Luận án tiến sĩ tiếng anh Investigations on key technologies for LTE network optimization

学校代码: 10286 分类号: 密 级: TN929.5 技术保护一年（2016 年 月 日—2017 年 月 日） U D C: 621.3 学 号: 129734 INVESTIGATIONS ON KEY TECHNOLOGIES FOR LTE NETWORK OPTIMIZATION 研究生姓名： PHAN NHU QUAN 导 师 姓 名： 潘志文 教授 申请学位类别 博士 一级学科名称 信息与通信工程 论文答辩日期 2015 年 12 月 16 日 二级学科名称 通信与信息系统 学位授予日期 20 答辩委员会主席 学位授予单位 陈明教授 评 阅 人 2015 年 12 月 25 日 东 南 大 学 年 月 日 博士学位论文 INVESTIGATIONS ON KEY TECHNOLOGIES FOR LTE NETWORK OPTIMIZATION 专 业 名 称：信息与通信工程 研究生姓名：PHAN NHU QUAN 导 师 姓 名：潘志文 ii 教授 INVESTIGATIONS ON KEY TECHNOLOGIES FOR LTE NETWORK OPTIMIZATION A Dissertation Submitted to Southeast University For the Academic Degree of Doctor of Engineering BY PHAN NHU QUAN Supervised by Prof PAN ZHI WEN School of Information Science and Engineering Southeast University Dec 2015 iv 东南大学学位论文独创性声明 ・ 本人声明所呈交的学位论文是我个人在导师指导下进行的研究工作及取得的研究成果。尽 我所知，除了文中特别加以标注和致谢的地方外，论文中不包含其他人已经发表或撰写过的研 究成果，也不包含为获得东南大学或其它教育机构的学位或证书而使用过的材料。与我一同工 作的同志对本研究所做的任何贡献均已在论文中作了明确的说明并表示了谢意。 研究生签名： 日期： 东南大学学位论文使用授权声明 东南大学、中国科学技术信息研究所、国家图书馆有权保留本人所送交学位论文的复印件 和电子文档，可以采用影印、缩印或其他复制手段保存论文。本人电子文档的内容和纸质论文 的内容相一致。除在保密期内的保密论文外，允许论文被查阅和借阅，可以公布（包括以电子 信息形式刊登）论文的全部内容或中、英文摘要等部分内容。论文的公布（包括以电子信息形 式刊登）授权东南大学研究生院办理。・ 研究生签名： 导师签名： 日期： 摘要 随着无线互联网的快速发展，无线业务量呈指数倍增长，使得服务提供商必须不断 地对无线网络覆盖进行优化，提升网络的系统容量，以满足用户的服务需求。为达到上 述目标，可以采用的主要技术方法有：修改系统参数设置、收发站开/关、根据负载状 况调整发送功率、优化小区布局、依据地形或用户密度调整天馈单元、安装大规模天线、 调整天线参数如倾角等。 本论文主要研究基站天线倾角调整算法，以实现包括网络覆盖优化、网络容量提升 和网络负载均衡在内的无线网络性能优化。 本论文主要包括以下研究内容： 第一章介绍论文的研究背景和研究意义。介绍了 LTE 网络中的自组织网络技术及 其特性，包括自配置、自优化和自愈特性。详细阐述了自优化中的网络覆盖及容量优化 (CCO)和负载均衡(LB)优化及其特征，并指出覆盖及容量优化(CCO)和负载均衡(LB)是 本文研究的关键问题。此外，还详细介绍了天线方向图和天线倾角调整的基本原理。 第二章研究 LTE 网络的覆盖问题，提出基于 eNB 天线倾角(ATA)调整的网络覆盖 优化算法。覆盖优化算法的性能指标是 eNB 覆盖的移动台 (MS)数目，该数目由 MS 测 量到的参考信号接收功率(RSRP)决定。本章通过最大化 eNB 覆盖的 MS 数目优化网络 覆盖，提出一种基于改进粒子群优化(MPSO)算法的网络覆盖优化算法。在 MPSO 中存 在一群粒子，每个粒子对应一组天线倾角集合，适应度函数由被服务的 MS 数目决定， 进化速度为每次迭代中 ATA 的调整尺度。仿真结果表明，与固定倾角相比，得益于提 出的天线倾角优化算法，基站服务的 MS 数目增加了 7.2%，接收信号质量提升 20dBm， 并且系统吞吐量也得到了 55Mbps 的有效提升。 第三章研究 eNB 负载约束及用户速率需求对网络覆盖的影响，提出考虑网络负载 约束的网络覆盖优化算法。虽然按照前一章的方法调整 ATA 能够有效提升整个网络覆 盖，但在 eNB 负载约束下，一些 eNB 过载导致一些用户的服务无法得到满足。因此， 在第三章中，提出考虑网络负载约束的网络覆盖优化算法。定义无线网络的覆盖能力为 综合考虑移动台 RSRP 和 eNB 负载约束的被服务 MS 数目，通过优化网络负载约束下 被服务的 MS 数目优化网络覆盖。提出一种基于 MPSO 的覆盖优化算法，该算法考虑 网络负载约束，通过调整 eNB 的 ATA 来最大化 eNB 服务的用户数。仿真结果表明，得 益于提出的算法，每个 eNB 服务的用户数量显著增加，系统吞吐量得到了显著提升， 并且网络平均负载和带宽效率也得到了改善。 第四章研究 LTE 网络的负载均衡问题，通过优化 eNB 的 ATA 来实现 LTE 网络的 负载均衡。以简氏公平系数作为评价网络负载均衡的标准，本章提出了基于 MPSO 算 法的负载均衡算法，通过联合优化 eNB 的 ATA 获得 LTE 网络负载均衡。仿真表明，所 i 提出的负载均衡算法可以有效实现负载均衡，显著改善了呼叫阻塞率，并且明显地增加 了网络带宽效率。 第五章研究 LTE 网络覆盖和负载均衡的联合优化问题。如果不考虑负载均衡，仅 考虑网络负载约束，优化 eNB 的 ATA 可能会出现以下情况：某信道条件较差的用户接 入负载较重的 eNB 并在该 eNB 内占用过多的资源，然而该用户附近还有一个低负载 eNB 没有得到利用。这种情况会使得网络资源无法得到有效利用，出现小区间负载不均 衡的问题。在第五章中为了在改善 eNB 覆盖的同时保证 LTE 网络负载均衡，通过联合 考虑覆盖因子 (CF)和负载均衡指标(LBI)来实现 eNB 覆盖和负载均衡的联合优化，其中 覆盖因子反映 eNB 的覆盖能力，负载均衡指标通过简氏公平系数进行评估，反应网络 负载均衡能力。将覆盖和负载均衡问题联合建模为一个多目标优化函数，提出一种基于 MPSO 的 ATA 调整方案。仿真结果表明，所提方案在有效增加网络覆盖的同时，能显 著提升负载均衡和网络带宽效率，并且网络吞吐量也得到了有效改善。 关键词：LTE 网络，网络优化，天线倾角，覆盖优化，负载均衡，改进粒子群算法。 ii ABSTRACT The exponential increase in the traffic volume forces the services providers unavoidably facing with constantly evolving the wireless network system to satisfy the user demands, such as to optimize the coverage of Evolved Node Base Station (eNB), and increase the capacity of the network By changing the system parameters, or switching on/off the base transceiver stations, or adjusting the transmission power, or suitably rearranging cell layout, or replacing antenna elements according to the topographical or the user density in urban or rural areas, or installing massive MIMO (Multiple Input Multiple Output) or adjusting the antenna parameters such as ATA are important ways to achieve the above goals In this dissertation, we investigate the adjustment of antenna tilt angle of base station to optimize the performance for LTE networks, including the coverage and capacity optimization and load balancing The main works of this dissertation are follows: In Chapter 1, the research background and research significance are introduced The selforganizing networks technologies and its features including self-configuration, selfoptimization and self-healing in LTE network are also