2021/05/26 by M. Gupta, Gupta, M., S. Sharma +5
Computer Science · Engineering · #Advanced Adaptive Filtering Techniques #FOS: Electrical engineering #Signal Processing (eess.SP) #Sparse and Compressive Sensing Techniques #Speech and Audio Processing #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2105.12693
openalex publication_date 2021/05/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The deployment of cellular spectrum in licensed, shared and unlicensed spectrum demands wideband sensing over non-contiguous sub-6 GHz spectrum. To improve the spectrum and energy efficiency, beamforming and massive multi-antenna systems are being explored which demand spatial sensing i.e. blind identification of vacant frequency bands and direction-of-arrival (DoA) of the occupied bands. We propose a reconfigurable architecture to perform spatial sensing of multi-band spectrum digitized via wideband radio front-end comprising of the sparse antenna array (SAA) and Sub-Nyquist Sampling (SNS). The proposed architecture comprises SAA pre-processing and algorithms to perform spatial sensing directly on SNS samples. The proposed architecture is realized on Zynq System on Chip (SoC), consisting of the ARM processor and FPGA, via hardware-software co-design (HSCD). Using the dynamic partial reconfiguration (DPR), on-the-fly switching between algorithms depending on the number of active signals in the sensed spectrum is enabled. The functionality, resource utilization, and execution time of the proposed architecture are analyzed for various HSCD configurations, word-length, number of digitized samples, signal-to-noise ratio (SNR), and antenna array (sparse/non-sparse).