【作者】 陈雷；

【导师】 王晓湘；

【作者基本信息】 北京邮电大学 ， 信号与信息处理， 2013， 博士

【摘要】 最近,随着无线通信技术,网络技术和数字信号处理技术的发展,无线多媒体多播广播技术,已经逐渐成为下一代移动蜂窝网络发展的种趋势。无线多媒体多播广播技术首先在3GPP的R6版本中被介绍,该技术是通过占用相同的网络资源,从一个数据源向多个目标用户传输相同的数据,因此可以节省大量的网络资源,进而提高资源的利用率。但是在传统的多播策略中,多播速率受限于多播组中最差用户的容量,因此系统的吞吐量严重受限。为了提高多播系统的性能,本文针对无线多播系统中,基于分层编码的多播优化技术进行研究,分别从时域、频域、码域和空间域进行综合分析,首先,针对单组多播中的多播用户的速率受限于最差用户的情况,从码域方面研究了FGS视频编码技术,并将其应用到时域和频域的优化算法中,在保证每个用户QoS需求的同时,最大化系统吞吐量。其次,将分层信源编码与擦除纠错信道编码相结合,并将其应用于多组多播中,用以提高系统吞吐量。再次,针对实际多播系统中,上行反馈负载量大的问题,设计了有限反馈策略,并采用多描述编码,来提高多播系统的容量。最后,将多天线技术引入多播系统,并讨论多播系统中的空域、时域、频域和码域的联合优化问题。论文的主要创新点和工作从以下几个方面展开。(1)研究了在信道信息全反馈时,基于分层信源编码的单组多播系统的优化技术。从码域、时域和频域,3方面考虑多播系统的优化。从系统吞吐量和用户QoS需求方面,来研究单组多播中的多播优化问题。首先使用分层信源编码,将原始的多播数据分为一个基本层和多个增强层。基本的数据要求被每个多播用户所正确接收,增强层的数据是发送给信道条件好的用户。采用分层编码技术可以根据用户信道条件的差异,提供质量差异的多播服务。其次,为了避免最优化算法的高的计算复杂度,提出了低复杂度的,2阶段次优化算法。最后,通过仿真可以看到,在与最优化算法达到的系统性能差别不大的情况下,有效的降低了计算复杂度,并且提出的算法明显优于传统的多播策略。(2)研究了在信道信息全反馈时,基于分层信源编码联合信道编码的多组多播系统的优化技术。在单频网场景下,采用分层信源编码,来编码原始多播数据,形成基本层数据和增强层数据,之后再使用擦除纠错编码来重新编码基本层和增强层数据。使用擦除纠错编码,可以在接收端恢复因为信道质量差而丢失的数据包,从而可以减少反馈重传,节省网络资源。首先研究在保证基本层所需的最小速率的情况下,来最大化增强层和速率的最优化问题；其次,提出了计算复杂度低的,基于联合编码的次优化的子载波和功率分配算法。在子载波分配上根据每个多播组不同的QoS需求和保持每个多播组比例公平的情况下,来合理分配子载波,以提高系统性能。在功率分配上提出了改进的注水功率分配算法,以保证每个多播组QoS需求的同时,进一步提高多播系统性能。(3)研究了在信道信息有限反馈时,采用分层信源编码的单组多播系统的优化技术。在单组多播的场景下,我们采用多描述分层信源编码策略。之后为了减少多播系统的上行反馈负载,根据我们优化的目标,我们设计了上行的有限反馈策略。首先研究在有限反馈时,采用多描述编码策略并利用多播组内的多用户分集增益；其次,在子载波分配阶段,根据用户QoS需求和信道质量,采用2阶段的比例公平子载波分配算法。再次,在功率分配阶段,提出了保证用户QoS需求的基于梯度的功率分配算法。为了进一步提高系统性能,我们又提出了保证用户QoS需求的基于拉格朗日乘数的功率分配算法。(4)研究了在信道信息有限反馈时,采用分层信源编码联合信道编码的多天线多组多播系统的优化技术。从码域、时域、频域和空域,4个方面考虑多播系统的优化。针对在有限反馈的情况下,对多天线多播系统中的预编码和联合编码与子载波分配和功率分配展开研究,从多播系统吞吐量与保证多播组间QoS需求上来分析多播优化问题。首先,设计分层的有限反馈策略,其次设计预编码策略,再次设计联合编码策略,最后在保证每个多播组不同的QOS需求时,按比例分配子载波,来最大化系统吞吐量,并且为了进一步提升系统性能,采用2种改进的功率分配算法。仿真结果显示,提出的基于有限反馈策略的算法功效,明显优于传统多播策略和另外一些算法。而且,提出的有限反馈策略与全反馈策略相比,能够减少50%的反馈量。更多还原

