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Cân bằng Zero-Forcing và Sai số Bình phương Trung bình Tối thiểu×Kỹ thuật Đa đầu vào Đa đầu ra (MIMO)×Định lý dung lượng kênh Shannon×
Lĩnh vựcViễn thôngViễn thôngViễn thông
HọProcess / pipelineProcess / pipelineProcess / pipeline
Năm ra đời197419951948
Người khởi xướngSaleh Mansour and Paul ZervosTelatar, Foschini, and GansClaude Shannon
Loạilinear equalization algorithmspatial multiplexing techniquefundamental theoretical bound
Công trình gốcProakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill. link ↗Telatar, I. (1999). Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 10(6), 585-595. DOI ↗Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423. DOI ↗
Tên gọi khácchannel equalization, interference cancellationspatial multiplexing, antenna diversitychannel capacity, information theory bound
Liên quan555
Tóm tắtZero-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.MIMO is a technique that uses multiple transmit and receive antennas to significantly increase channel capacity and reliability. Pioneered theoretically by Telatar (1999) and Foschini & Gans (1998), MIMO exploits multipath propagation—typically a liability in wireless—as an asset by creating independent spatial channels. It is now fundamental to all modern wireless systems including LTE, WiFi-6, and 5G, where it provides both capacity gains through spatial multiplexing and robustness through diversity.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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ScholarGateSo sánh phương pháp: ZF/MMSE Equalization · MIMO · Shannon Capacity. Truy cập ngày 2026-06-18 từ https://scholargate.app/vi/compare