异构无线网络中基于多网协同优化的资源管理技术研究
|
摘要
在无线移动通信高速化、泛在化的进程中,人们为不同的通信环境和用户需求研究、开发、部署了多种类型的无线通信系统。当前,多种异构网络已广泛部署,2G通信系统已经成熟,3G网络初具规模,并正向着4G网络不断演进,另外以IEEE802.11为代表的无线局域网(WLAN)技术,以其鲜明的技术特征和清晰的市场定位获得了巨大成功。
从当前无线通信的现状来看,2G网络用户基数大负担较重,3G和WLAN网络建设初具规模但用户少,利用效率低,LTE正在加紧部署,未来一段时间的用户基数和利用效率也较低。考虑到多种异构网络的业务承载能力存在差异性,进行多种异构网络间的协同优化,通过有效地协同异构网络资源,可以降低2G网络负担,提高3G和WLAN网络资源利用效率。对此,本文将结合现网从以下几个方面研究基于多网协同优化的资源管理技术：
首先,多网协同应该做好各单一网络的优化,其中包括2G优化和3G优化。2G优化主要包括基于PCC的无线资源调控和自组织网络技术,3G优化主要考虑覆盖优化和网络容量提升。特别的,针对目前运营商没有有效的3G容量规划方法,本文研究了基于随机背包优化算法的载频级容量规划新方案。基于某运营商现网,本文第二部分重点探讨了针对2G、3G、WLAN和LTE异构环境下的四网协同优化方案,并落地实施。另外,结合实际网络运营中的典型场景,如WLAN与2G的无缝互操作和高铁通信场景,本文针对典型场景的特殊需求研究多网协同下有效的资源管理方案,并进行了可行性分析和验证。最后,对全文进行了概括和总结,指出方案需要进一步改善的地方和今后的研究方向。
With the growing demand of high speed and ubiquitous trend in mobile communication, multiple types of wireless telecommunication systems have been extensively researched, developed and deployed for different communication scenarios and various user requirements. Nowadays, several heterogeneous networks have been applied.3G network is starting to bloom, and evolving to4G network deployment while2G telecommunication system is already well-established. On the other hand, WLAN technology represented by IEEE802.11is proved to be a major success due to its distinctive technical features and definite market orientation.
Inspecting the current situation in mobile communication network,2G network is undertaking heavy load due to the large base of subscribers while3G and WLAN are just at the stage of their blooming development with much less subscribers and low utilization. The deployment of LTE is speeding up, however, it will face similar load and utility situation with3G network in the near future. Considering the complementarity of different networks for different services, effective and cooperative resource management technology can reduce the burden of2G network and enhance the utilization of3G and WLAN network. This thesis addresses the task of resource management based on multi-network cooperative optimization from the following aspects.
First, the optimization of single network including2G and3G is crucial. The Optimization of2G network can be realized through the joint effort of radio resource management and technology of self-organizing networks. Coverage optimization and network throughput enhancement are concerned in the optimization of3G network. In this thesis a carrier frequency level capacity planning scheme based on improved stochastic knapsack is proposed to cope with mobile operator's lack of effective3G network planning tool. Furthermore, the network cooperation and optimization scheme under heterogeneous network environment consisting of2G,3G, WLAN and LTE is studied and deployed. Additionally, practical network operation consists of many typical scenarios such as the seamless interoperability between2G and3G networks, high-speed communication scenario. This thesis analyzes in detail the effective scheme for resource management in these special scenarios and provides feasibility analysis and validation. Finally, the conclusion of this thesis is presented; the further improvement of current scheme and the future research work are pointed out.
从当前无线通信的现状来看,2G网络用户基数大负担较重,3G和WLAN网络建设初具规模但用户少,利用效率低,LTE正在加紧部署,未来一段时间的用户基数和利用效率也较低。考虑到多种异构网络的业务承载能力存在差异性,进行多种异构网络间的协同优化,通过有效地协同异构网络资源,可以降低2G网络负担,提高3G和WLAN网络资源利用效率。对此,本文将结合现网从以下几个方面研究基于多网协同优化的资源管理技术：
首先,多网协同应该做好各单一网络的优化,其中包括2G优化和3G优化。2G优化主要包括基于PCC的无线资源调控和自组织网络技术,3G优化主要考虑覆盖优化和网络容量提升。特别的,针对目前运营商没有有效的3G容量规划方法,本文研究了基于随机背包优化算法的载频级容量规划新方案。基于某运营商现网,本文第二部分重点探讨了针对2G、3G、WLAN和LTE异构环境下的四网协同优化方案,并落地实施。另外,结合实际网络运营中的典型场景,如WLAN与2G的无缝互操作和高铁通信场景,本文针对典型场景的特殊需求研究多网协同下有效的资源管理方案,并进行了可行性分析和验证。最后,对全文进行了概括和总结,指出方案需要进一步改善的地方和今后的研究方向。
With the growing demand of high speed and ubiquitous trend in mobile communication, multiple types of wireless telecommunication systems have been extensively researched, developed and deployed for different communication scenarios and various user requirements. Nowadays, several heterogeneous networks have been applied.3G network is starting to bloom, and evolving to4G network deployment while2G telecommunication system is already well-established. On the other hand, WLAN technology represented by IEEE802.11is proved to be a major success due to its distinctive technical features and definite market orientation.
