New Insights into Channel vs Subspace Codes for Large-Scale Beamspace MIMO Channel Sensing
2026-04-23T08:51:39Z•5aac64f71bcb2e48fcdd43b4e525269a2a09aae68727741c187856db3d16be05
BPSKDU-PSISTAGauss–MarkovGolomb rulersISTALSTMXL-MIMOalgebraic signal processingbeamspace MIMOchannel sensingconvolutional beamspacesdeep unfoldingdenoising diffusiondiffusion modelsgroup theoryinvariant transformslocalization dataset','HYMN','multi-technology positioning','Wi‑mobility modelingmulti-scale attentionnoncoherent decodingoptical wireless communicationsketchingsparse recoverysubspace codeswideband channel estimation
What happened
This document is an arXiv eess-sp feed (April 23, 2026) containing multiple new papers across wireless communications and signal processing. Key contributions include: (1) analysis of channel vs. subspace codes for single-RF nonadaptive beamspace MIMO sensing, deriving exact subspace-distance expressions for binary linear (BPSK-mapped) codes, showing Hamming distance alone is insufficient and proposing sparse-antenna (Golomb-ruler) beamspace subspace codes and convolutional beamspaces for sample- and hardware-efficient sensing; (2) a hybrid Gauss–Markov + LSTM mobility model for indoor optical
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 5aac64f71bcb2e48fcdd43b4e525269a2a09aae68727741c187856db3d16be05
- Enrichment time
- 2026-04-23T08:51:39Z
- AI-assisted enrichment
- Yes
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