introduced Self-optimization is detailed including its use cases such as the Coverage and Capacity Optimization (CCO), and Load Balancing (LB) optimization CCO and LB are two key issues in this study Also, the fundamental of antenna pattern and its tilt angle are introduced In Chapter 2, the coverage problem in LTE networks is investigated and a network coverage optimization algorithm based on the Antenna Tilt Angle (ATA) adjustment of the eNBs is proposed The number of Mobile Stations (MS) under the coverage of eNB is determined by the Reference Signal Received Power (RSRP) measured from MS, and is considered as the performance metrics for coverage optimization algorithm In this chapter, the network coverage is optimized by maximizing the number of MS under the coverage of eNBs and a Modified Particle Swarm Optimization (MPSO) based tilt angle adjusting algorithm for coverage optimization is proposed In MPSO, a swarm of particles known as the set of ATAs is available, the fitness function is defined as the total number of the served MSs, and the evolution velocity corresponds to the tilt angles adjustment scale for each iteration cycle Simulation results show that compared with the fixed tilt angles, the number of served MSs by base stations is significantly increased by 7.2%, the quality of received signal is considerably improved by 20 dBm, and particularly the system throughput is also effectively increased by 55 Mbps benefiting from the proposed algorithm In Chapter 3, the effect of the load constraint and the requirements of MSs is investigated, and a coverage optimization algorithm considering the load constraint of eNBs is proposed Although adjusting the ATA according to Chapter can efficiently improve the network coverage, but under the load constraint, the service requirements of some MSs might not be met because of the overload of the eNBs Therefore, the network coverage optimization iii algorithm considering the network load is proposed in Chapter The coverage ability of the wireless network is defined as the number of served MSs of eNBs considering both the RSRP measured from the MSs and the load constraint of eNBs, and the network coverage is optimized by optimizing the number of served MSs under the constraint of the network load An MPSO-based coverage optimization algorithm that adjusts the ATAs of eNBs considering the network load to maximize the number of users served by eNBs is proposed Simulation results show that both of the number of served users by each eNB and the system throughput are significantly increased As well, the average load and the bandwidth efficiency of the network are improved benefiting from the proposed algorithm In Chapter 4, we investigate the problem of load balancing optimization The load balance of the LTE network is achieved by optimizing the ATAs of the eNBs Jain’s fairness index is used to evaluate the load balance of the network An MPSO-based load balancing algorithm is proposed The load balance of the network is achieved by cooperatively optimizing the ATAs of the eNBs Simulations show that the proposed approach can efficiently improve load balancing, and significantly improves the call blocking rate, the network bandwidth efficiency In Chapter 5, the joint coverage and load balancing optimization problem is investigated Without consideration of the load balancing, adjusting the ATAs of the eNBs with the constraints of network load may result in the following problem: some users in the poor channel condition access the heavy load eNB and occupy too many resources in the eNB, however, the light load eNB nearby these users will be under used This results in load imbalance problem between eNBs Therefore, to further improve the coverage of eNB, and simultaneously guarantee the even distribution of load in the LTE networks, in Chapter 5, we jointly optimize the coverage of eNB and load balancing by considering the Coverage Factor (CF) and Load Balancing Index (LBI) The coverage factor represents the coverage ability of eNB, and load balancing is represented by load balancing index such as Jain’s fairness index We formulate the coverage and