超高密度无线网络的自组织技术

doi:10.11959/j.issn.1000-436x.2016131

摘要/Abstract

摘要：

网络密集化是应对未来5G无线网络容量提升1 000倍挑战的主要手段之一，且超高密度网络中单节点要配置和优化的参数超过2 000个，因此，只有通过新一代自组织技术来感知网络运行的态势，自主发现和调配网络资源来精准匹配网络中的业务流，才能有效提高网络的承载能力。分析了超高密度网络自组织技术面临的挑战和呈现的新属性，给出了超高密度网络中自组织技术的2个典型用例，展望了超高密度无线网络中自组织技术的发展前景和方向。

关键词: 超密无线网络, 自组织技术, 可密集性

Abstract:

Network densification was one of the main ways to deal with the challenge of supporting 1 000 times higher capacity in 5G networks. Wherein, a single node needs to configure and optimize more than 2 000 parameters. Therefore, novel self-organizing network (SON) would be the inevitable technique for wireless networking, where decision makers were enabled with the ability of perceiving the dynamic network situation and meanwhile, autonomously discovering as well as configuring network resources. With the aid of this promising technique, users' demands and network resources could be well matched and furthermore, the capacity of networks could be significantly improved. The trend of dense development in wireless communications was discussed. Then, the potential challenges and required new properties was analyzed when util-izing SON in ultra-dense wireless networks. Meanwhile, two typical use cases were depicted. Finally, for future ultra-densely deployed wireless networks, the possible development prospect and direction of SON were briefly presented.

Key words: ultra-dense wireless network, self-organizing technique, densability

李建东,滕伟,盛敏,徐超. 超高密度无线网络的自组织技术[J]. 通信学报, 2016, 37(7): 30-37.

Jian-dong LI,Wei TENG,Min SHENG,Chao XU. Self-organizing techniques in ultra-dense wireless network[J]. Journal on Communications, 2016, 37(7): 30-37.

