Methoden vergleichen

	Low-Density Parity-Check Codes (LDPC)	Multiple-Input Multiple-Output (MIMO)	Satz von der Kanalkapazität nach Shannon
Fachgebiet	Telekommunikation	Telekommunikation	Telekommunikation
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Entstehungsjahr	1962	1995	1948
Urheber	Robert Gallager	Telatar, Foschini, and Gans	Claude Shannon
Typ	linear error-correcting code	spatial multiplexing technique	fundamental theoretical bound
Wegweisende Quelle	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.
Aliasnamen	sparse codes, belief propagation codes	spatial multiplexing, antenna diversity	channel capacity, information theory bound
Verwandt	5	5	5
Zusammenfassung	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.