Methoden vergleichen

	Zero-Forcing (ZF) und Minimum Mean-Square Error (MMSE) Equalization	Turbo-Codierung mit iterativem Dekodieren
Fachgebiet	Telekommunikation	Telekommunikation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1974	1993
Urheber	Saleh Mansour and Paul Zervos	Claude Berrou, Alain Glavieux, and Punya Thitimajshima
Typ	linear equalization algorithm	iterative error-correcting code
Wegweisende Quelle	Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill.	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.
Aliasnamen	channel equalization, interference cancellation	iterative decoding, concatenated codes
Verwandt	5	5
Zusammenfassung	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.