Stochastic Electromagnetic Correlation Green’s Functions for Wireless Communications—Part II: Computational Models and Applications

This paper provides comprehensive numerical validation of the source-based stochastic electromagnetic (EM) correlation framework established in Part I. The alternative reciprocity theorem is rigorously verified against method of moments benchmarks, demonstrating that the reciprocity-based formulation accurately captures the physical response of coupled antenna arrays and revealing the current intensity hierarchy in which self-current corrections and cross-antenna induced currents introduce non-negligible pathways for correlation. Two stochastic source generation methodologies are introduced: the random spherical surface sprinkling scheme, which successfully reproduces far-field (FF) correlation results consistent with the Clarke-Jakes power angle spectrum, and the random spherical volume sprinkling scheme, which models sources within bounded scattering clusters for near-field (NF) analysis. Utilizing these schemes, the numerical simulations confirm that NF correlation behavior is fundamentally distinct from FF predictions, exhibiting strong dependence on source distance, frequency, and cluster geometry, with the NF contribution retaining considerable strength even at the NF-FF boundary. The correlation Green’s function-derived correlation matrices are incorporated into a Kronecker channel model to evaluate system-level multiple-input multiple-output (MIMO) performance metrics, including average effective degree of freedom and ergodic capacity, revealing that NF source statistics, array size, element polarization, and mixed NF/FF distributions can reshape the channel eigenvalue structure and affect spatial multiplexing capability. The impact of EM mutual coupling on cross-correlation is rigorously quantified through a nine-term decomposition, showing that mutual coupling contributes 80%–90% of the total cross-correlation in NF configurations and remains substantial even in the FF regime, with self-interaction terms dominating the contribution. The system-level analysis further reveals that mutual coupling is not universally detrimental: Depending on array spacing and NF source statistics, it can either degrade or partially improve the available spatial eigenchannels. By providing rigorous numerical confirmation of the theoretical framework, this work establishes a physics-compliant foundation for cross-correlation analysis in MIMO systems, underscoring the necessity of incorporating NF and mutual coupling effects for accurate performance prediction and optimization of next-generation wireless systems.