arXiv subjects

Robert Qiu

Publications and source records attributed to Robert Qiu.

22 records · Page 2Linked to original sources

arXiv2011

Demonstration of Spectrum Sensing with Blindly Learned Feature

Spectrum sensing is essential in cognitive radio. By defining leading \textit{eigenvector} as feature, we introduce a blind feature learning algorithm (FLA) and a feature template matching (FTM) algorithm using learned feature for spectrum sensing. We implement both algorithms on Lyrtech software defined radio platform. Hardware experiment is performed to verify that feature can be learned blindly. We compare FTM with a blind detector in hardware and the results show that the detection performance for FTM is about 3 dB better.

cs.IT↗

arXiv2011

Spectrum Sensing Based on Blindly Learned Signal Feature

Spectrum sensing is the major challenge in the cognitive radio (CR). We propose to learn local feature and use it as the prior knowledge to improve the detection performance. We define the local feature as the leading eigenvector derived from the received signal samples. A feature learning algorithm (FLA) is proposed to learn the feature blindly. Then, with local feature as the prior knowledge, we propose the feature template matching algorithm (FTM) for spectrum sensing. We use the discrete Karhunen--Lo{è}ve transform (DKLT) to show that such a feature is robust against noise and has maximum effective signal-to-noise ratio (SNR). Captured real-world data shows that the learned feature is very stable over time. It is almost unchanged in 25 seconds. Then, we test the detection performance of the FTM in very low SNR. Simulation results show that the FTM is about 2 dB better than the blind algorithms, and the FTM does not have the noise uncertainty problem.

cs.IT↗

arXiv2011

Cooperative Wideband Spectrum Sensing for the Centralized Cognitive Radio Network

Various primary user (PU) radios have been allocated into fixed frequency bands in the whole spectrum. A cognitive radio network (CRN) should be able to perform the wideband spectrum sensing (WSS) to detect temporarily unoccupied frequency bands. We summarize four occupancy features for the frequency bands. 1. The occupancy is sparse; 2. The frequency band allocation information is fixed and common; 3. There are three categories for the frequency band usages; 4. The occupied frequency bands are common in the CRN. For the first time, we consider all features as the prior knowledge in the compressed sensing based cooperative WSS (CWSS) algorithm design for a centralized CRN. We propose a modified orthogonal matching pursuit (Mod-OMP) algorithm and a modified simultaneous orthogonal matching pursuit (Mod-SOMP) algorithm for the CWSS. We compare the CWSS performance of Mod-OMP/Mod-SOMP with the original OMP/SOMP and show the performance improvements.

cs.IT↗

arXiv2011

Modified Orthogonal Matching Pursuit Algorithm for Cognitive Radio Wideband Spectrum Sensing

Sampling rate is the bottleneck for spectrum sensing over multi-GHz bandwidth. Recent progress in compressed sensing (CS) initialized several sub-Nyquist rate approaches to overcome the problem. However, efforts to design CS reconstruction algorithms for wideband spectrum sensing are very limited. It is possible to further reduce the sampling rate requirement and improve reconstruction performance via algorithms considering prior knowledge of cognitive radio spectrum usages. In this paper, we group the usages of cognitive radio spectrum into three categories and propose a modified orthogonal matching pursuit (OMP) algorithm for wideband spectrum sensing. Simulation results show that this modified OMP algorithm outperforms two modified basis pursuit de-noising (BPDN) algorithms in terms of reconstruction performance and computation time.

cs.IT↗