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ゼロフォーシング(ZF)および最小二乗誤差(MMSE)等化×反復復号化によるターボ符号化×
分野通信工学通信工学
系統Process / pipelineProcess / pipeline
提唱年19741993
提唱者Saleh Mansour and Paul ZervosClaude Berrou, Alain Glavieux, and Punya Thitimajshima
種類linear equalization algorithmiterative error-correcting code
原典Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill. link ↗Berrou, C., Glavieux, A., & Thitimajshima, P. (1993). Near Shannon limit error-correcting coding and decoding: Turbo-codes. In Proceedings of the IEEE International Conference on Communications (ICC), 1064-1070. DOI ↗
別名channel equalization, interference cancellationiterative decoding, concatenated codes
関連55
概要Zero-Forcing (ZF) and Minimum Mean-Square Error (MMSE) equalization are fundamental linear receiver algorithms for combating intersymbol interference in dispersive channels. Developed in the context of data transmission theory, these methods form the basis of modern channel equalization in wireless and wired systems. While ZF aggressively cancels interference, MMSE balances interference suppression with noise enhancement, making it the optimal linear solution under Gaussian noise.Turbo codes, introduced by Berrou, Glavieux, and Thitimajshima in 1993, are a landmark in channel coding history. They achieve performance within 0.5 dB of the Shannon limit—the theoretical boundary for reliable communication—a feat previously thought impossible with practical complexity. Turbo codes use concatenated convolutional codes with an interleaver and iterative decoding via belief propagation. They were adopted in 3G (UMTS) and remain important in 4G/5G systems alongside LDPC codes.
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ScholarGate手法を比較: ZF/MMSE Equalization · Turbo Code. 2026-06-15に以下より取得 https://scholargate.app/ja/compare