Accurate channel state information (CSI) is crucial for reliable decoding over fading channels. In many existing works, the CSI acquisition relies greatly on accurate knowledge of the channel model information (CMI), which includes, in particular, the power spectrum of the fading process and the statistical distribution of the fading gain. In practice, it may be difficult to obtain or keep track of the CMI accurately. In this paper, we consider the decoding of Reed- Solomon convolutional concatenated (RSCC) codes over the quasi-static fading channel, and propose a robust, decision-directed, soft-output convolutional decoder which does not require explicit CSI acquisition. Simulation result shows that the proposed decoder has a lower bit-error rate for convolutional decoding than the conventional soft-output Viterbi algorithm and the BCJR algorithm with pilot-symbol-assisted channel estimation. The advantage of the former in terms of the accuracy of soft-decision output is demonstrated by the superiority of word-error performance in the RSCC decoding.
['Haifeng Yuan', 'Pooi Yuen Kam']
Robust Decoding of Concatenated RS-Convolutional Codes over the Quasi-Static Fading Channel with No Explicit CSI Acquisition