Modeling of non-Gaussian colored noise and application in CR multi-sensor networks

• Main Authors: Zheng Dou, Chengzhuo Shi, Yun Lin, Wenwen Li
• Format: Article
• Language: English
• Published: SpringerOpen 2017-11-01
• Series: EURASIP Journal on Wireless Communications and Networking
• Subjects: Non-Gaussian colored noise model; BP-FLOM; Estimation; Practical noise data; CR multi-sensor networks
• Online Access: http://link.springer.com/article/10.1186/s13638-017-0983-3

Abstract Motivated by the practical and accurate demand of intelligent cognitive radio (CR) sensor networks, a new modeling method of practical background noise and a novel sensing scheme are presented, where the noise model is the non-Gaussian colored noise based on α stable process and the sensing method is improved fractional low-order moment (FLOM) detection algorithm with balance parameter. First, we establish the non-Gaussian colored noise model through combining α-distribution with a linear system represented by a matrix. And a fitting curve of practical noise data is given to verify the validity of the proposed model. Then we present a parameter estimation method with low complexity to obtain the balance parameter, which is an important part of the detection algorithm. The balance parameter-based FLOM (BP-FLOM) detector does not require any a priori knowledge about the primary user signal and channels. Monte Carlo simulations clearly demonstrate the performance of the proposed method versus the generalized signal-to-noise ratio, the characteristic exponent α, and the number of detectors in sensing networks.