Inspecting the current situation in mobile communication network,2G network is undertaking heavy load due to the large base of subscribers while3G and WLAN are just at the stage of their blooming development with much less subscribers and low utilization. The deployment of LTE is speeding up, however, it will face similar load and utility situation with3G network in the near future. Considering the complementarity of different networks for different services, effective and cooperative resource management technology can reduce the burden of2G network and enhance the utilization of3G and WLAN network. This thesis addresses the task of resource management based on multi-network cooperative optimization from the following aspects.
First, the optimization of single network including2G and3G is crucial. The Optimization of2G network can be realized through the joint effort of radio resource management and technology of self-organizing networks. Coverage optimization and network throughput enhancement are concerned in the optimization of3G network. In this thesis a carrier frequency level capacity planning scheme based on improved stochastic knapsack is proposed to cope with mobile operator's lack of effective3G network planning tool. Furthermore, the network cooperation and optimization scheme under heterogeneous network environment consisting of2G,3G, WLAN and LTE is studied and deployed. Additionally, practical network operation consists of many typical scenarios such as the seamless interoperability between2G and3G networks, high-speed communication scenario. This thesis analyzes in detail the effective scheme for resource management in these special scenarios and provides feasibility analysis and validation. Finally, the conclusion of this thesis is presented; the further improvement of current scheme and the future research work are pointed out.
引文
[1]张永靖,端到端可重配置系统中的联合无线资源管理研究,[博士学位论文],北京邮电大学,2007
[2]冯志勇,张平等著.认知无线网络理论与关键技术,第一版,北京：人民邮电出版社,2011,1-25.
[3]http://baike.baidu.com/view/930948.htm
[4]乌云霄,王蕴实,吕召彪.LTE/HSPA SON关键技术研究.全国无线及移动通信学术大会.2011
[5]3GPP TS 36.300. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access Network (E-UTRAN), overall description,2010
[6]3GPP TS 36.331. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN), overall description,2010
[7]3GPP TR 36.902. Evolved universal terrestrial radio access network (E-UTRAN), self-onfiguring and self-optimizing network (SON) use cases and solutions,2010
[8]罗建迪,汪丁鼎,肖清华,et al. TD-SCDMA无线网络规划设计与优化.第三版,北京,人民邮电出版社,2010.
[9]刘莉,荆涛,付立,et al.一种CDMA网络多业务的呼叫语序控制算法.电子信息学报,30(6)2008,1466-1469.
[10]Gupta, A., Krishnaswamy, R., Molinaro, M., et al. Approximation Algorithms for Correlated Knapsacks and Non-martingale Bandits. Foundations of Computer Science (FOCS), California, USA,2011,827-836.
[11]Singh, R.P.. Solving 0-1 Knapsack problem using Genetic Algorithms. Communication Software and Networks (ICCSN), Zhengzhou, China, June 2-3,2011,591-595.
[12]Kosuch, S., Lisser, A. On two-stage stochastic knapsack problems,8th Cologne/Twente Workshop on Graphs and Combinatorial Optimization, Conservatoire Nat1 Arts Metiers (CNAM), Paris, FRANCE,159(16),2009,1827-1841.
[13]Dean, B.C., Goemans, M.X., Vondrdk, J.. Approximating the stochastic knapsack problem: the benefit of adaptivity, Foundations of Computer Science,2004,208-217.
[14]Sarangan, V., Ghosh, D., Gautam, N.. Steady state distribution for stochastic knapsack with bursty arrivals, Communications Letters, IEEE,2005,9(2):189-189.
[15]Gavious, A., Rosberg, Z.. A restricted complete sharing policy for a stochastic knapsack problem in B-ISDN, Communications, IEEE Transactions,1994,42(7):2375-2379.
[16]Liang Lei, Aiping Huang, Cunqing Hua. Analysis of uplink capacity in TD-SCDMA systems supporting multiclass services, Communication Technology (ICCT),2010 12th IEEE International Conference, Nanjing, China,2010,607-611.
[17]Luo Bin-de, Shi Zhi-yong, Ma Da-wei. Design and Capacity Analysis of PoC Service Based on TD-SCDMA Network. Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, China, Sep.22-25,2010,1-4.
[18]罗建迪,单刚,朱东照.TD-SCDMA系统混合业务容量估算.无线通信,2007,X(12)：42-45.
[19]姚雅倩,丁长林.浅析高铁通信系统专利的现状和发展趋势.铁道通信信号.第48卷第1期.2012年1月.
