Design of Optimal Non-Uniform Quantizer in Imperfect Noisy Reporting Channels for Collaborative Spectrum Sensing

We design an optimal non-uniform quantizer for collaborative spectrum sensing (CSS) in cognitive radio networks (CRNs). We assume non-ideal reporting channels are and consist of additive white Gaussian noise (AWGN). To design the optimum quantization at the transmitter, we minimize the mean square e...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2020-11, Vol.69 (11), p.12870-12882
Main Authors: Naderipour, Masoumeh, Taherpour, Amirhossein, Taherpour, Abbas, Gazor, Saeed
Format: Article
Language:English
Subjects:
AWGN channels
Cascading style sheets
Channel noise
Channels
Codes
Cognitive radio
Cognitive radio networks
Collaboration
collaborative spectrum sensing
Counters
Decision making
distributed signal processing
Measurement
MMSE estimation
Noise
Noise measurement
non-uniform quantization
Optimization
Quantization (signal)
Random noise
Sensors
Signal to noise ratio
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Summary:We design an optimal non-uniform quantizer for collaborative spectrum sensing (CSS) in cognitive radio networks (CRNs). We assume non-ideal reporting channels are and consist of additive white Gaussian noise (AWGN). To design the optimum quantization at the transmitter, we minimize the mean square error (MMSE) at the receiver. The local data at each secondary user (SU) is quantized and transmitted via an AWGN reporting channel. Then, quantized symbols are received and decoded at the fusion center (FC) by a maximum a-posteriori probability (MAP) rule and, the final collaborative decision is made. By this method, a prediction is done for representation points of the quantizer and moreover, quantization and reporting channel noises are minimized, simultaneously. In addition, by taking into account the reporting channel noise in quantizer design, detection performance will be adaptive to change of signal to noise ratio (SNR) in the reporting channel. The simulation results demonstrate the superiority of the proposed quantizer compared to different quantizers in practical noisy reporting channels.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2020.3015219