Title :
Multiple hypothesis testing for compressive wideband sensing
Author :
Chepuri, Sundeep Prabhakar ; Leus, Geert ; De Francisco, Ruben
Author_Institution :
Fac. of Electr. Eng., Delft Univ. of Technol., Delft, Netherlands
Abstract :
The classical Compressive Sensing (CS) techniques for wideband spectral sensing consist of a two-stage estimation detection approach. A novel approach is proposed to solve the detection problem directly from observations with incomplete frequency information, for e.g., signals acquired using sub-Nyquist rate sampling. The wideband occupancy detection problem is formulated as a multiple hypothesis testing problem under a non-Bayesian framework, and a Neyman-Pearson-like criterion is proposed. The detector based on exhaustive search performs better than the conventional CS based techniques. However, it is impractical for large block sizes. Hence, we propose a sub-optimal greedy algorithm whose complexity and performance can be traded-off by construction.
Keywords :
compressed sensing; computational complexity; greedy algorithms; search problems; signal detection; spectral analysis; statistical testing; CS technique; Neyman-Pearson-like criterion; compressive wideband sensing; exhaustive search; incomplete frequency information; multiple hypothesis testing problem; nonBayesian framework; suboptimal greedy algorithm; two-stage estimation detection; wideband occupancy detection problem; wideband spectral sensing; Complexity theory; Detectors; Signal to noise ratio; Vectors; Wideband;
Conference_Titel :
Signal Processing Advances in Wireless Communications (SPAWC), 2012 IEEE 13th International Workshop on
Conference_Location :
Cesme
Print_ISBN :
978-1-4673-0970-7
DOI :
10.1109/SPAWC.2012.6292978