load balancing problem as a multi-objective optimization function, and an MPSO algorithm based ATAs adjusting scheme is proposed Simulation results show that our proposed algorithm can efficiently increase the network coverage This significantly improves the load balancing, and appreciably increases the network bandwidth efficiency Also, the system throughput is considerably improved benefiting from the proposed algorithm Keywords: LTE Networks, Network Optimization, Antenna Tilt Angle, Coverage Optimization, Load Balancing and Modified Particle Swarm Optimization iv Investigations on Key Technologies for LTE Network Optimization, Ph.D Thesis, Phan Nhu Quan 86 Chapter Conclusion and Future Work CHAPTER 6: CONCLUSION AND FUTURE WORK 6.1 Conclusion Important issues of CCO and LB are addressed in this thesis The overview of SON is addressed in Chapter We introduce the self-organizing networks and its features including self-configuration, self-optimization and selfhealing in LTE network Self-optimization is detailed with its characteristics such as the coverage and capacity optimization (CCO), and load balancing (LB) optimization CCO and LB are two key issues in this study Also, the fundamental of antenna pattern and its tilt angle adjusting are discussed In Chapter 2, we investigate the ATA adjusting scheme for LTE coverage optimization The number of user under covered of eNB is determined based on the reference signal received power measured from the users, and is used as the metrics for coverage optimization The tilt angles are adjusted based on MPSO The simulation results demonstrate the effectiveness and robustness of our methods It shows that the proposed methods significantly increased the number of served users under the coverage of cells; the system throughput is effectively increased benefiting from the proposed algorithm The proposed method shows that the MPSO based tilt angle adjusting is more effective than the traditional adjusting method In Chapter 3, we improve the performance of the ATA adjusting by proposing a tilt angle adjusting considering the network load By considering cell load condition, the proposed algorithm can deal with the non-convex problems by adjusting ATA under the cell load condition The simulation results show that the average network load and the system throughput both are improved benefiting from the proposed algorithm The proposed method shows that the MPSO based tilt angle adjusting considering the network load is more effective than the tilt angle adjusting only method However, the load balancing is not considered, ATA adjusting algorithm cannot perform balancing load, thus results in a lightly unbalanced load between cells In Chapter 4, we solve the problem of load balancing; the ATA is adjusted to improve load balancing By constructing an objective function in which the load balancing index is used to evaluate the level of load balancing We use the MPSObased tilt angle adjusting algorithm; the proposed approach demonstrates that the load balancing of our algorithm can efficiently achieve about This significantly improves the call blocking rate, and appreciably increases the network bandwidth efficiency Also, the average network load is considerably improved In Chapter 5, to solve the problem in Chapter and cooperative Chapter 4, the ATA adjusting jointly considering coverage factor and load balancing index to reduce the unbalanced load is considered By constructing the multi-objective function in 87 Investigations on Key Technologies for LTE Network Optimization, Ph.D Thesis, Phan Nhu Quan which the coverage factor and the load balancing index are jointly optimized, Chapter proposes a joint coverage and load balancing optimization scheme in which the coverage is represented by Coverage Factor (CF) that defined as the ratio of the served user number to the total user number in the network, and load balancing is represented by the Load Balancing Index (LBI) By using MPSO based on tilt angle adjusting, the proposed approach demonstrates the high effectiveness and efficiency with bandwidth efficiency, system throughput, load balancing index and coverage