手法を比較

	Multiple-Input Multiple-Output (MIMO)	レイ・トレーシング伝搬モデル	シャノンチャネル容量定理
分野	通信工学	通信工学	通信工学
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	1995	1993	1948
提唱者	Telatar, Foschini, and Gans	Maciel, Bertoni, and Xia	Claude Shannon
種類	spatial multiplexing technique	deterministic propagation algorithm	fundamental theoretical bound
原典	Telatar, I. (1999). Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 10(6), 585-595.	Maciel, T. F., Bertoni, H. L., & Xia, H. H. (1993). Unified approach to prediction of propagation over buildings for all ranges of frequencies. IEEE Transactions on Vehicular Technology, 42(1), 41-45.	Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
別名	spatial multiplexing, antenna diversity	deterministic propagation, site-specific modeling	channel capacity, information theory bound
関連	5	4	5
概要	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.	Ray tracing is a deterministic propagation modeling technique for predicting electromagnetic field strength at specific locations. Instead of empirical formulas (like Okumura-Hata), ray tracing traces paths of electromagnetic energy as it reflects, diffracts, and scatters off buildings and terrain. With accurate 3D geometry and material properties, ray tracing predicts site-specific path loss, multipath delay profiles, and angle of arrival, making it ideal for detailed coverage planning, interference analysis, and system design. Ray tracing is now standard in professional cellular planning tools.	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.