PN Code Acquisition Using Belief Propagation with Adaptive Parity Check Matrix
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Pseudonoise (PN) code acquisition technique based on iterative message passing algorithm (iMPA) has been proposed due to its short acquisition time and low complexity. However, the cyclic and regular nature of constructed tanner graph makes it difficult to achieve promising performance. To address this problem, this correspondence proposes a new message passing algorithm based on adaptive parity check matrix. We find multiple sets of linear sparse constraints for PN sequence by squaring the generator polynomial. The topology of the graphic models as well as the parity check matrix is adapted every a few iterations to avoid local optima. The performance of proposed algorithm is evaluated in terms of detection probability. Simulation results show that this method provides more than 3 dB gains over iMPA with fixed parity check matrix.
KeywordsPN code acquisition Belief propagation (BP) Adaptive parity check matrix
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