ratio 6.2 Future Work The proposed methods are verified on the datasets of tilt angles, the constraint of cell load However, the proposed methods based tilt angles are readily to be adopted for other scenarios, e.g improving performance of the heterogeneous networks by joint adjusting antenna tilt angles and the transmitting power of cell with considering the constraint of network load In this thesis, the acceleration coefficients are chosen by empirical studies, only the inertia weight can be modified, and all the proposed methods employ an ATA adjusting scheme However, in some practical applications, it may be difficult to obtain the fast convergence In the future, to increase the sensitivity or the convergence of the MPSO algorithm, acceleration parameters as the changeable parameters can be considered In this dissertation, we only consider the Down-link (DL) transmission of the LTE cellular systems But in the practical system, the down-link and up-link interference scenarios are fundamentally different We will consider both the up-link and down-link in the future works The CCO and LB are only performed in scenario for a regular hexagonal multi-cell wireless networks, universal frequency reuse, MIMO omnidirectional antenna configurations, adaptive modulation and coding technique, and multipath selective fading channel conditions The design of the custom built system level simulator, implementation of various scenarios of the LTE system will be investigated in the future work 88 Bibliography BIBLIOGRAPHY Arunabha 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2010, 3GPP TR 36.814 133 Fehske, A.J., et al., Concurrent Load-Aware Adjustment of User Association and Antenna Tilts in Self-Organizing Radio Networks IEEE Transactions on Vehicular Technology, 2013 62(5): p 1974-1988 134 P NhuQuan, B.T., J Huilin,, Coverage Optimization of LTE Networks Based on ATA Adjusting Considering Network Load Journal of China Communications, 2015 Accepted 135 3GPP TS 36.331 V9.3.0 (2010-06), Technical Specification 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal 2010 98 Publication PUBLICATION Most of the material presented in this dissertation has been published in the following publications [1] Phan NhuQuan, Jiang Huilin, Bui ThiOanh, at el “A Modified Particle Swarm Optimization Based Antenna Tilt Angle Adjusting Scheme for LTE Coverage Optimization.” Journal of Southeast University 2015, In press, to be published 2016.1 [2] Phan NhuQuan, Bui ThiOanh, Jiang Huilin, at el “Coverage Optimization of LTE Networks Based on ATA Adjusting Considering Network Load.” China Communication, 2015, accepted [3] Phan NhuQuan, Jiang Huilin, Bui ThiOanh, at el “Joint Mobility Load Balancing and Coverage Optimizing Based on Tilt Adjusting in LTE Networks.” IEEE 2nd EAI International Conference on Nature of Computation and Communication (ICTCC), RachGia, Vietnam, 2016 , submitted [4] Jiang Huilin, Tong En, Li Zhihang, Phan NhuQuan, at el “A power adjustment based eICIC algorithm for hyper-dense HetNets considering the alteration of user association.” Science China Information Sciences, 2015 58(8): p 1-15 [5] Li Pei, Jiang Huilin, Phan NhuQuan, at el “Analysis of Delay in Ultra-dense Networks with BS Sleeping and Access Control.” IEEE ICC, Malaysia, 2016, submitted [6] Wang Jijuan, Phan NhuQuan, Pan Zhiwen, Liu Nan, You Xiaohu, and Deng Tianle, “An Improved TCM-based Cell Outage Detection Scheme for SelfHealing in LTE HetNets.” IEEE VTC 2016 Spring, submitted PATENT [1] 潘志文，潘如君，蒋慧琳，刘楠，尤肖虎, “一种基于改进粒子群优化的 LTE 网络覆盖优化方法,” 申请号： 201510981422.6 99 100 [...]