOI:10.3969/j.issn.1003-7985.2017.02.001.