AI & ML
Channel orthogonalization via movable antennas
arXiv eess.SP0 views
arXiv:2610.32606v1 Announce Type: new Abstract: This paper investigates the orthogonalization of far-field multiuser channels through the optimal positioning of the antennas constituting an array. To solve the ensuing continuous geometry optimization problem, a graph-theoretic framework is introduced that maps pairwise user channel correlations to graph edges, translating channel orthogonalization into a discrete graph-covering problem on a complete graph. The minimum number of array antennas required for orthogonalization is established for 1D, 2D, and 3D array geometries, and a binary linear program is formulated that identifies the most compact array attaining such orthogonality. The graph framework is also shown to accommodate null-steering scenarios and multipath channels. Furthermore, a fundamental tradeoff is revealed whereby relaxing exact orthogonality to near-orthogonality reduces the antenna count at the expense of a less compact array, and a method is presented to enforce minimum antenna spacings without sacrificing orthogonality.
Source:https://arxiv.org/abs/2610.32606PreviousAn Evidence-Guided Framework for Tissue-Barrier Impedance Review: Deletion and Resistance SensitivityNextEMG Tokenization Preserves Movement Information at a Fraction of the Bitrate
Related posts
Ballot Rejections Have Soared in Rural Counties as USPS Reduces Mail Service
0Hacker News
Cloudflare DNS Zone Builder cuts peak memory 85% and halves build delay
0dev.to News
O dia em que a cliente pediu desconto num bolo de pistache (e pagou R$ 30 num cafe)
0dev.to Design
O telefone tocou as 19h: Por que cancelam seu contrato primeiro na crise?
0dev.to Design
Which Cursor model is best for everyday work?
0dev.to Productivity
Is AI going to get cheaper or more expensive?
0dev.to Machine Learning