ArticleSensors (Basel, Switzerland)2026
LC-SVC: A Low-Complexity Sparse Vector Coding Scheme for Reliable Short-Packet Transmission in MIMO-Based Wireless Sensor Systems.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Reliable short-packet transmission is essential for MIMO-based wireless sensor systems, where low-power terminals upload short data blocks to multi-antenna gateways under stringent latency and complexity constraints. Although multi-antenna combining improves the equivalent received signal-to-noise ratio, the post-combining recovery of sparse-vector-coded packets is still limited by the high inter-column correlation of short binary spreading matrices and redundant searches over invalid indices in conventional orthogonal matching pursuit. To address these issues, this paper proposes a low-complexity sparse vector coding scheme for reliable short-packet transmission in MIMO-based wireless sensor systems. Specifically, at the transmitter, a low-coherence binary spreading matrix (LCB-SM) construction algorithm is designed based on Hadamard initialization and column-wise correlation optimization, which improves the distinguishability of sparse support positions while preserving multiplication-free encoding. At the receiver, a frozen-index-pruned orthogonal (FIP-OMP) matching pursuit algorithm is developed to exploit the predefined sparse mapping rule, thereby excluding invalid indices during atom selection and reducing noise-induced false support detection. Simulation results show that, for N=24, Ls=16, and K=2, the LCB-SM achieves a signal-to-noise (SNR) ratio gain of approximately 1.2 dB over the optimized partial hadamard matrix (OPHM) at a BLER of 10-2; for K=3, it reduces the high-SNR BLER by more than two orders of magnitude compared with OPHM. Meanwhile, the FIP-OMP achieves an approximately 0.5-0.8 dB gain over conventional orthogonal matching pursuit at a BLER of 10-2 with an average decoding time close to that of orthogonal matching pursuit (OMP) and much lower than that of multipath matching pursuit, Dynamic OMP and compressive sampling matching pursuit. A software defined radio-based wireless experiment further validates the reconstruction capability of LC-SVC for continuous sensing data, achieving an RMSE of 0.0612. These results demonstrate that LC-SVC improves the reliability of the considered short-packet recovery task with lightweight transmitter-side encoding and low gateway-side decoding overhead.
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