小区间干扰抑制的协作波束成形技术
发布时间：2018-09-08 17:03
【摘要】：4G无线通信系统和4G Beyond系统下行采用长期演进(LTE)技术,以正交频分多址(OFDMA)为接入方式,同时,为提高频谱利用率,4G系统采用了同频覆盖组网方式。这会对小区用户,特别是小区边缘用户造成非常严重的小区间干扰(ICI)。为了保证小区内所有用户享受到良好和公平的服务质量,需要一种技术来对ICI进行抑制,提高系统的整体吞吐量,并且保证用户间的公平性。小区协作波束成型技术,是无线标准中多点协作(CoMP)技术的一种。它要求基站之间共享信道状态信息(CSI)和必要信令,而并不需要共享发送的数据,具有较好性能和可实现性。所以协作波束成型技术是这一领域的研究热点。目前大部分的波束成型技术都采用中心式的方案,需要基站间高度的同步和信息交互,难以实施。而且目前现有的技术很少考虑CSI误差对系统性能造成的影响,在实际的场景中会有很严重的性能损失,使用户陷入中断。为此,减小波束成型算法开销、提升算法的鲁棒性是国内外近期无线通信领域两个个重要的研究方向。论文围绕波束成型算法和小区协作机制开展了理论分析研究与计算机仿真实验,具体工作如下:(1)针对减小系统开销和信息交互的需求,本文提出了理想信道模型下的分布式的信干噪比动态惩罚算法(Distributed Dynamic SINR Pricing Algorithm,DDSPA)。该算法要求每个基站根据非本小区用户的SINR条件以有限的信息交互设计SINR惩罚项,用来限制本基站对这些用户的干扰,在保证小区用户SINR的情况下优化基站的发送功率。仿真结果显示,DDSPA以较快的速度逼近已有的最优性能。算法以迭代的方式进行,本文分析了迭代收敛的概率和一次迭代需要的信息交互量。(2)针对减小系统开销和提升鲁棒性两点需求,本文进一步提出了基于博弈论的鲁棒性算法。为了实现分布式,这种算法要求基站之间不作任何信息交互,用户估计自身受到的小区间干扰上报基站,进行小区内单独优化。为了实现算法的鲁棒性,算法考虑了CSI估计误差模型和延时误差模型,以用户平均最小均方误差(Average Minimun Square Error,AMSE)为优化目标。仿真显示,算法能够有效地抑制CSI误差对系统性能的影响。文章也分析了算法收敛概率和收敛速度。(3)为了进一步提升系统性能,减小开销,提高工程可实现性,本文提出了一种闭式的的鲁棒性算法,在发送功率约束下最小化AMSE和。算法采用采用KKT条件解决优化问题,能够达到最优性能。问题的解为闭式形式,而且无需迭代,系统开销少。算法也设计了基站间的协作方式,在TDD制式下能够以分布式的方式实施,X2接口中仅需要交互信令。仿真结果显示,算法能够进一步提高系统性能,并且具有鲁棒性。
[Abstract]:4G wireless communication system and 4G Beyond system adopt long-term evolution (LTE) technology, take orthogonal frequency division multiple access (OFDMA) as access mode, at the same time, in order to improve spectrum efficiency and 4G system, the same frequency coverage network is adopted. This can cause very serious cell interference (ICI). For cell users, especially for cell edge users. In order to ensure that all users in the cell enjoy good and fair quality of service, a technology is needed to suppress the ICI, improve the overall throughput of the system, and ensure the fairness between users. Cell cooperative beamforming is a multi-point cooperative (CoMP) technology in wireless standard. It requires the sharing of channel state information (CSI) and necessary signaling between the base stations, without the need to share the transmitted data, so it has better performance and realizability. Therefore, cooperative beamforming technology is a research hotspot in this field. At present, most of the beamforming technologies adopt the central scheme, which requires high synchronization and information exchange between the base stations, so it is difficult to implement. At present, the existing techniques seldom consider the impact of CSI error on system performance, and there will be a serious performance loss in the actual scenario, causing the user to fall into interruption. Therefore, reducing the overhead of beamforming algorithm and improving the robustness of the algorithm are two important research directions in the field of wireless communication at home and abroad. This paper focuses on beamforming algorithm and cell collaboration mechanism, and carries out theoretical analysis and computer simulation experiments. The main work is as follows: (1) to reduce system overhead and information interaction, In this paper, a distributed SINR dynamic penalty algorithm (Distributed Dynamic SINR Pricing Algorithm,DDSPA) based on ideal channel model is proposed. The algorithm requires each base station to design a SINR penalty term with limited information interaction according to the SINR conditions of non-cell users, which is used to limit the interference of the base station to these users and optimize the transmission power of the base station under the condition of guaranteeing the SINR of the cell users. Simulation results show that DDSPA approaches the existing optimal performance at a faster speed. The algorithm is carried out iteratively. In this paper, the probability of iterative convergence and the amount of information interaction required by one iteration are analyzed. (2) for the two requirements of reducing system overhead and improving robustness, a robust algorithm based on game theory is proposed. In order to achieve distribution, the algorithm requires that the base stations do not interact with each other, and the users estimate their own inter-cell interference and report it to the base station for individual optimization in the cell. In order to realize the robustness of the algorithm, the CSI estimation error model and the delay error model are considered, and the user average minimum mean square error (Average Minimun Square Error,AMSE) is taken as the optimization objective. Simulation results show that the algorithm can effectively suppress the effect of CSI error on system performance. This paper also analyzes the convergence probability and convergence speed of the algorithm. (3) in order to further improve the system performance, reduce the overhead and improve the engineering realizability, a closed robust algorithm is proposed to minimize the AMSE sum under transmission power constraints. The KKT condition is used to solve the optimization problem and the optimal performance can be achieved. The solution of the problem is closed form, and without iteration, the system cost is less. The algorithm also designs the mode of cooperation between base stations. Only interactive signaling is needed to implement the X2 interface in a distributed manner under the TDD system. Simulation results show that the algorithm can further improve the system performance and has robustness.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5
