On the exact convolution of discrete random variables
Applied Mathematics and Computation
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Autocorrelation-based decentralized sequential detection of OFDM signals in cognitive radios
IEEE Transactions on Signal Processing
On the optimality of the binary reflected Gray code
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Algorithms for computing the distributions of sums of discrete random variables
Mathematical and Computer Modelling: An International Journal
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This paper analyzes the effect of quantization and channel errors on the performance of collaborative spectrum sensing in cognitive radios. Each secondary user (SU) employs a simple and computationally efficient autocorrelation-based detector for Orthogonal Frequency Division Multiplexing (OFDM) signals of the primary user (PU). The local decision statistics in the form of log-likelihood ratio (LLR) from individual detectors are quantized and sent to the fusion center (FC). The statistical properties of the decision statistics in the presence of quantization are established. The quantized decision statistics are sent through a channel that may cause errors. The effect of channel errors is incorporated in the analysis through Bit Error Probability (BEP). The detection performance at the fusion center is studied using analytical tools and simulations.