MIMO Capacity Enhancement by Grating Walls: A Physics-Based Proof of Principle
arXiv:2604.01786v1 Announce Type: new Abstract: This paper investigates the passive enhancement of MIMO spectral efficiency through boundary engineering in a simplified two dimensional indoor proof of principle model. The propagation channel is constructed from the electromagnetic Green's function of a room with boundaries modeled as free space, drywall, perfect electric conductor (PEC), or binary gratings. Within this framework, grating coated walls enrich the non line of sight (NLoS) multipath field, reduce channel correlation, and enhance spatial multiplexing over a broad range of receiver locations. Comparisons with the drywall and PEC reference cases further reveal that the observed capacity enhancement arises not from diffraction alone, but from the combined effects of effective wall
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Abstract:This paper investigates the passive enhancement of MIMO spectral efficiency through boundary engineering in a simplified two dimensional indoor proof of principle model. The propagation channel is constructed from the electromagnetic Green's function of a room with boundaries modeled as free space, drywall, perfect electric conductor (PEC), or binary gratings. Within this framework, grating coated walls enrich the non line of sight (NLoS) multipath field, reduce channel correlation, and enhance spatial multiplexing over a broad range of receiver locations. Comparisons with the drywall and PEC reference cases further reveal that the observed capacity enhancement arises not from diffraction alone, but from the combined effects of effective wall reflectivity, which confines and reradiates energy within the room, and diffraction induced angular redistribution, which enriches the channel eigenstructure.
Comments: 10 pages, 12 figures
Subjects:
Signal Processing (eess.SP)
Cite as: arXiv:2604.01786 [eess.SP]
(or arXiv:2604.01786v1 [eess.SP] for this version)
https://doi.org/10.48550/arXiv.2604.01786
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Xiaolu Yang [view email] [v1] Thu, 2 Apr 2026 08:55:40 UTC (6,229 KB)
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