能量因子修正的常数模盲均衡

CMA Blind Equalization Modified By Energy Factor

针对通信信号传输过程中能量损耗影响常数模盲均衡收敛性能问题,提出了一种能量因子修正的常数模盲均衡算法。通过在常数模代价函数中引入能量因子,对接收信号功率进行放大,以满足SW定理在盲均衡实现中对传输信号能量的约束条件。能量因子采用梯度下降算法进行自适应调整,解决了能量因子估计困难问题。能量因子修正的常数模盲均衡算法在能量因子约束条件下对代价函数进行寻优,可有效提高算法的收敛性能,并且改进方法体现在对代价函数的修正上,可推广到基于梯度算法的各类改进常数模盲均衡算法中。仿真结果表明,文中提出的方法与传统CMA算法相比具有更快的收敛速度和更小的稳态剩余误差。

To solve the problem that the energy loss during the transmission in the communication system degrades the convergence performance of CMA blind equalization,a new CMA blind equalization modified by energy factor is proposed. The energy factor is added to the cost function of CMA,which can amplify the power of the received signal to meet the constraints of transmission signal energy to achieve blind equalization in SW theorem. The energy factor uses the gradient descent algorithm for adaptive updating,which can solve the difficult problem of energy factor estimation. The proposed method implements optimizing the cost function under the constraint conditions of the energy factor,which can effectively improve the convergence performance. Furthermore,CMA blind equalization modified by energy factor is designed in the revision of the cost function,which can be extended to all other improved types of CMA blind equalization based on gradient descent algorithm. The simulation results show that the proposed method can obtain faster convergence rate and lower steady state residual error compared with the traditional CMA blind equalization.