Double-detector for Sparse Signal Detection from One Bit Compressed Sensing Measurements
This work addresses signal detection in compressed sensing for applications like spectrum sensing, but it is incremental as it builds on existing one-bit methods by extending them to vector signals and adding a detector scheme.
The paper tackles sparse vector signal detection from one-bit compressed sensing measurements, extending previous scalar methods to vector cases and introducing a double-detector scheme that integrates sensor-level threshold detection with network-level GLRT, achieving performance close to oracle and clairvoyant detectors and comparable to energy detectors using only sign data.
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.