Compara mètodes

	Equalització Zero-Forcing (ZF) i Minimum Mean-Square Error (MMSE)	Teorema de la Capacitat del Canal de Shannon
Camp	Telecomunicacions	Telecomunicacions
Família	Process / pipeline	Process / pipeline
Any d'origen	1974	1948
Autor original	Saleh Mansour and Paul Zervos	Claude Shannon
Tipus	linear equalization algorithm	fundamental theoretical bound
Font seminal	Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill.	Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
Àlies	channel equalization, interference cancellation	channel capacity, information theory bound
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.	Shannon's channel capacity theorem, published in 1948, establishes the maximum rate at which information can be reliably transmitted over a noisy channel. Expressed as C = B log2(1 + S/N) for additive white Gaussian noise (AWGN), it is a fundamental bound in information theory and communications engineering. Shannon proved that reliable communication is possible at any rate below capacity, and impossible above it. This theorem underpins the design of all modern communication systems and motivates coding theory, modulation, and signal processing techniques.