Browsing by Author "Jia, Jia"

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    Impulsive noise suppression in modern communication systems
    (University of New Brunswick, 2015) Jia, Jia; Julian Meng
    Compared to additive white Gaussian noise (AWGN), impulsive noise has unique characteristics which include random occurrence, short time duration, wide band spectrum, and high-energy content. Due to these distinctive features, impulsive noise with significant power can degrade the transmission quality of various communication systems. In this research, the impact of impulsive noise on Orthogonal Frequency-Division Multiplexing (OFDM)-based communication systems and ZigBee wireless sensor networks (WSNs) based on direct sequence spread spectrum (DSSS) modulation are addressed. For the purpose of improving system performance, several impulsive noise suppression approaches are proposed for both of the two communication systems mentioned above. First, this research proposes a novel time domain filtering approach for both OFDM and DSSS modulation with the aid of Reed-Solomon (RS) coding and noise estimation to mitigate the influence of impulsive noise on the transmitted signal. This filter utilizes a composite comparison value (CCV) algorithm to improve the accuracy of impulsive noise detection. Performance comparisons with previously proposed filtering and coding methods demonstrate the effectiveness of the CCV filter. In the second case, we describe a new Error-Balanced Wavelet (EB-Wavelet) filtering process for the impulsive noise suppression in ZigBee-based WSNs utilizing DSSS modulation. Theoretical analysis shows that the bit error rate (BER) of ZigBee systems is related to the received noise power and any filter generated distortion. The EB-Wavelet filter employs a multiresolution analysis and weighting matrix for bandwidth management to limit the presence of impulsive noise power while balancing the overall filter distortion. Computer simulations are performed to compare the performance of the proposed EB-Wavelet approach with conventional finite impulse response filters. Results show that the EB-Wavelet filter can further improve the BER performance of ZigBee systems in the presence of significant impulsive noise while maintaining a low complexity of ZigBee receiver design. Additionally, in this dissertation, the impulsive noise performances of 915 MHz and 2.4 GHz band ZigBee communication systems are compared. A novel impulsive noise model based on the statistical characteristics of the impulsive noise measured in electricity substations is proposed and utilized for the comparison procedure. Both theoretical and simulation results show the advantage of deploying the 2.4 GHz band ZigBee in impulsive noise environments in order to enhance transmission quality. However, it may be possible to deploy the 915 MHz band ZigBee for partial discharge fault monitoring in related environments.