Compara mètodes

	Equalització Zero-Forcing (ZF) i Minimum Mean-Square Error (MMSE)	Codificació Turbo amb Descòdificació Iterativa
Camp	Telecomunicacions	Telecomunicacions
Família	Process / pipeline	Process / pipeline
Any d'origen	1974	1993
Autor original	Saleh Mansour and Paul Zervos	Claude Berrou, Alain Glavieux, and Punya Thitimajshima
Tipus	linear equalization algorithm	iterative error-correcting code
Font seminal	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.
Àlies	channel equalization, interference cancellation	iterative decoding, concatenated codes
Relacionats	5	5
Resum	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.