MIMO有限反馈及多基站协作系统相关技术研究
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摘要
未来移动通信系统须要支持每秒百兆甚至千兆以上的传输速率,在无线频谱资源日趋紧张的情况下,需要深入探讨并拓展应用MIMO传输技术,充分挖掘利用空间维度的无线资源,提高频谱利用率,改善小区边缘用户的性能。
MIMO技术是公认的下一代移动通信系统的关键技术,而MIMO系统中的有限反馈技术对于发送端获得信道信息,发送端的预编码及功率分配方案有着重要的作用。而多基站协作技术对提高频谱利用率,改善小区边缘的性能,满足未来无线移动通信的传输速率和频谱效率要求,具有重要的意义。
本论文重点研究了与MIMO系统的有限反馈技术和多基站协作MIMO系统相关的几方面问题：单基站和多基站协作MIMO系统有限反馈性能的分析,单基站和多基站协作MIMO统的用户调度,多基站协作系统反馈方案设计,多基站协作系统中天线选择和基站选择等。论文工作的创新点主要体现在以下几方面：
1)针对Nakagami-m衰落信道下,多个发送天线单个接收天线(MISO)系统,分析了采用随机向量量化有限反馈波束成形时系统的性能,推导出了平均比特错误概率和中断概率的闭式解,并将得到的结果扩展到基于接收天线选择的MIMO系统。通过对闭式解的进一步分析,揭示了各系统参数与系统性能之间的联系,为实际系统应用提供了理论依据。
2)针对多基站协作波束成形系统,分析了有限反馈对系统吞吐量的影响,在各协作小区内只有一个活动用户和多个活动用户两种情况下,推导了吞吐量损耗的上限。经分析获得了吞吐量损耗的上限值与反馈bit数之间的关系式。在每个小区多个用户情况下,设计了一种最优的用户反馈比特分配方案,当用户总反馈比特数固定时,通过最优反馈方案可使吞吐量损耗的上限值最小。
3)针对基于有限反馈的MIMO下行多用户系统,分别对单基站和多基站协作两种情况提出了适合系统特点的调度算法。在单基站系统中,算法以系统吞吐量的下限为目标函数,通过最大化吞吐量下限的办法选择用户,使系统获得多用户分集增益,从而增加了系统吞吐量。在多基站协作调度系统中,提出了一种基于机会SDMA的用户调度算法。算法中每个基站采用正交随机向量作为波束成形向量,参与协作的各基站间通过高速链路共享波束成形信息。在接收端计算每个用户的SINR,发送端选择SINR最大的用户作为调度用户。采用该算法进行用户选择时,不需要考虑干扰小区的用户选择结果,很好的解决了多基站协作调度的困难,并获得了系统容量的增益。
4)针对基站协作系统的特点,提出了一种基于误差修正的有限量化反馈方案。方案将信道向量量化过程分为与协作基站数相等的若干步骤,每一步量化均对前一步的量化误差进行修正。该方案在复杂度和系统性能方面获得了很好的折中,适用于多基站联合处理的基站协作系统。
5)根据多基站协作系统的特点,对多基站协作系统中应用天线选择技术的两种方式：分布天线选择和基站选择进行了研究。针对多基站天线选择提出了三种天线选择算法：最优基站天线选择算法(OAS, Optimal Antenna Seletction),基于协作基站总体信道矩阵范数的天线选择算法(ACFAS, Aggregate Channel Frobenius Norm Antenna Seletction)和基于每个协作基站信道矩阵范数的天线选择算法(ICFAS, Individual Channel Frobenius Norm Antenna Seletction)。 OAS算法,是一种穷举性能最优的算法,ACFAS算法和ICFAS算法是两种次优的低复杂度算法。其中ACFAS算法以全部协作基站与用户的整体信道矩阵的Frobenius范数为天线选择的目标函数,而ICFAS算法则以参与协作的每个基站与用户的信道矩阵的Frobenius范数为天线选择的目标函数。针对多基站协作系统中的基站选择,提出了一种综合考虑基站选择和用户调度的基站、用户联合的选择算法。该算法以系统容量最大化为目标,在用户端和基站端分步骤进行基站和用户的联合选择,同时在用户端加入了波束选择,从而达到系统性能的最优化。
In the future, mobile communication system will have to support transmission rates up to several Mbps and even tens of Mbps. In the situation where the spectrum resource is gradually limited, it is necessary to make a deep discussion on MIMO and to extend the application of it. In this way, the degree of freedom in the space domain can be exploited and utilized, and thus the spectrum efficiency can be increased, as well as the performance at the edge of cells.
