Adaptive Compressed Wideband Spectrum Detection Based on Optimized Measurement Matrix
Yongle Yu, Zhengbao Zhang, Chao Guo, Gaofeng Fan
Available Online May 2017.
- https://doi.org/10.2991/icmeit-17.2017.117How to use a DOI?
- cognitive radio, compressed sensing, spectrum detection, measurement matrix.
- The emergence of compressed sensing technology brought a revolutionary opportunity to wideband spectrum sensing, which could be used to reduce the sampling rate and reconstruct the sparse spectrum. In combination of measurement matrix optimization and adaptive process of compressive sampling, a modified adaptive compressed wideband spectrum sensing algorithm is proposed. In this paper, the column vector autocorrelation of the observation matrix was reduced, and the impact of optimized matrix on reconstruction algorithm was analyzed. The simulation results show that the proposed algorithm has a lower mean square error (MSE) than that of the traditional algorithm, and the detection probability is higher at the same number of observations.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yongle Yu AU - Zhengbao Zhang AU - Chao Guo AU - Gaofeng Fan PY - 2017/05 DA - 2017/05 TI - Adaptive Compressed Wideband Spectrum Detection Based on Optimized Measurement Matrix BT - 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icmeit-17.2017.117 DO - https://doi.org/10.2991/icmeit-17.2017.117 ID - Yu2017/05 ER -