An electromagnetic random field theoretic framework for capacity analysis of fluctuating communication channels

Abstract We propose a numerical method grounded in electromagnetic random field theory (EM-RFT) for characterizing and modeling random fields in electromagnetics, with future applications to information transmission and processing. By combining EM Green’s functions with the Karhunen–Loève (KL) expansion, the method enables efficient estimation of spatially continuous EM random fields through a finite set of fundamental KL modes. The key idea in EM-RFT is the use of EM Green’s functions to avoid separate KL expansions for each field or current; once the system response is determined, input information fields can be propagated to generate consistent random field models. Building upon this formulation, we further construct stochastic transmitter–scatterer–receiver configurations and analyze the channel capacity, enabling the modeling of random propagation environments. This unified framework provides physics-based analysis of dense-aperture information fields and evaluation of capacity over arbitrary continuous regions, establishing a computational foundation for future studies of realistic cMIMO channels through a synthesis of EM theory and information-theoretic principles.