基于压缩感知理论的频偏估计算法

针对基于交织子载波分配方式的OFDMA上行链路系统的频偏估计问题,提出了一种基于压缩传感理论的频偏估计算法.首先,利用频偏分布稀疏特性,构造出了一种具有稀疏结构的频偏估计模型;根据压缩感知理论,把OFDMA系统中频偏参数估计问题转化为凸优化问题并利用CVX求解最优稀疏向量;然后利用稀疏向量的非零元素位置有效地估计出系统中所有用户频偏信息.所提算法避免了子空间算法中特征值分解等复杂处理过程,从而更具有一定的实用性.仿真结果验证了所提算法的有效性.

Carrier Frequency Offset Estimation Algorithm Based on Compressive Sensing Theory

The carrier frequency offset (CFO) estimation problem was investigated for interleaved orthogonal frequency-division multiple-access (OFDMA) uplink systems. A CFO estimation algorithm was proposed on the compressive sensing theory. First, a CFO estimation model was given by using the sparse property of the CFO distribution. According to compressive sensing theory, the CFO estimation problem was transformed into convex optimization problem and the optimum sparse vector was obtained via CVX. The CFOs of all users could be effectively estimated by exploiting the location of non-zero elements in the sparse vector. The presented method could avoid the eigenvalue decomposition in the subspace methods, and would be more practical. Simulation results were presented to verify the efficiency of the proposed approach.