Compara mètodes

	Múltiple Entrada Múltiple Salida (MIMO)	Ortogonal Frequency Division Multiplexing (OFDM)	Equalització Zero-Forcing (ZF) i Minimum Mean-Square Error (MMSE)
Camp	Telecomunicacions	Telecomunicacions	Telecomunicacions
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	1995	1971	1974
Autor original	Telatar, Foschini, and Gans	Weinstein and Ebert	Saleh Mansour and Paul Zervos
Tipus	spatial multiplexing technique	multicarrier modulation scheme	linear equalization algorithm
Font seminal	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.
Àlies	spatial multiplexing, antenna diversity	multicarrier modulation	channel equalization, interference cancellation
Relacionats	5	5	5
Resum	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.