一种基于信道缩短的深衰落稀疏均衡改进算法

针对较低信噪比下的深衰落稀疏多径信道，提出了一种基于信道缩短的自适应稀疏均衡改进算法。该算法采用前置分数间隔信道缩短均衡器与后置自适应稀疏均衡器级联的均衡器结构，其中，首先利用短训练序列设计基于最小均方误差准则的前置均衡器，前置均衡器与稀疏多径信道级联后得到能量集中于较短时间区域且分布稀疏的等效信道，使得原始信道的深衰落畸变得到部分有效补偿；然后采用能实现稀疏信号重构的随机梯度追踪算法调整后置自适应均衡器的抽头系数，后置均衡器用于消除等效信道的剩余符号间干扰。仿真结果表明，与传统的单级分数间隔自适应均衡器相比，该算法具有收敛速度快和运算复杂度低的优点。

Adaptive equalization algorithm for deep fading sparse multipath channel based on channel shortening

A modified adaptive sparse equalization algorithm based on channel shortening is proposed for deep fading sparse multipath channel under low signal-to-noise ratio. The algorithm performs equalization by cascading a front-end fractional-spaced channel shortening equalizer with a back-end adaptive sparse equalizer. Firstly, the short training sequence is utilized to design the minimum mean square error based front-end equalizer, then the sparse multipath channel is first equalized to an equivalent channel whose energy focuses on a short period and distributes sparsely by the front-end equalizer, partially effectively compensating the deep fading distortion of the original channel. Secondly, the back-end equalizer adopts stochastic gradient pursuit algorithm which can recover sparse signal to update coefficients, eliminating the residual inter-symbol interference of the equivalent channel. Simulation results show that compared with single-stage fractional-spaced adaptive equalizer, the present algorithm provides superior performance by increasing the convergence rate and decreasing the computation.