图/表 7

图1

图2

图3

图4

图5

图6

图7

参考文献 35

[1]	Qualcomm Incorporated(2013,7). The 1 000x data challenge[EB/OL]. .
[2]	ANDREWSJG , BUZZI S , CHOI W . What will 5G be?[J]. IEEE Journal on Selected Areas in Communications, 2014,32(6):1065-1082.
[3]	BHUSHAN N , LI J , MALLADI D . Network densification: the dominant theme for wireless evolution into 5G[J]. IEEE Communications Magazine, 2014,52(2):82-89.
[4]	LEI L , SHEN X , DOHLER M , et al. Queuing models with applica-tions to mode selection in device-to-device communications underlay-ing cellular networks[J]. IEEE Transactions on Wireless Communications, 2014,13(12):6697-6715.
[5]	MOGENSEN P , PAJUKOSKI K , TIIROLA E . Centimeter-wave con-cept for 5G ultra-dense small cells[C]// Vehicular Technology Conference (VTC Spring), c2014:1-6.
[6]	IMRAN A , ZOHA A . Challenges in 5G: how to empower SON with big data for enabling 5G[J]. IEEE Network, 2014,28(6):27-33.
[7]	LOPEZ-PEREZ D , DING M , CLAUSSEN H , et al. Towards 1Gbps/UE: understanding ultra dense small cell deployments[J]. IEEE Communications Surveys ＆ Tutorial, 2015:1.
[8]	GOTSIS A , STEFANATOS S , ALEXIOU A . Ultra dense networks: the new wireless frontier for enabling 5G access[J]. Computer Science, 2015,23(1):72-79.
[9]	PENG H , XIAO Y , RUYUE Y N , et al. Ultra dense network: chal-lenges, enabling technologies and new trends[J]. China Communications, 2016,13(2):30-40.
[10]	DING M , WANG P , LOPEZ-PEREZ Y N , et al. Performance impact of NLoS and LoS transmissions in small cell networks[J]. IEEE Transactions on Wireless Communications, 2015.
[11]	EIGEN M , SCHUSTER P . A principle of natural self-organization[J]. Naturwissenschaften, 1977,64(11):541-565.
[12]	MILLS K L . A brief survey of self-organization in wireless sensor networks[J]. Wireless Communications and Mobile Computing, 2007,7(7):823-834.
[13]	DRESSIER F . A study of self-organization mechanisms in ad hoc and sensor networks[J]. Computer Communications, 2008,31(13):3018-3029.
[14]	DOBSON S , DENAZIS S , FERN'ANDEZ A , et al. A survey of auto-nomic communications[J]. ACM Transactions Autonomous Adaptive Systems, 2006,1(2):223-259.
[15]	JORGUSESKI L , PAIS A , GUNNARSSO F , et al. Self-organizing networks in 3GPP: standardization and future trends[J]. IEEE Com-munications Magazine, 2014,52(12):28-34.
[16]	Qualcomm Incorporated(2015,July). UltraSON: Self-organizing Small Cells[EB/OL]. .
[17]	QSON(quality of service aware energy efficient self organizing future cellular networks)[EB/OL]. .
[18]	FORTES S , GARCIA A A , FERNANDEZ-LUQUE J A . Context-aware self-healing: user equipment as the main source of information for small-cell indoor networks[J]. IEEE Vehicular Technology Magazine, 2016,11(1):76-85.
[19]	KHATIB E J , BARCO R , MUNOZ P , et al. Self-healing in mobile networks with big data[J]. IEEE Communications Magazine, 2016,54(1):114-120.
[20]	GOMEZ-ANDRADES A , MUNOZ P , SERRANO I . Automatic root cause analysis for LTE networks based on unsupervised techniques[J]. IEEE Transactions on Vehicular Technology, 2016,65(4):2369-2386.
[21]	HU H , ZHANG J , ZHENG X , et al. Self-configuration and self-optimization for LTE networks[J]. IEEE Communications Magazine, 2010,48(2):94-100.
[22]	BUVANESWARI A , DRABECK L , NITHI N . Self-optimization of LTE networks utilizing celnet xplorer[J]. Bell Labs Technical Journal, 2010,15(3):99-117.
[23]	BARCO R , LAZARO P , MUNOZ P . A unified framework for self-healing in wireless networks[J]. IEEE Communications Magazine, 2012,50(12):134-142.
[24]	ALIU O G , IMRAN A , DOHLER A , et al. A survey of self organisa-tion in future cellular networks[J]. IEEE Communications Surveys ＆Tutorials, 2013,15(1):336-361.
[25]	FENG S , SEIDEL E . Self-Organizing networks (SON) in 3GPP long term evolution[EB/OL]. .
[26]	XU C , SHENG M , WANG X J . Distributed subchannel allocation for interference mitigation in OFDMA femtocells: a utility-based learning approach[J]. IEEE Transactions on Vehicular Technology, 2015,64(6):2463-2475.
[27]	BUZZI S , COLAVOLPE G , SATURNINO D . Potential games for energy-efficient power control and subcarrier allocation in uplink mul-ticell OFDMA systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2012,6(2):89-103.
[28]	LA Q D , CHEW Y H , SOONG B H . Performance analysis of downlink multi-cell OFDMA systems based on potential game[J]. IEEE Transactions on Wireless Communications, 2012,11(9):3358-3367.
[29]	ROTH A , SOTOMAYOR M A O . Two-sided matching: a study in game-theoretic modeling and analysis[M]. New York, USA: Cambridge Press, 1992.
[30]	LEE H C , OH D C , LEE Y H . Mitigation of inter-femtocell interfer-ence with adaptive fractional frequency reuse[C]// IEEE ICC'10. c2010:1-5.
[31]	LIANG Y S , CHUNG W H , NI G K . Resource allocation with inter-ference avoidance in OFDMA femtocell networks[J]. IEEE Transactions on Vehicular Technology, 2012,61(5):2243-2255.
[32]	DOCOMO N . Performance of eICIC with control channel coverage limitation[C]. 3GPP TSG RAN WG1 Meeting. c2010.
[33]	YE Q Y , RONG B Y , CHEN Y D , et al. User association for load balancing in heterogeneous cellular networks[J]. IEEE Transactions on Wireless Communications, 2013,12(6):2706-2716.
[34]	PRASAD N , ARSLAN M , RANGARAJAN S . Exploiting cell dormancy and load balancing in LTE HetNets: optimizing the proportional fairness utility[J]. IEEE Transactions on Communications, 2014,62(10):3706-3722.
[35]	SHENK M , YU W . Downlink cell association optimization for het-erogeneous networks via dual coordinate descent[C]// 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. Vancouver, Canada,IEEE, c2013:4779-4783.