[Abstract]:4G wireless communication system and 4G Beyond system adopt long-term evolution (LTE) technology, take orthogonal frequency division multiple access (OFDMA) as access mode, at the same time, in order to improve spectrum efficiency and 4G system, the same frequency coverage network is adopted. This can cause very serious cell interference (ICI). For cell users, especially for cell edge users. In order to ensure that all users in the cell enjoy good and fair quality of service, a technology is needed to suppress the ICI, improve the overall throughput of the system, and ensure the fairness between users. Cell cooperative beamforming is a multi-point cooperative (CoMP) technology in wireless standard. It requires the sharing of channel state information (CSI) and necessary signaling between the base stations, without the need to share the transmitted data, so it has better performance and realizability. Therefore, cooperative beamforming technology is a research hotspot in this field. At present, most of the beamforming technologies adopt the central scheme, which requires high synchronization and information exchange between the base stations, so it is difficult to implement. At present, the existing techniques seldom consider the impact of CSI error on system performance, and there will be a serious performance loss in the actual scenario, causing the user to fall into interruption. Therefore, reducing the overhead of beamforming algorithm and improving the robustness of the algorithm are two important research directions in the field of wireless communication at home and abroad. This paper focuses on beamforming algorithm and cell collaboration mechanism, and carries out theoretical analysis and computer simulation experiments. The main work is as follows: (1) to reduce system overhead and information interaction, In this paper, a distributed SINR dynamic penalty algorithm (Distributed Dynamic SINR Pricing Algorithm,DDSPA) based on ideal channel model is proposed. The algorithm requires each base station to design a SINR penalty term with limited information interaction according to the SINR conditions of non-cell users, which is used to limit the interference of the base station to these users and optimize the transmission power of the base station under the condition of guaranteeing the SINR of the cell users. Simulation results show that DDSPA approaches the existing optimal performance at a faster speed. The algorithm is carried out iteratively. In this paper, the probability of iterative convergence and the amount of information interaction required by one iteration are analyzed. (2) for the two requirements of reducing system overhead and improving robustness, a robust algorithm based on game theory is proposed. In order to achieve distribution, the algorithm requires that the base stations do not interact with each other, and the users estimate their own inter-cell interference and report it to the base station for individual optimization in the cell. In order to realize the robustness of the algorithm, the CSI estimation error model and the delay error model are considered, and the user average minimum mean square error (Average Minimun Square Error,AMSE) is taken as the optimization objective. Simulation results show that the algorithm can effectively suppress the effect of CSI error on system performance. This paper also analyzes the convergence probability and convergence speed of the algorithm. (3) in order to further improve the system performance, reduce the overhead and improve the engineering realizability, a closed robust algorithm is proposed to minimize the AMSE sum under transmission power constraints. The KKT condition is used to solve the optimization problem and the optimal performance can be achieved. The solution of the problem is closed form, and without iteration, the system cost is less. The algorithm also designs the mode of cooperation between base stations. Only interactive signaling is needed to implement the X2 interface in a distributed manner under the TDD system. Simulation results show that the algorithm can further improve the system performance and has robustness.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5
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