IMT-Advanced系统中多播资源分配策略的研究

发布时间：2018-06-30 03:17

本文选题：资源分配 + 吞吐量　；参考：《北京邮电大学》2014年博士论文

【摘要】：随着无线通信技术的迅猛发展,移动用户数日益增多,服务质量要求越来越高,无线资源很难满足用户的通信需求。为了提高资源利用率,无线广播/多播技术(BMS)使用相同的时频资源给多个用户传输相同的业务,成为下一代移动蜂窝网络(IMT-Advanced)标准中的一项关键技术。为了改善现有资源分配算法中存在的问题,进一步增强多播传输的性能,本论文从增大多播系统吞吐量、保证多播用户间公平性、减小多播系统反馈量和实现多播传输时间与能量消耗均衡四个目标展开,研究了不同准则下多播系统的用户调度、用户间的子载波分配、功率分配和比特加载算法,主要研究内容如下： (1)研究了基于吞吐量最大化的机会多播调度问题,提出了一种基于自适应用户选择的多播调度方案。首先,阐述了机会多播调度原理；其次,建立了系统吞吐量矩阵,并用该矩阵模拟了机会多播调度过程；再次,根据用户的信道概率分布函数,推导了系统吞吐量矩阵中每个元素的值；最后,为了减低全搜索解法的运算复杂度,提出了一种次优化的启发式搜索方法；仿真结果显示,所提的自适应用户选择方案可以显著地提高系统的吞吐量。 (2)研究了保证用户间公平性的多播资源分配问题,提出了一种基于子载波协作和用户分组的多播资源分配算法。目标是在保证用户间完全公平的基础上最大化系统吞吐量。建立了多播系统中功率和带宽受限条件下的最优化函数。为了降低最优化算法的运算复杂度,提出了一种两阶段的次优化算法。在第一阶段,阐述了子载波协作方案,根据该方案设计了子载波协作及用户分组传输算法来增大多播系统传输效率,为了进一步降低运算复杂度,又提出了简化算法；在第二阶段,利用注水算法在子载波间进行了功率调整,进一步增大系统容量。仿真结果显示,所提算法不但能够保证用户接受完全相同质量的服务,而且具有较好的吞吐量性能。 (3)研究了较少反馈下的多播资源分配问题,针对用户信道概率分布函数未知与已知两种场景,分别提出了基于机会反馈的多播资源分配算法和基于编码的无反馈多播资源分配算法。在基于机会反馈的多播资源分配算法中,首先,理论证明了影响系统吞吐量性能的关键信道信息以较大概率属于一个信道增益区间；其次,采用概率统计方法估计了该区间；最后,提出了多播系统中的机会反馈方案,并在该反馈机制下完成了资源分配。较之已有的部分反馈方案,所提机会反馈方案能够显著的降低系统的反馈量。在基于编码的无反馈多播资源分配算法中,首先,提出了数据的可修正编码和分层编码联合编码方案；其次,根据信道增益概率密度函数推导了基本层和增强层的传输速率；最后,根据基本层和增强层数据的特征,分别提出了基础层算法和增强层算法。较之已有的无反馈方案,所提联合编码方案能够取得更好的吞吐量性能。 (4)研究了多播系统中的传输时间与能量消耗均衡问题,提出了一种基于自适应解调映射的均衡方案。首先,为了提高系统传输效率,将自适应解调映射方案引入到多播传输系统中；其次,理论推导了自适应解调映射方案下的多播传输时间和能量消耗的表达式；最后,建立了一个基于衰减因子的距离最小化问题来实现传输时间与能量消耗之间的均衡。所提均衡方案适用范围较广：对于时延敏感系统,可以实现传输时间最小化；对于能量敏感系统,可以实现能量消耗最小化；对于普通系统,可以实现传输时间和能量消耗的均衡。
[Abstract]:With the rapid development of wireless communication technology , the number of mobile users is increasing and the quality of service is more and more demanding . In order to improve the resource utilization rate , the wireless broadcast / multicast technology ( BMS ) uses the same time - frequency resources to transmit the same service to multiple users , and it becomes a key technology in the next generation mobile cellular network ( IMT - Advanced ) standard . In order to improve the throughput of the multicast system , to ensure the fairness among the multicast users , reduce the feedback amount of the multicast system and realize the equilibrium of the multicast transmission time and energy consumption , the paper studies the user scheduling of the multicast system , the subcarrier allocation , the power allocation and the bit loading algorithm among users , and the main research contents are as follows :

( 1 ) The problem of opportunistic multicast scheduling based on maximum throughput is studied , and a multicast scheduling scheme based on adaptive user selection is proposed . Firstly , the principle of opportunistic multicast scheduling is described .
Secondly , the system throughput matrix is established and the opportunity multicast scheduling process is simulated with the matrix .
thirdly , according to the channel probability distribution function of the user , the value of each element in the system throughput matrix is deduced ;
Finally , in order to reduce the computational complexity of the full search method , a heuristic search method is proposed .
Simulation results show that the proposed adaptive user selection scheme can significantly improve the throughput of the system .

( 2 ) A multicast resource allocation algorithm based on sub - carrier coordination and user grouping is proposed . The goal is to maximize the system throughput on the basis of guaranteeing the perfect fairness among users . The objective is to maximize the system throughput on the basis of ensuring the full fairness among users . In the first stage , a two - stage optimization algorithm is proposed . In the first stage , the sub - carrier cooperation and the user packet transmission algorithm are designed to increase the transmission efficiency of the multicast system . In order to further reduce the operation complexity , a simplified algorithm is proposed .
Simulation results show that the proposed algorithm not only can guarantee users to accept the same quality of service , but also has better throughput performance .

( 3 ) The multicast resource allocation problem with less feedback is studied , and the multicast resource allocation algorithm based on the opportunity feedback and the non - feedback multicast resource allocation algorithm based on the coding are proposed for the unknown and the known two scenarios of the probability distribution function of the user channel .

In the multicast resource allocation algorithm based on opportunity feedback , firstly , the theory proves that the key channel information affecting the system throughput performance belongs to a channel gain interval with larger probability ;
Secondly , the interval is estimated by probability statistics method .
Finally , an opportunity feedback scheme in the multicast system is proposed and the resource allocation is completed under the feedback mechanism . Compared with the existing partial feedback scheme , the proposed feedback scheme can significantly reduce the feedback amount of the system .

In the coding - based non - feedback multicast resource allocation algorithm , firstly , a scalable coding and hierarchical coding scheme of data is proposed .
secondly , the transmission rate of the base layer and the enhancement layer is deduced according to the channel gain probability density function ;
Finally , based on the characteristics of the base layer and the enhancement layer data , the base layer algorithm and the enhancement layer algorithm are proposed . Compared with the existing feedback scheme , the proposed joint coding scheme can achieve better throughput performance .

In order to improve the transmission efficiency of the system , the adaptive demodulation mapping scheme is introduced into the multicast transmission system .
Secondly , the expression of multicast transmission time and energy consumption under adaptive demodulation mapping scheme is deduced .
Finally , a distance minimization problem based on the attenuation factor is established to realize the equalization between transmission time and energy consumption . The proposed equalization scheme has a wide application range : for time delay sensitive system , the transmission time can be minimized ;
For energy sensitive systems , energy consumption can be minimized ;
For a conventional system , equalization of transmission time and energy consumption can be achieved .
【学位授予单位】：北京邮电大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN929.5

【参考文献】