MIMO is the universally acknowledged key technique for the next generation mobile communication system. The limited feedback technique is essentially important for obtaining the channel state information at the transmitter side, pre-coding at the transmitter and determining the power allocation strategy. While the multi base-station cooperation technique is meaningful for increasing the spectrum efficiency, improving the performances at the cell edge and satisfying the requirement of transmission rate and spectrum efficiency for future wireless mobile communication system.
This paper focuses on the issues related to limited feedback techniques in MIMO system and coordinated MIMO across multi base-stations, including: performance analysis of limited feedback for single base-station MIMO, performance analysis of limited feedback for multi base-station coordinated MIMO, user scheduling for both single base-station MIMO and multi base-station coordinated MIMO, design of limited feedback for multi base-station system, and the antenna selection and base-station selection in multi base-station coordinated system. The contributions of this paper are presented as follows:
1) Based on the Nakagami-m fading channel model, the performance of a beam-forming system in a MISO scenario, where the random vector quantization is employed for limited feedback, is analyzed. The closed-form expressions for average BER and outage capacity are derived. The corresponding results are further extended to support multi-antenna-selection based MIMO system. Besides, relations between system parameters and system performance are revealed by further studying the closed-form solution, which provide theoretical basis for practical system application.
2) For the multi base-station coordinated beam-forming system, the impact of limited feedback on the system capacity is analyzed. The upper bound of throughput loss is derived for the situations where there is either one active user or multi active users. Based on the theoretical analysis, the relation between the upper bound of throughput loss and the number of feedback bits is obtained. In this instance that there are multi users for each cell, an optimum strategy is designed for the allocation of feedback bits across multi cells, with which, the minimum upper bound of throughput loss can be achieved for the given number of user feedback bits.
3) For the downlink transmission in a limited-feedback based multi-user MIMO system, scheduling algorithms are proposed respectively for the single base-station and the multi base-station coordination. In the single base-station, users are selected by maximizing the lower bound of capacity, which is therefore employed as the target function of the proposed method. Using this method, multi user diversity gain can be achieved and thereby the system capacity is increased. In the multi base-station coordination system, an opportunistic SDMA algorithm is proposed for the user scheduling. In this algorithm, each base-station adopts an orthogonal random vector as the beam-forming vector, and the information of beam-forming is shared across based-stations involved in the coordination via high speed link. The SINR is calculated in the receiver for each user, and the user with the highest SINR will be scheduled by the transmitter. By using this algorithm, user selection does not need to consider the user selection results of interfering cells, which well resolves the difficulty of multi base-station coordination and obtains system capacity gain in addition.
4) Considering the characteristic of a multi based-station coordination system, a strategy for the limited quantization feedback is proposed, which is based on error revising technique. In this strategy, the channel quantization procedure is divided into several steps, the number of which is equal to the number of base-stations involved in the coordination. The quantization error of the last step will be revised in the current step. This method can achieve a good trade-off between complexity and system performances, and suitable for base-station coordination system with multi base-station joint processing mechanism.
5) Based on the characteristics of multi base-station coordination system, the antenna selection techniques are studied, which includes distributed antenna selection and base-station selection. Three antenna selection algorithms are proposed for the selection of multi base-station antennas:the Optimal Antenna Selection (OAS), the Aggregate Channel Frobenius Norm Antenna Selection (ACFAS), and the Individual Channel Frobenius Norm Antenna Selection (ICFAS). The OAS algorithm employs a exhaustive searching based strategy, and the ACFAS and the ICFAS are two suboptimal algorithms with lower complexity. The ACFAS method adopts the Frobenius norm of the aggregate channel matrix between the user and all the base-stations involved in the coordination as the antenna selection of target function, while the ICFAS algorithm adopts the Frobenius norm of the channel matrix between the user and each single base-station involved in the coordination as the target function. Considering both the base-station selection and user scheduling, a joint algorithm for selecting base-station and user is proposed, which aims to maximize the system capacity. Following a couple of steps, the base-station and user are selected jointly at both the user-end and the base-station end. Meanwhile, the beam selection is also adopted at the user-end. Therefore, the optimal system performance can be achieved.
