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ZF/MMSE Equalization׊enona kanāla ietilpības teorēma×
NozareTelekomunikācijasTelekomunikācijas
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads19741948
AutorsSaleh Mansour and Paul ZervosClaude Shannon
Tipslinear equalization algorithmfundamental theoretical bound
PirmavotsProakis, 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 ↗
Citi nosaukumichannel equalization, interference cancellationchannel capacity, information theory bound
Saistītās55
KopsavilkumsZero-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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ScholarGateSalīdzināt metodes: ZF/MMSE Equalization · Shannon Capacity. Izgūts 2026-06-18 no https://scholargate.app/lv/compare