LMMSE channel estimation with soft statistics for turbo-MIMO receivers

• Published in: IEEE communications letters Vol. 13; no. 8; pp. 585 - 587
• Main Authors: SHIN, Wooram, SEUNG JOON LEE, KWON, Dong-Seung, KANG, Joonhyuk
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Blocking; Channel estimation; Channels; Coding, codes; Decoding; Detection, estimation, filtering, equalization, prediction; Error analysis; Errors; Exact sciences and technology; expectation maximization (EM); Fading; Information, signal and communications theory; linear minimum mean squared error (LMMSE); Maximization; maximum likelihood (ML); Maximum likelihood decoding; Maximum likelihood estimation; Mean square error methods; MIMO; Quadrature phase shift keying; Receivers; Robustness; Signal and communications theory; Signal, noise; soft statistics; Statistics; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Turbo MIMO receiver; Performance evaluation; MIMO system; Estimation error; Second order; Parameter estimation; Turbo MIMO receiver; Order statistic; linear minimum mean squared error (LMMSE); Iterative method; Turbo code; Decoding; expectation maximization (EM); Block error rate; Mean square error; Learning; Statistical method; maximum likelihood (ML); Channel estimation; A priori estimation; soft statistics; Maximum likelihood; Growth of error; EM algorithm; Signal detection
• ISSN: 1089-7798; 1558-2558
• DOI: 10.1109/LCOMM.2009.090831

Channel estimation techniques for turbo multiple-input multiple-output receivers are addressed, which exploit a priori information to refine the poor performance of initial channel estimates solely using training symbols. We study linear minimum mean squared error channel estimation (LMMSE-CE) using second-order soft statistics to incorporate the degree of decoding reliability. Utilizing this additional information effectively minimizes the error propagation which the maximum likelihood based expectation maximization channel estimation (ML-CE) suffers. The LMMSE-CE provides a smaller mean square error of channel estimation and block error rate than the ML-CE.