[20]Karimi, O.B. Jiangchuan Liu; Chonggang Wang. Seamless Wireless Connectivity for Multimedia Services in High Speed Trains. IEEE Journal on selected Areas in Communications,2012,30(4),729-739
[21]TD-LTE引入策略》
[22]ITU-T G.114
[23]华为技术有限公司,GSM无线网络规划与优化,人民邮电出版社,2007
[24]Buddhikot M., ChandranmenonG., HanS, etal, Integration of 802.11 and Third-Generation Wireless Data Networks. Proeeeding of INFOCOM'03, Apr.2003.
[25]罗强,张平.B3G网络联合无线资源管理的研究.电信科学,2006年第6期,PP：42-37.
[26]黎文边,林粤伟,王小猛.认知无线网络中基于微观经济学的动态频谱管理算法.电子与信息学报,31(4).2009.897-902
[27]E3 Deliverables D5.1 "Overview of Support for Heterogeneous Standards Research Approaches and Plans", May 2008
[28]E3 Deliverables D3.1, "Requirements for Collaborative Cognitive RRM", July 2008
[2]冯志勇,张平等著.认知无线网络理论与关键技术,第一版,北京：人民邮电出版社,2011,1-25.
[3]http://baike.baidu.com/view/930948.htm
[4]乌云霄,王蕴实,吕召彪.LTE/HSPA SON关键技术研究.全国无线及移动通信学术大会.2011
[5]3GPP TS 36.300. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access Network (E-UTRAN), overall description,2010
[6]3GPP TS 36.331. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN), overall description,2010
[7]3GPP TR 36.902. Evolved universal terrestrial radio access network (E-UTRAN), self-onfiguring and self-optimizing network (SON) use cases and solutions,2010
[8]罗建迪,汪丁鼎,肖清华,et al. TD-SCDMA无线网络规划设计与优化.第三版,北京,人民邮电出版社,2010.
[9]刘莉,荆涛,付立,et al.一种CDMA网络多业务的呼叫语序控制算法.电子信息学报,30(6)2008,1466-1469.
[10]Gupta, A., Krishnaswamy, R., Molinaro, M., et al. Approximation Algorithms for Correlated Knapsacks and Non-martingale Bandits. Foundations of Computer Science (FOCS), California, USA,2011,827-836.
[11]Singh, R.P.. Solving 0-1 Knapsack problem using Genetic Algorithms. Communication Software and Networks (ICCSN), Zhengzhou, China, June 2-3,2011,591-595.
[12]Kosuch, S., Lisser, A. On two-stage stochastic knapsack problems,8th Cologne/Twente Workshop on Graphs and Combinatorial Optimization, Conservatoire Nat1 Arts Metiers (CNAM), Paris, FRANCE,159(16),2009,1827-1841.
[13]Dean, B.C., Goemans, M.X., Vondrdk, J.. Approximating the stochastic knapsack problem: the benefit of adaptivity, Foundations of Computer Science,2004,208-217.
[14]Sarangan, V., Ghosh, D., Gautam, N.. Steady state distribution for stochastic knapsack with bursty arrivals, Communications Letters, IEEE,2005,9(2):189-189.
[15]Gavious, A., Rosberg, Z.. A restricted complete sharing policy for a stochastic knapsack problem in B-ISDN, Communications, IEEE Transactions,1994,42(7):2375-2379.
[16]Liang Lei, Aiping Huang, Cunqing Hua. Analysis of uplink capacity in TD-SCDMA systems supporting multiclass services, Communication Technology (ICCT),2010 12th IEEE International Conference, Nanjing, China,2010,607-611.
[17]Luo Bin-de, Shi Zhi-yong, Ma Da-wei. Design and Capacity Analysis of PoC Service Based on TD-SCDMA Network. Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, China, Sep.22-25,2010,1-4.
[18]罗建迪,单刚,朱东照.TD-SCDMA系统混合业务容量估算.无线通信,2007,X(12)：42-45.
[19]姚雅倩,丁长林.浅析高铁通信系统专利的现状和发展趋势.铁道通信信号.第48卷第1期.2012年1月.
[20]Karimi, O.B. Jiangchuan Liu; Chonggang Wang. Seamless Wireless Connectivity for Multimedia Services in High Speed Trains. IEEE Journal on selected Areas in Communications,2012,30(4),729-739
[21]TD-LTE引入策略》
[22]ITU-T G.114
[23]华为技术有限公司,GSM无线网络规划与优化,人民邮电出版社,2007
[24]Buddhikot M., ChandranmenonG., HanS, etal, Integration of 802.11 and Third-Generation Wireless Data Networks. Proeeeding of INFOCOM'03, Apr.2003.
[25]罗强,张平.B3G网络联合无线资源管理的研究.电信科学,2006年第6期,PP：42-37.
[26]黎文边,林粤伟,王小猛.认知无线网络中基于微观经济学的动态频谱管理算法.电子与信息学报,31(4).2009.897-902
[27]E3 Deliverables D5.1 "Overview of Support for Heterogeneous Standards Research Approaches and Plans", May 2008
[28]E3 Deliverables D3.1, "Requirements for Collaborative Cognitive RRM", July 2008