基于部分信道信息的协同传输物理层关键技术研究
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摘要
随着无线通信系统的不断发展,人们对无线通信的传输速率和通信质量提出了更高的要求。由第三代合作伙伴计划(3rd Generation Partership Project,3GPP)推进的长期演进(Long Term Evlution, LTE)项目近年来受到了广泛的瞩目和研究。目前在中国的许多城市已有LTE应用网络在进行试点,下一步将要大规模商用化。LTE中采用了更高的带宽,以及正交频分多址复用(Orthnomol Frequency Division Multiple Accesss, OFDMA)和多输入多输出(Multiple Input Multiple Output, MIMO)等物理层关键技术,可提供更高的上行／下行传输速率和更好的通信质量。然而,随着无线用户数量越来越大,用户移动性越来越高,未来的无线通信网络不仅需要提供更高的通信速率,更需要提供更大范围的网络覆盖以及小区边缘用户更高的无线通信速率。因此,直接将OFDM. MIMO等技术应用在传统的移动蜂窝网络已无法解决这些问题。近年来无线协同通信成为解决网络覆盖问题的关键技术之一。协同通信是长期演进增强技术(LTE-Advanced, LTE-A)中提出的网络技术之一。无线协同通信主要包括分布式天线(Distributed Antenna System),基站间协同,中继(Relay)技术和家庭基站(Femtocell)等。其中,分布式天线是一种从“小区分裂”出发考虑的新型网络架构,在LTE-A中又称为协同多点(Coordinative Multiple Point, CoMP)传输。这种技术通过插入大量新的分布式站点拉近天线和用户的距离,实现“小区分裂”,获得更高的分集增益。基站协同与分布式天线系统相似,也需要在相邻站点之间布置RoF光纤,所不同的是,这种系统并没有将多个基站的基带处理单元集中在一个“超级基站”,每个基站仍具有完整基带处理功能的基站,基站之间通过光纤进行紧密协同。本文主要针对协同MIMO技术进行了研究,其主要工作和创新成果如下：
1、基于下行多用户MIMO系统中,提出了一种基于最小均方误差(Minimum Mean Square Error, MMSE)的稳健的预编码机制.该机制不仅像传统的MMSE预编码方案一样考虑了噪声功率的影响,同时也考虑了信道量化误差造成的性能损失,因而是一种稳健的预编码方案。仿真结果表明该方案比以前的预编码方案相比有更好的性能。
2、在分布式MIMO系统中,提出了一种新型的功率分配方案。在该模型中,用户选择小区内的一个或多个分布式RRU (Remote Radio Unit,远程天线单元)进行通信。用户通过信道估计计算出用户和每个RRU之间的信道大尺度衰落和发送天线相关性信息,并将这些信息反馈给中央处理单元。中央处理单元将这些大尺度衰落信息和天线相关性信息代入用户传输SER (Symbol Error Rate)的闭式表达式中,利用最优化算法计算得到使SER最小时每个RRU分配的发射功率。因为大尺度衰落和信道天线相关性的变化速率远远低于小尺度衰落的变化速率,属于慢衰落,因此用户仅需要定期反馈相应的大尺度衰落和相关性信息给基站,这大大降低了用户反馈的开销和处理复杂度,并且有接近理想信道最优注水的性能。
3、在基站协同通信系统中,提出一种新的自适应反馈机制。在该模型中,一个主小区中心的主基站同时服务多个用户,主基站周围有若干干扰基站,这些基站通过backhaul链路连接并交换数据。在本系统中,每个用户会受到两种干扰：来自本小区的多用户干扰和邻小区的小区间干扰。用户不仅反馈量化的信道状态信息(channel state information, CSI)给本小区服务基站,同时也反馈干扰信道的CSI给相邻的干扰基站。本文中的算法在每个用户总反馈比特固定的条件下自适应为服务CSI和干扰CSI分配合理的反馈比特数,以使信道量化误差造成的容量损失最低。
4、在基于有限反馈的多小区网络MIMO系统中,每个用户选择小区内若干个基站为其服务。选择不同个数的基站数会造成信道维度发生变化,因为量化信道的码本维度也需要相应变化。本文中提出一种低复杂度的基站选择算法,用户和基站只需要一套码本便可以量化不同维度的CSI,很大程度上降低了码本储存开销。最后,我们提出一种自适应反馈机制,每个用户自适应得为服务信道CSI和干扰信道CSI分配反馈比特数,在总反馈比特数固定的前提下,使传输速率达到最高。
With the rapid development of wireless communications systems, people put forward higher request for transmission rate and communication quality on wireless communication. The Long Time Evolve (LTE), boosted by3rd Generation Partnership Project (3GPP), has received extensive attention and research in recent years. LTE application networks are being tested in many cities in China, and will be commercialized in large scale in the next step. LTE adopts higher bandwidth and key technologies for physical layer, such as Orthogonal Frequency Division Multiple Accesss (OFDMA) and Multiple Input Multiple Output (MIMO), to provide higher uplink/downlink transmission rate and better communication quality. However, with larger amount of users and higher user mobility, future wireless communication networks not only needs to provide a higher data rate, but also wider range of network coverage and higher communication rate of cell edge users. Thus, directly applying these technologhies such as MIMO and OFDM in traditional mobile cellular networks is unable to slove these problems. Cooperative communication is a network thechnology proposed by LTE-Advanced (LTE-A). Wireless cooperative communication mainly includes distributed antenna system (DAS), basestation cooperation, relay and femtocell. Distributed antenna is a kind of new type of network architecture with cell division, also called Coordinative Multiple Point (CoMP) transmission in LTE-A. This technology obtains cell division and higher frequencty reuse by inserting a large