Võrdle meetodeid

	Okumura-Hata signaalitee kahju ennustamise mudel	MIMO (Multiple-Input Multiple-Output)	Shannoni kanali võimsuse teoreem
Valdkond	Telekommunikatsioon	Telekommunikatsioon	Telekommunikatsioon
Perekond	Process / pipeline	Process / pipeline	Process / pipeline
Tekkeaasta	1968	1995	1948
Looja	Masahiro Okumura and Masahiro Hata	Telatar, Foschini, and Gans	Claude Shannon
Tüüp	empirical path loss model	spatial multiplexing technique	fundamental theoretical bound
Algallikas	Okumura, Y., Ohmori, E., Kawano, T., & Fukuda, K. (1968). Field strength and its variability in VHF and UHF land mobile radio service. Review of the Electrical Communication Laboratory, 16(9-10), 825-873.	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.
Rööpnimetused	path loss model, propagation prediction	spatial multiplexing, antenna diversity	channel capacity, information theory bound
Seotud	4	5	5
Kokkuvõte	The Okumura-Hata model is an empirical propagation model for predicting path loss in mobile radio systems. Developed by Okumura (1968) and mathematically formalized by Hata (1980), it is one of the most widely used models for cellular network planning. The model predicts median path loss as a function of frequency, distance, and antenna heights, with environment-specific correction factors. Despite its age, the Okumura-Hata model remains a standard in 2G/3G planning and is often used as a baseline for more sophisticated models.	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.