Research On The Wireless Multicast Optimization Technology Based On Layered Source Coding

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.