多小区OFDMA系统资源分配算法与信道估计
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摘要
随着无线通信应用的丰富和发展，服务质量(QoS)需求与无线通信资源有限的矛盾日益尖锐。为缓解这一矛盾，必须从无线通信系统的各个层面展开研究。在物理层，正交频分复用(OFDM)是一种非常适合于宽带无线系统的技术;在链路层，采用资源分配和调度可以显著改善通信系统的频谱效率和吞吐量。另外，OFDMA技术的独特优势，为资源分配提供了灵活的自由度，因此，OFDMA系统中的资源分配算法得到了广泛的关注。
正交频分多址(OFDMA)是将正交频分复用(OFDM)技术和频分多址(FDMA)技术相结合的多址方案，是第四代移动通信系统(4G)的关键技术之一。OFDMA以OFDM调制为基础，通过给不同用户独立地分配子载波来实现多用户接入，在多用户同时接入的情况下，OFDMA系统基于无线信道的状态、服务质量(QoS)要求等参数动态地制定资源配置方案，从而实现资源的自适应最优配置。这样，系统既能获得更高的频谱利用率，又可以更好地满足QoS要求。自适应资源配置是当前一个重要的研究课题，也是OFDMA系统急需解决的核心问题之一。
针对这个研究方向，本文在深入研究多小区OFDMA自适应资源配置过程中提出了一种基于罚函数的资源分配算法和一种低复杂度资源分配算法，同时研究了系统中信道噪声的估计，提出了一种基于最大似然法的联合测量干扰和噪声功率水平的非数据辅助算法。全文系统地分析和研究了在多小区OFDMA系统进行自适应资源配置需要解决的问题，具体主要有如下三个方面的工作和创新:
(1)基于罚函数的模拟退火资源分配算法，在多小区OFDMA系统中，基于集中式资源管理，考虑本小区对其他小区的干扰情况，对各个小区的子载波和功率分配进行调整，从而达到最小化总功率的目的。通过功率离散化来建立多小区OFDMA问题模型，使用罚函数法来简化问题模型，并采用改进的模拟退火算法进行求解。本文提出的罚函数SA（Penalty-Simulation Annealing）资源分配算法，简化了问题模型，从而降低了模型求解复杂度。理论分析和仿真结果表明，离散功率个数的选择在一定范围内具有随机性。文章提出的算法获得了更好的系统吞吐量，同时有效降低了求解复杂度，且对整体性能不会产生不良影响；与多分配算法相比，单位功率吞吐量有显著提高。
(2)提出了一种低复杂度资源分配算法，通过对一组线性方程组的求解，在最小化传输功率的同时满足了用户最大传输需求。该算法把子载波和功率分配分别实施，即把资源分配过程分成子载波分配和功率分配两个独立的步骤进行，在子载波分配时，假设频效率固定简化了分配复杂度，在固定频率效率的情况下，功率分配可以通过一组线性方程组求得，当方程组的解出现负值时，通过调整算法对负值的解进行处理实现正确的分配结果，仿真结果表明该算法在系统吞吐量、功率效率、算法复杂度等方面，取得了一个介于最优算法和多分配算法之间的折衷。
(3)提出了一个基于最大似然法的平坦信道估计算法，该算法是一种联合测量干扰和噪声功率水平的非数据辅助算法。针对确定性未知高斯白噪声干扰的有限状态离散信号，该算法首先假设在特定条件下，得到一个近似的闭形式解，然后以些解为初始值，采用迭代的方法，以最大似然准则为基础，得到完善的估计结果。仿真结果表明该方法具有收敛速度快，准确性高等特性。
With the rapid development of wireless communications, the contradiction between thelimited wireless resources and the increasing requirements for Quality of Service (QoS)becomes more and more apparent. To solve this problem various technologies at differentlayers of wireless systems should be involved. In the physical layer, Orthogonal FrequencyDivision Multiplexing (OFDM) technology has proved to be very suitable for widebandwireless systems. In the data link layer, resource allocation and scheduling can be used toimprove the frequency efficiency and throughput of communication systems. Moreover,OFDMA provides flexibility for resource allocation due to its unique characteristic. Thus,resource allocation in OFDMA systems has attracted great attention in recent years.