number of new sites to close the distance between antennas and users. Basestation cooperation is similar as DAS, which needs to arrange Remote optical fiber (ROF) between adjacent sites. The difference is that the system does not concentrate all the baseband processing units of multiple basestations into a "super basestation", each basestation still has a fully baseband processing function, basestation cooperates closely through optical fiber. This paper mainly researches on cooperative MIMO technology, the main works and innovations are as follows:
1、We propose a robust precoding scheme based on Minimum Mean Square Error (MMSE) criteria in downlink multi-user MIMO systems. This scheme considers not only the effect of noise power as traditional MMSE precoding scheme, but the performance loss caused by channel quantization error as well. Thus, it is a robust precoding scheme. Simulation results show that the proposed scheme has better performance than traditional schemes.
2、We propose a new power allocation scheme in distributed MIMO system. In this model, user within the cell chooses one or more distributed Remote Radio Units (RRUs) for communication. User calculates the channel large-scale fading and antenna correlation informations between RRU through channel estimation, and feeds back these informations back to a central processing unit (CPU). The CPU substitutes these large-scale fading information and antenna correlation informations into the closed-form expression of Symbol Error Rate (SER), and calculates the optimal transmit power of each RRU using optimal theory. Since the change rate of channel large-scale fadings and antenna correlations is much slower than that of small-scale fadings, user only needs to feed back the large-scale fading and correlation information to basestation periodically. This scheme reduces the user feedback overhead and operation complexity greatly and effectively approaches the performance of optimal water filling.
3、We propose a new feedback scheme in base-station cooperation communication system. In this model, a basestation within a central cell serves multiple users simultaneously. Several interfering basestations are around the main basestation, these base-stations are connected by backhaul links and interchange data with each other. Each user of the system is suffered by two interferences:multi-user interferences from local cell and inter-cell interferences from adjacent cells. User not only feeds back the quantized channel state information (CSI) to local service basestation, but feeds back the interference CSI to adjacent basestation as well. This paper proposes that in the algorithm, each user adaptively allocates reasonable feedback bit number for desired CSI and interfering CSI to minimize the capacity loss caused by channel quantization error.
4、In network MIMO network with limited feedback, each user chooses several basestations from a cluster for communication. Selecting different basestation numbers will cause the change of channel dimensions, thus the codebook dimension will change correspondingly. This paper proposes a basestation selection algorithm with low complexity, user only needs a codebook to quantize different dimensions of CSI, which greatly reduces the codebook storage overhead. Finally, we propose an adaptive bit feedback scheme, each user adaptively allocate feedback bits for desired CSI and interfering CSI with fixed feedback bandwidth, to maximize the transmission rate.