... network stable operation and abnormal situation In Self-configuration process, when a new base station is added to an existing network, the system automatically processes to configure a series of parameters during the installation, so that it can adapt to run in the current network environment This is the preparation stage, i.e 3 Investigations on Key Technologies for LTE Network Optimization, Ph.D Thesis,... the network work in the best condition Self -optimization includes Coverage and Capacity Optimization (CCO), Random Access Channel Optimization (RACHO), Energy Saving Optimization, Mobile Robustness Optimization (MRO) and Mobility Load Balancing Optimization (MLBO), etc Following are specific description some use cases 1.2.2.3.1 Coverage and Capacity Optimization An important task of network operation... Introduction (3) This new eNB requires own the hardware configuration, the cell type etc., information is sent to the OAM control center to authenticate certification; download from the OAM some of the necessary software and configuration data; (4) Data transmission and wireless configuration follows the base station configuration; (5) The new eNB connection to OAM control center in all areas, and contact... base station, and hence that changes in the network topology is uncertain Behavior of users on the network can also cause varying network traffic distribution Facing with so many changes, operators must optimize the network at any time to adapt for changing network conditions The main work of network optimization is cyclical operation during the stable operation of the network, through monitoring of... angle on CCO and LB have not been comprehensively investigated The aforementioned challenges give rise to a motivation to design feasible CCO and LB schemes for wireless networks The design specifications to overcome the challenges may be different from each other In this dissertation, we will highlight our recently developed schemes for CCO and LB 13 Investigations on Key Technologies for LTE Network Optimization, ... admission control for a load balancing handover 1.2.3 Base Station Antenna and ATA 1.2.3.1.Introduction Antenna parameters selection and optimization play an important role in achieving maximum capacity, coverage performance and LB in LTE and LTE- A Dipole and monopole antennas are commonly used for wireless mobile communication systems [12-16] Due to the broadband characteristics and simple construction... monitoring of multiple devices, network performance, analyzing reasons for the decline of network performance and taking necessary measures such as adjusting the parameters to make the network work in the best condition In a traditional network optimization, this work is done by manpower [10] Self -optimization means to automatically sense the changes in the surrounding environment, automatically adjust... location A mathematical model for user traffic in coverage and capacity optimization was used, including relative user density map, general definitions (such as the average number of users per pixel, the area covered by cell, the number of physical resource blocks), optimization functions based on cell-specific measures and optimization functions based on network- wide measures For the optimization objective... Time Division Duplex (TDD) and Frequency Division Duplex (FDD) both are supported by LTE Nevertheless, LTE also supports a flexible and scalable bandwidth e.g., 1.25, 5, 10 and 20MHz LTE also has a very flexible radio interface [3, 4] 1 Investigations on Key Technologies for LTE Network Optimization, Ph.D Thesis, Phan Nhu Quan In order to differentiate NodeB from Universal Mobile Telecommunication System... solutions and concepts for solving the CCO use case [33, 49] Conventional manual procedures for CCO are intricate and time consuming due to the increasing complexity of wireless cellular networks Recently, a few people have been investigating the CCO In [50], a framework about CCO optimization problem for single tier model is introduced Authors considered a pixel-based model for an LTE network consisting ...博士学位论文 INVESTIGATIONS ON KEY TECHNOLOGIES FOR LTE NETWORK OPTIMIZATION 专 业 名 称：信息与通信工程 研究生姓名：PHAN NHU QUAN 导 师 姓 名：潘志文 ii 教授 INVESTIGATIONS ON KEY TECHNOLOGIES FOR LTE NETWORK OPTIMIZATION A Dissertation... schemes for CCO and LB 13 Investigations on Key Technologies for LTE Network Optimization, Ph.D Thesis, Phan Nhu Quan The research described in this thesis focuses on CCO and LB technologies for LTE. .. blocks), optimization functions based on cell-specific measures and optimization functions based on network- wide measures For the optimization objective is a well-known non-convex function and