Abstract
In this paper, we propose a near maximum likeli- hood (ML) estimator of channel and signal parameters for block turbo coded slow frequency-hopped spread spectrum (SFH-SS) systems under jamming environments. The estimated parameters and the jamming states are employed in the soft-in/soft-out (SISO) decoding, while two types of jammers, partial-band noise jammer (PBNJ) and band multitone jammer (BMTJ) are considered. Our approach is to determine the jamming state for each hop and refine the desired parameters from the proposed estimator to obtain the optimum detection. Besides, the optimum decoding metric is derived as well. Simulation results show that our estimator needs hundreds of samples to be converged. The system performance with estimated channel parameters and perfect channel parameters under two types of jamming environments has also been illustrated in terms of signal-to-noise (SNR) ratio.
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