Spectrum Data Compression for Cognitive Radio Network

Abstract

Incognitive radio systems, interactive perception spectrum data between cognitive users can effectively improve the overall performance of the user’s perception of communication. However, a large number of spectrum data accumulation will increasing the consumption of resources during interaction In, lack of effective spectrum data compression algorithm cognition become a bottleneck restricting the collaboration. This paper presents a wideband spectrum data compression algorithm based on the energy detection and sliding window, removing redundant information of noise, compressing the detail of signal with different weights, reserving useful information, improving the compression ratio and reducing compression loss. In addition, the algorithm retains the spectrum details of the signal by the DWT transform in the case of a high compression ratio, and those details are propitious to spectrum analysis. Especially under low occupancy ratio circumstances, experimental results show that the compression performance of this algorithm increase several times compare to DCT and JPEG2000.