2007/10/23 by Kamal Shahtalebi, Shahtalebi, Kamal, Golam Reza Bakhshi +3
Computer Science · Engineering · Mathematics · #Advanced Adaptive Filtering Techniques #Advanced Wireless Communication Techniques #Applications (stat.AP) #FOS: Computer and information sciences #Wireless Communication Networks Research #stat.AP
paper · pdf · doi:10.48550/arxiv.0710.4171
5 pages, 3 figures, 2 tables, conference
arxiv created 2007/10/23 · openalex publication_date 2007/10/23 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference cancelation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancelation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the next one. When all user channels are balanced, the unit magnitude is the principal property of the cancelation weight elements. Based on this fact and using a set of NLMS algorithms with different step-sizes, the parallel LMS-PPIC (PLMS-PPIC) method is proposed. In each iteration of the algorithm, the parameter estimate of the NLMS algorithm is chosen to match the elements' magnitudes of the cancelation weight estimate with unity. Simulation results are given to compare the performance of our method with the LMS-PPIC algorithm in three cases: balanced channel, unbalanced channel and time varying channel.