方法对比

	Alamouti时空分组码	低密度奇偶校验码 (LDPC)	多输入多输出 (MIMO)	香农信道容量定理
领域	电信	电信	电信	电信
方法族	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	1998	1962	1995	1948
提出者	Siavash Alamouti	Robert Gallager	Telatar, Foschini, and Gans	Claude Shannon
类型	space-time coding scheme	linear error-correcting code	spatial multiplexing technique	fundamental theoretical bound
开创性文献	Alamouti, S. M. (1998). A simple transmit diversity technique for wireless communications. IEEE Journal on Selected Areas in Communications, 16(8), 1451-1458.	Gallager, R. G. (1962). Low-density parity-check codes. IRE Transactions on Information Theory, 8(1), 21-28.	Telatar, I. (1999). Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 10(6), 585-595.	Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
别名	space-time coding, transmit diversity	sparse codes, belief propagation codes	spatial multiplexing, antenna diversity	channel capacity, information theory bound
相关	5	5	5	5
摘要	The Alamouti code is an elegant space-time coding scheme that provides full transmit diversity using two antennas and a simple linear receiver. Introduced by Siavash Alamouti in 1998, it requires no channel state information at the transmitter, achieves the same bit-error rate as a single-antenna system with receiver diversity, and uses linear processing for decoding. The Alamouti code has become the de facto standard for transmit diversity in cellular systems and is adopted in LTE, WiFi, and many 5G protocols.	LDPC codes, invented by Robert Gallager in 1962 and rediscovered in the 1990s by MacKay, are linear error-correcting codes defined by sparse parity-check matrices. They achieve performance within 0.4 dB of the Shannon limit with iterative belief-propagation decoding and have become the standard for modern wireless (WiFi-6, 5G NR, Digital Video Broadcasting). Unlike turbo codes, LDPC codes have a more elegant graph-theoretic structure and more mature theoretical analysis.	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.