Orthogonal Frequency Division Multiple Access (OFDMA) is a multiple accesstechnology combining OFDM with Frequency Division Multiple Access (FDMA) and hasbeen considered as one of the key technologies in4G mobile communication systems. Basedon the OFDM modulation，OFDMA achieves the multi-user access by allocating subcarriersto every user independently. In the scenario of multi-user accessing simultaneously, OFDMAsystems choose resource allocation strategy according to the condition of wireless channel,QoS, etc, in order to realize optimal adaptive resource allocation. Then the system can notonly achieve higher spectrum utilization, but also better satisfy QoS requirements. Therefore,adaptive resource allocation is a very important research topic and is also one of the mainproblems to be solved in OFDMA systems.
In this thesis，we researched on adaptive resource allocation in multi-cell OFDMA andproposed a resource allocation algorithm based on the penalty function and a low-complexityresource allocation algorithm. We also studied channel noise estimation and came up with anon-data-aided algorithm for joint measurement of interference and noise power based on themaximum likelihood criterion. Our contributions can be summarized in the following threeaspects:
(1) In the multi-cell OFDMA systems, based on the centralized resource management,taking the interference between cells into consideration, the subcarrier and power allocationfor each cell is adjusted so as to minimize the total power. Discretize power to establish a multi-cell OFDMA model. Then the problem is simplified by penalty function and solved byan improved simulated annealing algorithm. In this thesis, a penalty function SA(Penalty-Simulation Annealing) resource allocation algorithm has been proposed to simplifythe model and reduce the complexity. Theoretical analysis and simulation results show thatthe selection of the number of discrete power is random within certain range. The proposedalgorithm can achieve better throughput with reduced complexity and the same overallperformance; compared with the multi-allocation algorithm, the unit power throughput issignificantly improved.
(2) A low complexity resource allocation algorithm is proposed, which minimizestransmission power and in the mean time satisfies great transmission demand by solving a setof linear equations. The resource allocation process is carried out in two steps: sub-carrierassignment and power allocation. In the sub-carrier assignment, it is assumed that fixing thefrequency efficiency simplifies allocation. With fixed frequency efficiency, power allocationproblem can be solved through a set of linear equations. When the solution is negative, correctdistribution results are obtained by adjusting the algorithm. Simulation results show that thealgorithm achieves a compromise between the optimal algorithm and the multi-allocationalgorithm in throughput, power efficiency, complexity, etc.
(3) A flat channel estimation algorithm based on Maximum Likelihood criterion isproposed. It is a non-data-aided algorithm, which carries out joint measurement ofinterference and noise power. Targeting at finite state discrete signals interfered by unknownwhite Gaussian noise, the algorithm first assumes that under certain conditions, anapproximate closed form solution can be obtained. Then with this solution as the initial value,using an iterative approach, a complete estimation result is obtained based on the maximumlikelihood criterion. Simulation results show that this method has the advantages of fastconvergence, high accuracy, etc.
正交频分多址(OFDMA)是将正交频分复用(OFDM)技术和频分多址(FDMA)技术相结合的多址方案，是第四代移动通信系统(4G)的关键技术之一。OFDMA以OFDM调制为基础，通过给不同用户独立地分配子载波来实现多用户接入，在多用户同时接入的情况下，OFDMA系统基于无线信道的状态、服务质量(QoS)要求等参数动态地制定资源配置方案，从而实现资源的自适应最优配置。这样，系统既能获得更高的频谱利用率，又可以更好地满足QoS要求。自适应资源配置是当前一个重要的研究课题，也是OFDMA系统急需解决的核心问题之一。
针对这个研究方向，本文在深入研究多小区OFDMA自适应资源配置过程中提出了一种基于罚函数的资源分配算法和一种低复杂度资源分配算法，同时研究了系统中信道噪声的估计，提出了一种基于最大似然法的联合测量干扰和噪声功率水平的非数据辅助算法。全文系统地分析和研究了在多小区OFDMA系统进行自适应资源配置需要解决的问题，具体主要有如下三个方面的工作和创新:
(1)基于罚函数的模拟退火资源分配算法，在多小区OFDMA系统中，基于集中式资源管理，考虑本小区对其他小区的干扰情况，对各个小区的子载波和功率分配进行调整，从而达到最小化总功率的目的。通过功率离散化来建立多小区OFDMA问题模型，使用罚函数法来简化问题模型，并采用改进的模拟退火算法进行求解。本文提出的罚函数SA（Penalty-Simulation Annealing）资源分配算法，简化了问题模型，从而降低了模型求解复杂度。理论分析和仿真结果表明，离散功率个数的选择在一定范围内具有随机性。文章提出的算法获得了更好的系统吞吐量，同时有效降低了求解复杂度，且对整体性能不会产生不良影响；与多分配算法相比，单位功率吞吐量有显著提高。
(2)提出了一种低复杂度资源分配算法，通过对一组线性方程组的求解，在最小化传输功率的同时满足了用户最大传输需求。该算法把子载波和功率分配分别实施，即把资源分配过程分成子载波分配和功率分配两个独立的步骤进行，在子载波分配时，假设频效率固定简化了分配复杂度，在固定频率效率的情况下，功率分配可以通过一组线性方程组求得，当方程组的解出现负值时，通过调整算法对负值的解进行处理实现正确的分配结果，仿真结果表明该算法在系统吞吐量、功率效率、算法复杂度等方面，取得了一个介于最优算法和多分配算法之间的折衷。
