Low Complexity Adaptive and Blind Equalization for Underwater Channel
The complex multiplication in the iteration process of the Least Mean Square (LMS) and Constant Modulus algorithm (CMA) may produce significant latency in high data rate communication. Hence, it is essential to reduce the computational complexity. The sign version of LMS and CMA has the advantage of low complexity, but lack of stability and convergence rate. In this paper, the method of error quantization with power-of-2 is used to quantify the error term of the LMS and CMA algorithm, reducing the multiplication significantly. And this method is successfullyused to the corresponding adaptive and blind Decision Feedback Structures. Because of the multi-bits quantization, the performance of the algorithms using Error Quantization is superior to that of the sign version algorithms. Equalization of the underwater channel shows that the adaptive and blind algorithms using error quantization method behaves similarly to the original algorithms.
Wang Feng Zhao Junwei LiHongsheng
Northwestern Polytechnical University, Xian 710072, P. R. C.
国际会议
北京
英文
378-382
2007-10-01（万方平台首次上网日期，不代表论文的发表时间）