MIMO技术是公认的下一代移动通信系统的关键技术,而MIMO系统中的有限反馈技术对于发送端获得信道信息,发送端的预编码及功率分配方案有着重要的作用。而多基站协作技术对提高频谱利用率,改善小区边缘的性能,满足未来无线移动通信的传输速率和频谱效率要求,具有重要的意义。
本论文重点研究了与MIMO系统的有限反馈技术和多基站协作MIMO系统相关的几方面问题：单基站和多基站协作MIMO系统有限反馈性能的分析,单基站和多基站协作MIMO统的用户调度,多基站协作系统反馈方案设计,多基站协作系统中天线选择和基站选择等。论文工作的创新点主要体现在以下几方面：
1)针对Nakagami-m衰落信道下,多个发送天线单个接收天线(MISO)系统,分析了采用随机向量量化有限反馈波束成形时系统的性能,推导出了平均比特错误概率和中断概率的闭式解,并将得到的结果扩展到基于接收天线选择的MIMO系统。通过对闭式解的进一步分析,揭示了各系统参数与系统性能之间的联系,为实际系统应用提供了理论依据。
2)针对多基站协作波束成形系统,分析了有限反馈对系统吞吐量的影响,在各协作小区内只有一个活动用户和多个活动用户两种情况下,推导了吞吐量损耗的上限。经分析获得了吞吐量损耗的上限值与反馈bit数之间的关系式。在每个小区多个用户情况下,设计了一种最优的用户反馈比特分配方案,当用户总反馈比特数固定时,通过最优反馈方案可使吞吐量损耗的上限值最小。
3)针对基于有限反馈的MIMO下行多用户系统,分别对单基站和多基站协作两种情况提出了适合系统特点的调度算法。在单基站系统中,算法以系统吞吐量的下限为目标函数,通过最大化吞吐量下限的办法选择用户,使系统获得多用户分集增益,从而增加了系统吞吐量。在多基站协作调度系统中,提出了一种基于机会SDMA的用户调度算法。算法中每个基站采用正交随机向量作为波束成形向量,参与协作的各基站间通过高速链路共享波束成形信息。在接收端计算每个用户的SINR,发送端选择SINR最大的用户作为调度用户。采用该算法进行用户选择时,不需要考虑干扰小区的用户选择结果,很好的解决了多基站协作调度的困难,并获得了系统容量的增益。
4)针对基站协作系统的特点,提出了一种基于误差修正的有限量化反馈方案。方案将信道向量量化过程分为与协作基站数相等的若干步骤,每一步量化均对前一步的量化误差进行修正。该方案在复杂度和系统性能方面获得了很好的折中,适用于多基站联合处理的基站协作系统。
5)根据多基站协作系统的特点,对多基站协作系统中应用天线选择技术的两种方式：分布天线选择和基站选择进行了研究。针对多基站天线选择提出了三种天线选择算法：最优基站天线选择算法(OAS, Optimal Antenna Seletction),基于协作基站总体信道矩阵范数的天线选择算法(ACFAS, Aggregate Channel Frobenius Norm Antenna Seletction)和基于每个协作基站信道矩阵范数的天线选择算法(ICFAS, Individual Channel Frobenius Norm Antenna Seletction)。 OAS算法,是一种穷举性能最优的算法,ACFAS算法和ICFAS算法是两种次优的低复杂度算法。其中ACFAS算法以全部协作基站与用户的整体信道矩阵的Frobenius范数为天线选择的目标函数,而ICFAS算法则以参与协作的每个基站与用户的信道矩阵的Frobenius范数为天线选择的目标函数。针对多基站协作系统中的基站选择,提出了一种综合考虑基站选择和用户调度的基站、用户联合的选择算法。该算法以系统容量最大化为目标,在用户端和基站端分步骤进行基站和用户的联合选择,同时在用户端加入了波束选择,从而达到系统性能的最优化。
In the future, mobile communication system will have to support transmission rates up to several Mbps and even tens of Mbps. In the situation where the spectrum resource is gradually limited, it is necessary to make a deep discussion on MIMO and to extend the application of it. In this way, the degree of freedom in the space domain can be exploited and utilized, and thus the spectrum efficiency can be increased, as well as the performance at the edge of cells.
