Double-detector for Sparse Signal Detection from One Bit Compressed Sensing Measurements

TL;DR

This paper introduces a double-detector scheme for sparse vector signal detection using one-bit compressed sensing, extending previous scalar detection methods to vector signals and demonstrating improved performance through simulations.

Contribution

It develops a novel double-detector approach combining sensor and network level detection, with optimal quantizer design for sparse vector signals from one-bit measurements.

Findings

Double-detector outperforms sign-GLRT in simulations

Performance close to oracle and clairvoyant detectors

Effective in spectrum sensing with only sign data

Abstract

This letter presents the sparse vector signal detection from one bit compressed sensing measurements, in contrast to the previous works which deal with scalar signal detection. In this letter, available results are extended to the vector case and the GLRT detector and the optimal quantizer design are obtained. Also, a double-detector scheme is introduced in which a sensor level threshold detector is integrated into network level GLRT to improve the performance. The detection criteria of oracle and clairvoyant detectors are also derived. Simulation results show that with careful design of the threshold detector, the overall detection performance of double-detector scheme would be better than the sign-GLRT proposed in [1] and close to oracle and clairvoyant detectors. Also, the proposed detector is applied to spectrum sensing and the results are near the well known energy detector which uses the real valued data while the proposed detector only uses the sign of the data.