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Zero-Forcing og Minimum Mean-Square Error Equalization×Shannon Kanal Kapacitetsteorem×
FagområdeTelekommunikationTelekommunikation
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår19741948
OphavspersonSaleh Mansour and Paul ZervosClaude Shannon
Typelinear equalization algorithmfundamental theoretical bound
Oprindelig kildeProakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill. link ↗Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423. DOI ↗
Aliasserchannel equalization, interference cancellationchannel capacity, information theory bound
Relaterede55
ResuméZero-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.
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ScholarGateSammenlign metoder: ZF/MMSE Equalization · Shannon Capacity. Hentet 2026-06-17 fra https://scholargate.app/da/compare