MIMO is the universally acknowledged key technique for the next generation mobile communication system. The limited feedback technique is essentially important for obtaining the channel state information at the transmitter side, pre-coding at the transmitter and determining the power allocation strategy. While the multi base-station cooperation technique is meaningful for increasing the spectrum efficiency, improving the performances at the cell edge and satisfying the requirement of transmission rate and spectrum efficiency for future wireless mobile communication system.
This paper focuses on the issues related to limited feedback techniques in MIMO system and coordinated MIMO across multi base-stations, including: performance analysis of limited feedback for single base-station MIMO, performance analysis of limited feedback for multi base-station coordinated MIMO, user scheduling for both single base-station MIMO and multi base-station coordinated MIMO, design of limited feedback for multi base-station system, and the antenna selection and base-station selection in multi base-station coordinated system. The contributions of this paper are presented as follows:
1) Based on the Nakagami-m fading channel model, the performance of a beam-forming system in a MISO scenario, where the random vector quantization is employed for limited feedback, is analyzed. The closed-form expressions for average BER and outage capacity are derived. The corresponding results are further extended to support multi-antenna-selection based MIMO system. Besides, relations between system parameters and system performance are revealed by further studying the closed-form solution, which provide theoretical basis for practical system application.
2) For the multi base-station coordinated beam-forming system, the impact of limited feedback on the system capacity is analyzed. The upper bound of throughput loss is derived for the situations where there is either one active user or multi active users. Based on the theoretical analysis, the relation between the upper bound of throughput loss and the number of feedback bits is obtained. In this instance that there are multi users for each cell, an optimum strategy is designed for the allocation of feedback bits across multi cells, with which, the minimum upper bound of throughput loss can be achieved for the given number of user feedback bits.
3) For the downlink transmission in a limited-feedback based multi-user MIMO system, scheduling algorithms are proposed respectively for the single base-station and the multi base-station coordination. In the single base-station, users are selected by maximizing the lower bound of capacity, which is therefore employed as the target function of the proposed method. Using this method, multi user diversity gain can be achieved and thereby the system capacity is increased. In the multi base-station coordination system, an opportunistic SDMA algorithm is proposed for the user scheduling. In this algorithm, each base-station adopts an orthogonal random vector as the beam-forming vector, and the information of beam-forming is shared across based-stations involved in the coordination via high speed link. The SINR is calculated in the receiver for each user, and the user with the highest SINR will be scheduled by the transmitter. By using this algorithm, user selection does not need to consider the user selection results of interfering cells, which well resolves the difficulty of multi base-station coordination and obtains system capacity gain in addition.
4) Considering the characteristic of a multi based-station coordination system, a strategy for the limited quantization feedback is proposed, which is based on error revising technique. In this strategy, the channel quantization procedure is divided into several steps, the number of which is equal to the number of base-stations involved in the coordination. The quantization error of the last step will be revised in the current step. This method can achieve a good trade-off between complexity and system performances, and suitable for base-station coordination system with multi base-station joint processing mechanism.
5) Based on the characteristics of multi base-station coordination system, the antenna selection techniques are studied, which includes distributed antenna selection and base-station selection. Three antenna selection algorithms are proposed for the selection of multi base-station antennas:the Optimal Antenna Selection (OAS), the Aggregate Channel Frobenius Norm Antenna Selection (ACFAS), and the Individual Channel Frobenius Norm Antenna Selection (ICFAS). The OAS algorithm employs a exhaustive searching based strategy, and the ACFAS and the ICFAS are two suboptimal algorithms with lower complexity. The ACFAS method adopts the Frobenius norm of the aggregate channel matrix between the user and all the base-stations involved in the coordination as the antenna selection of target function, while the ICFAS algorithm adopts the Frobenius norm of the channel matrix between the user and each single base-station involved in the coordination as the target function. Considering both the base-station selection and user scheduling, a joint algorithm for selecting base-station and user is proposed, which aims to maximize the system capacity. Following a couple of steps, the base-station and user are selected jointly at both the user-end and the base-station end. Meanwhile, the beam selection is also adopted at the user-end. Therefore, the optimal system performance can be achieved.
引文
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