基于分簇的小基站用户资源分配方案
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摘要
为降低密集网络系统层内干扰并提高系统容量,提出一种基于分簇的用户资源分配方案。在分簇阶段,根据小基站到簇头的最大距离方差与簇头间最小距离对初始分簇结果进行消除、合并及分裂操作,实现网络拓扑变化情况下的自适应分簇。在资源分配阶段,通过用户剩余资源有效利用及资源块微调,保障用户业务速率。仿真结果表明,与现有用户资源分配方案相比,该方案提高了系统容量及用户公平性。
In order to reduce the intra-layer interference in dense network systems and increase the system capacity,a clustering-based user resource allocation scheme is proposed.In the clustering stage,the initial clustering results are eliminated,merged and split according to the maximum distance variance from Small Base Station(SBS) to cluster-heads and the minimum distance between cluster-heads so as to realize adaptive clustering under the changing network topology.In the resource allocation stage,the user service rate is guaranteed by making use of user remaining resources and the fine adjustment of resource blocks.Simulation results show that compared with the existing user resource allocation scheme,the scheme improves system capacity and user fairness.
In order to reduce the intra-layer interference in dense network systems and increase the system capacity,a clustering-based user resource allocation scheme is proposed.In the clustering stage,the initial clustering results are eliminated,merged and split according to the maximum distance variance from Small Base Station(SBS) to cluster-heads and the minimum distance between cluster-heads so as to realize adaptive clustering under the changing network topology.In the resource allocation stage,the user service rate is guaranteed by making use of user remaining resources and the fine adjustment of resource blocks.Simulation results show that compared with the existing user resource allocation scheme,the scheme improves system capacity and user fairness.
引文
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[12] 杨峰义,谢伟良,张建敏.5G无线网络及关键技术[J].通信学报,2017,38(3):184-185.
[13] 张海波,邹剑,刘开健,等.Femtocell网络中基于分簇的资源分配机制[J].通信学报,2017,38(1):16-25.
[14] XU Liang,MAO Yuming,LENG Supeng.A cluster-based resource allocation strategy with energy harvesting in dense small-cell networks[C]//Proceedings of International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.Washington D.C.,USA:IEEE Press,2017:303-310.
[15] ZHAO Caidan,XU Xiaofei,GAO Zhibin.A coloring-based cluster resource allocation for ultra dense network[C]//Proceedings of IEEE International Conference on Signal Processing,Communications and Computing.Washington D.C.,USA:IEEE Press,2016:1-5.
[16] LIN Shangjing,TIAN Hui.Clustering based interference management for QoS guarantees in OFDMA femtocell[C]//Proceedings of Wireless Communications and Networking Conference.Washington D.C.,USA:IEEE Press,2013:649-654.
[17] WEI Rong,WANG Ying,ZHANG Yuan.A two-stage cluster-based resource management scheme in ultra-dense networks[C]//Proceedings of IEEE/CIC International Conference on Communications.Washington D.C.,USA:IEEE Press,2015:738-742.
[18] 贾瑞玉,宋建林.基于聚类中心优化的最佳聚类数确定方法[J].微电子学与计算机,2016,33(5):62-66.
[2] SAUNDERS S,CARLAW S,GIUSTINA A,et al.Femtocells:opportunities and challenges for business and technology[M].New York,USA:John Wiley and Sons,2009.
[3] 3GPP.Requirements for further advancements for evolved universal terrestrial radio access:ETSI TR 36.913 V8.0.1[R/OL].[2018-02-17].https://www.etsi.org/deliver/etsi_tr/136900_136999/136913/09.00.00_60/tr_136913v090000p.pdf.
[4] 尤肖虎,潘志文,高西奇,等.5G移动通信发展趋势与若干关键技术[J].中国科学:信息科学,2014,44(5):551-563.
[5] KAMEL M,HAMOUDA W,YOUSSEF A.Ultra-dense networks:a survey[J].IEEE Communications Surveys and Tutorials,2017,18(4):2522-2545.
[6] ACHAR R,RAJESH A,NAKKEERAN R,et al.Heterogeneous resource allocation in LTE based femtocell networks[C]//Proceedings of International Conference on Circuit,Power and Computing Technologies.Washington D.C.,USA:IEEE Press,2015:1-6.
[7] VARGHESE A,SUDHA T.A resource allocation scheme for throughput maximization in OFDMA femtocell networks[C]//Proceedings of International Conference on Control Communication and Computing India.Washington D.C.,USA:IEEE Press,2016:407-412.
[8] SHEIKHZADEH S,MOKARI N,SAEEDI H.Radio resource allocation for interference management in OFDMA-based femtocell-macrocell deployment[C]//Proceedings of the 24th Iranian Conference on Electrical Engineering.Washington D.C.,USA:IEEE Press,2016:757-761.
[9] LIU Yuanfei,WANG Ying,ZHANG Yuan,et al.Game-theoretic hierarchical resource allocation in ultra-dense networks[C]//Proceedings of IEEE International Symposium on Personal,Indoor,and Mobile Radio Communications.Washington D.C.,USA:IEEE Press,2016:1-6.
[10] VU N H,LONG B L.Fair resource allocation for OFDMA femtocell networks with macrocell protection[J].IEEE Transactions on Vehicular Technology,2014,63(3):1388-1401.
[11] 王莹,缪中宇,张平.超高密度网络关键技术及研究现状[J].北京邮电大学学报,2015,38(5):1-17.
[12] 杨峰义,谢伟良,张建敏.5G无线网络及关键技术[J].通信学报,2017,38(3):184-185.
[13] 张海波,邹剑,刘开健,等.Femtocell网络中基于分簇的资源分配机制[J].通信学报,2017,38(1):16-25.
[14] XU Liang,MAO Yuming,LENG Supeng.A cluster-based resource allocation strategy with energy harvesting in dense small-cell networks[C]//Proceedings of International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.Washington D.C.,USA:IEEE Press,2017:303-310.
[15] ZHAO Caidan,XU Xiaofei,GAO Zhibin.A coloring-based cluster resource allocation for ultra dense network[C]//Proceedings of IEEE International Conference on Signal Processing,Communications and Computing.Washington D.C.,USA:IEEE Press,2016:1-5.
[16] LIN Shangjing,TIAN Hui.Clustering based interference management for QoS guarantees in OFDMA femtocell[C]//Proceedings of Wireless Communications and Networking Conference.Washington D.C.,USA:IEEE Press,2013:649-654.
[17] WEI Rong,WANG Ying,ZHANG Yuan.A two-stage cluster-based resource management scheme in ultra-dense networks[C]//Proceedings of IEEE/CIC International Conference on Communications.Washington D.C.,USA:IEEE Press,2015:738-742.
[18] 贾瑞玉,宋建林.基于聚类中心优化的最佳聚类数确定方法[J].微电子学与计算机,2016,33(5):62-66.
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