(3)提出了一个基于最大似然法的平坦信道估计算法，该算法是一种联合测量干扰和噪声功率水平的非数据辅助算法。针对确定性未知高斯白噪声干扰的有限状态离散信号，该算法首先假设在特定条件下，得到一个近似的闭形式解，然后以些解为初始值，采用迭代的方法，以最大似然准则为基础，得到完善的估计结果。仿真结果表明该方法具有收敛速度快，准确性高等特性。
With the rapid development of wireless communications, the contradiction between thelimited wireless resources and the increasing requirements for Quality of Service (QoS)becomes more and more apparent. To solve this problem various technologies at differentlayers of wireless systems should be involved. In the physical layer, Orthogonal FrequencyDivision Multiplexing (OFDM) technology has proved to be very suitable for widebandwireless systems. In the data link layer, resource allocation and scheduling can be used toimprove the frequency efficiency and throughput of communication systems. Moreover,OFDMA provides flexibility for resource allocation due to its unique characteristic. Thus,resource allocation in OFDMA systems has attracted great attention in recent years.
Orthogonal Frequency Division Multiple Access (OFDMA) is a multiple accesstechnology combining OFDM with Frequency Division Multiple Access (FDMA) and hasbeen considered as one of the key technologies in4G mobile communication systems. Basedon the OFDM modulation，OFDMA achieves the multi-user access by allocating subcarriersto every user independently. In the scenario of multi-user accessing simultaneously, OFDMAsystems choose resource allocation strategy according to the condition of wireless channel,QoS, etc, in order to realize optimal adaptive resource allocation. Then the system can notonly achieve higher spectrum utilization, but also better satisfy QoS requirements. Therefore,adaptive resource allocation is a very important research topic and is also one of the mainproblems to be solved in OFDMA systems.
In this thesis，we researched on adaptive resource allocation in multi-cell OFDMA andproposed a resource allocation algorithm based on the penalty function and a low-complexityresource allocation algorithm. We also studied channel noise estimation and came up with anon-data-aided algorithm for joint measurement of interference and noise power based on themaximum likelihood criterion. Our contributions can be summarized in the following threeaspects:
(1) In the multi-cell OFDMA systems, based on the centralized resource management,taking the interference between cells into consideration, the subcarrier and power allocationfor each cell is adjusted so as to minimize the total power. Discretize power to establish a multi-cell OFDMA model. Then the problem is simplified by penalty function and solved byan improved simulated annealing algorithm. In this thesis, a penalty function SA(Penalty-Simulation Annealing) resource allocation algorithm has been proposed to simplifythe model and reduce the complexity. Theoretical analysis and simulation results show thatthe selection of the number of discrete power is random within certain range. The proposedalgorithm can achieve better throughput with reduced complexity and the same overallperformance; compared with the multi-allocation algorithm, the unit power throughput issignificantly improved.
(2) A low complexity resource allocation algorithm is proposed, which minimizestransmission power and in the mean time satisfies great transmission demand by solving a setof linear equations. The resource allocation process is carried out in two steps: sub-carrierassignment and power allocation. In the sub-carrier assignment, it is assumed that fixing thefrequency efficiency simplifies allocation. With fixed frequency efficiency, power allocationproblem can be solved through a set of linear equations. When the solution is negative, correctdistribution results are obtained by adjusting the algorithm. Simulation results show that thealgorithm achieves a compromise between the optimal algorithm and the multi-allocationalgorithm in throughput, power efficiency, complexity, etc.
(3) A flat channel estimation algorithm based on Maximum Likelihood criterion isproposed. It is a non-data-aided algorithm, which carries out joint measurement ofinterference and noise power. Targeting at finite state discrete signals interfered by unknownwhite Gaussian noise, the algorithm first assumes that under certain conditions, anapproximate closed form solution can be obtained. Then with this solution as the initial value,using an iterative approach, a complete estimation result is obtained based on the maximumlikelihood criterion. Simulation results show that this method has the advantages of fastconvergence, high accuracy, etc.
引文
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