【Abstract】 Recently, with the development of wirless communications technology, digital signal processing techniques and wireless communication network, wireless multicast broadcast and multicast services (MBMS) becomes a trend of the next-generation mobile cellular networks. MBMS introduced by3GPP in Release6, it can provide the same information from one single source to multiple users using the same resource of network. Therefore, the broadcast and multicast transmission can improve resource utilization efficiency. In conventional multicast scheme (CMS), the total throughput of multicast group is constrained by the user with the worst channel quality. In order to overcome this problem of limited throughput, this dissertation focuses on the wireless multicast optimization technology based on layered source coding in wireless multicast systems. We consider comprehensivly the problem on time domain, frequency domain, spatial domain and coding domain. Firstly, in conventional multicast scheme (CMS), the total throughput of multicast group is constrainted by the user with the worst channel quality. We exploit fine granularity scalability (FGS) video coding in the multicast optimization technology during the time domain and frequency domain. The objective is maximum throughput of a whole multicast group while at the same time guaranteeing the quality of services (QoS) requirements of all users. Secondly, we exploit layered coding combined with erasure correction coding for multicast services among multiple multicast groups in order to improve the performance of system. Thirdly, to reduce the feedback overhead of uplink, we design a novel transmission scheme with limited feedback. We utilize the multiple description coding (MDC) to improve the throughput of system. Lastly, we discuss the multicast optimization technology in multi-antenna multicast system during time domain, frequency domain, spatial domain and coding domain. The main innovation and contents of this dissertation are presented as follows:l)We research on the optimization technology based on FGS video coding of the single multicast group, when all the users’channel state information can be full feed back to BS. We consider the problem from time domain, frequency domain and coding domain. Firstly, we exploit the FGS video coding to encode the original multicast data into a base layer and several enhancement layers. The base layer data should be sent to all users. The enhancement layer data should be sent to some users who have the better channel quality. Layered coding can provide the different multicast services according to users’different channel quality. Secondly, a two-phase suboptimal algorithm is proposed to reduce the computational complexity. Simulation results show that the performance gap between the optimal algorithm and the proposed suboptimal algorithm is quite small. The proposed algorithm significantly outperforms CMS. Moreover, it obtains more throughput than another existing algorithm.2) We research on the optimization technology based on FGS video coding combined with unequal error protection (UEP) Reed-Solomon (RS) coding during the multiple multicast groups, when all the users’ channel state information can be full feed back to BS. We propose an optimal resource allocation algorithm by exploiting layered coding combined with erasure correction coding for multicast services in the downlink of OFDMA-based single frequency networks (SFN). In this algorithm, we exploit unequal error protection UEP RS coding to compensate for possible data packet loss of base layer and enhancement layers which are obtained from FGS video coding. In order to reduce the feedback load, BSs only utilize the average channel state information (CSI) of the users. The proposed algorithm maximizes the enhancement layers throughput while guaranteeing the minimum data rate of the base layer in each multicast group. A two-phase suboptimal algorithm is proposed to reduce the computational complexity. Simulation results show that the performance of the algorithm with UEP RS coding is much better than the algorithm without. Moreover, the proposed algorithms significantly outperform CMS.3) We research on the optimization technology based on FGS video coding of the single multicast group under the limited feedback. We exploit MDC to encode the original multicast data into many layers. The users can correctly receive the more data when their channel quality is better. According to the characteristic of MDC, we design the feedback scheme of uplink. We discuss the MDC under the limited feedback scheme. Secondly, we propose two-phase proportional fairness subcarrier allocation algorithm. Thirdly, we propose power allocation algorithm based on gradient while guaranteeing QoS requirements of all users. Lastly, in order to further improve the performance of system, we also propose power allocation algorithm based on Lagrange multiplier method while guananteeing QoS requirements.4) We research on the optimization technology based on jointly coding scheme and precoding scheme during the multiple multicast groups under limited feedback scheme. We consider the multicast optimization technology form time domain, frequency domain, spatial domain and coding domain. To reduce the feedback overhead of uplink, we design a novel transmission scheme with layered limited feedback. Then, we formulate the joint subcarrier and power allocation problem for the data of base layer and enhancement layers, which is shown to be NP hard. Hence, in order to reduce the computational complexity, we propose a three-phase suboptimal algorithm. The algorithm is designed to maximize the system throughput while at the same time guaranteeing the QoS requirements of all multicast groups. It is composed of precoding scheme, proportional fairness subcarrier allocation algorithm and2modified power allocation algorithms Simulation results show that the proposed algorithms based on limited feedback scheme significantly outperform CMS and any other existing algorithm with full feedback. Moreover, the proposed scheme can efficiently reduce50%of the full feedback overhead.更多还原