1、基于下行多用户MIMO系统中,提出了一种基于最小均方误差(Minimum Mean Square Error, MMSE)的稳健的预编码机制.该机制不仅像传统的MMSE预编码方案一样考虑了噪声功率的影响,同时也考虑了信道量化误差造成的性能损失,因而是一种稳健的预编码方案。仿真结果表明该方案比以前的预编码方案相比有更好的性能。
2、在分布式MIMO系统中,提出了一种新型的功率分配方案。在该模型中,用户选择小区内的一个或多个分布式RRU (Remote Radio Unit,远程天线单元)进行通信。用户通过信道估计计算出用户和每个RRU之间的信道大尺度衰落和发送天线相关性信息,并将这些信息反馈给中央处理单元。中央处理单元将这些大尺度衰落信息和天线相关性信息代入用户传输SER (Symbol Error Rate)的闭式表达式中,利用最优化算法计算得到使SER最小时每个RRU分配的发射功率。因为大尺度衰落和信道天线相关性的变化速率远远低于小尺度衰落的变化速率,属于慢衰落,因此用户仅需要定期反馈相应的大尺度衰落和相关性信息给基站,这大大降低了用户反馈的开销和处理复杂度,并且有接近理想信道最优注水的性能。
3、在基站协同通信系统中,提出一种新的自适应反馈机制。在该模型中,一个主小区中心的主基站同时服务多个用户,主基站周围有若干干扰基站,这些基站通过backhaul链路连接并交换数据。在本系统中,每个用户会受到两种干扰：来自本小区的多用户干扰和邻小区的小区间干扰。用户不仅反馈量化的信道状态信息(channel state information, CSI)给本小区服务基站,同时也反馈干扰信道的CSI给相邻的干扰基站。本文中的算法在每个用户总反馈比特固定的条件下自适应为服务CSI和干扰CSI分配合理的反馈比特数,以使信道量化误差造成的容量损失最低。
4、在基于有限反馈的多小区网络MIMO系统中,每个用户选择小区内若干个基站为其服务。选择不同个数的基站数会造成信道维度发生变化,因为量化信道的码本维度也需要相应变化。本文中提出一种低复杂度的基站选择算法,用户和基站只需要一套码本便可以量化不同维度的CSI,很大程度上降低了码本储存开销。最后,我们提出一种自适应反馈机制,每个用户自适应得为服务信道CSI和干扰信道CSI分配反馈比特数,在总反馈比特数固定的前提下,使传输速率达到最高。
With the rapid development of wireless communications systems, people put forward higher request for transmission rate and communication quality on wireless communication. The Long Time Evolve (LTE), boosted by3rd Generation Partnership Project (3GPP), has received extensive attention and research in recent years. LTE application networks are being tested in many cities in China, and will be commercialized in large scale in the next step. LTE adopts higher bandwidth and key technologies for physical layer, such as Orthogonal Frequency Division Multiple Accesss (OFDMA) and Multiple Input Multiple Output (MIMO), to provide higher uplink/downlink transmission rate and better communication quality. However, with larger amount of users and higher user mobility, future wireless communication networks not only needs to provide a higher data rate, but also wider range of network coverage and higher communication rate of cell edge users. Thus, directly applying these technologhies such as MIMO and OFDM in traditional mobile cellular networks is unable to slove these problems. Cooperative communication is a network thechnology proposed by LTE-Advanced (LTE-A). Wireless cooperative communication mainly includes distributed antenna system (DAS), basestation cooperation, relay and femtocell. Distributed antenna is a kind of new type of network architecture with cell division, also called Coordinative Multiple Point (CoMP) transmission in LTE-A. This technology obtains cell division and higher frequencty reuse by inserting a large number of new sites to close the distance between antennas and users. Basestation cooperation is similar as DAS, which needs to arrange Remote optical fiber (ROF) between adjacent sites. The difference is that the system does not concentrate all the baseband processing units of multiple basestations into a "super basestation", each basestation still has a fully baseband processing function, basestation cooperates closely through optical fiber. This paper mainly researches on cooperative MIMO technology, the main works and innovations are as follows:
1、We propose a robust precoding scheme based on Minimum Mean Square Error (MMSE) criteria in downlink multi-user MIMO systems. This scheme considers not only the effect of noise power as traditional MMSE precoding scheme, but the performance loss caused by channel quantization error as well. Thus, it is a robust precoding scheme. Simulation results show that the proposed scheme has better performance than traditional schemes.
2、We propose a new power allocation scheme in distributed MIMO system. In this model, user within the cell chooses one or more distributed Remote Radio Units (RRUs) for communication. User calculates the channel large-scale fading and antenna correlation informations between RRU through channel estimation, and feeds back these informations back to a central processing unit (CPU). The CPU substitutes these large-scale fading information and antenna correlation informations into the closed-form expression of Symbol Error Rate (SER), and calculates the optimal transmit power of each RRU using optimal theory. Since the change rate of channel large-scale fadings and antenna correlations is much slower than that of small-scale fadings, user only needs to feed back the large-scale fading and correlation information to basestation periodically. This scheme reduces the user feedback overhead and operation complexity greatly and effectively approaches the performance of optimal water filling.
3、We propose a new feedback scheme in base-station cooperation communication system. In this model, a basestation within a central cell serves multiple users simultaneously. Several interfering basestations are around the main basestation, these base-stations are connected by backhaul links and interchange data with each other. Each user of the system is suffered by two interferences:multi-user interferences from local cell and inter-cell interferences from adjacent cells. User not only feeds back the quantized channel state information (CSI) to local service basestation, but feeds back the interference CSI to adjacent basestation as well. This paper proposes that in the algorithm, each user adaptively allocates reasonable feedback bit number for desired CSI and interfering CSI to minimize the capacity loss caused by channel quantization error.
4、In network MIMO network with limited feedback, each user chooses several basestations from a cluster for communication. Selecting different basestation numbers will cause the change of channel dimensions, thus the codebook dimension will change correspondingly. This paper proposes a basestation selection algorithm with low complexity, user only needs a codebook to quantize different dimensions of CSI, which greatly reduces the codebook storage overhead. Finally, we propose an adaptive bit feedback scheme, each user adaptively allocate feedback bits for desired CSI and interfering CSI with fixed feedback bandwidth, to maximize the transmission rate.
引文
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