Methoden vergleichen

	Multiple-Input Multiple-Output (MIMO)	Orthogonales Frequenzmultiplexverfahren (OFDM)	Zero-Forcing (ZF) und Minimum Mean-Square Error (MMSE) Equalization
Fachgebiet	Telekommunikation	Telekommunikation	Telekommunikation
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Entstehungsjahr	1995	1971	1974
Urheber	Telatar, Foschini, and Gans	Weinstein and Ebert	Saleh Mansour and Paul Zervos
Typ	spatial multiplexing technique	multicarrier modulation scheme	linear equalization algorithm
Wegweisende Quelle	Telatar, I. (1999). Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 10(6), 585-595.	Weinstein, S. B., & Ebert, P. M. (1971). Data transmission by frequency-division multiplexing using the discrete Fourier transform. IEEE Transactions on Communication Technology, 19(5), 628-634.	Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill.
Aliasnamen	spatial multiplexing, antenna diversity	multicarrier modulation	channel equalization, interference cancellation
Verwandt	5	5	5
Zusammenfassung	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.	OFDM is a multicarrier modulation technique that divides a wideband channel into many narrowband orthogonal subcarriers. Introduced by Weinstein and Ebert in 1971, it exploits the duality between time and frequency domains to efficiently use spectrum while mitigating intersymbol interference in frequency-selective channels. OFDM is now the standard for high-speed wireless systems including WiFi, cellular LTE, and digital broadcasting.	Zero-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.