Independent Component Analysis Based Blind Adaptive Interference Reduction and Symbol Recovery for OFDM Systems

• Published in: 中国通信（英文版） Vol. 13; no. 2; pp. 41 - 54
• Main Author: LUO Zhongqiang ZHU Lidong LI Chengjie
• Format: Journal Article
• Language: English
• Published: National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China 01.02.2016
• Subjects: OFDM信号; OFDM系统; 正交频分复用; 混合矩阵; 独立分量分析; 统计独立; 自适应干扰抑制; 载波频率偏移; orthogonal frequency division multiplexing (OFDM); blind interference suppression; symbol recovery; independent component analysis (ICA); blind source separation (BSS)
• ISSN: 1673-5447
• DOI: 10.1109/CC.2016.7405724

To overcome the inter-carrier interference （ICI） of orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis （ICA）. Taking into account statistical independence of subcarriers＇ signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation （BSS） framework. In this paper, the ICA- based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.