In this paper, we investigate the weighted iterative decoding to improve the performance of turbo-polar code. First of all, a minimum weighted mean square error criterion is proposed to optimize the scaling factors(SF...In this paper, we investigate the weighted iterative decoding to improve the performance of turbo-polar code. First of all, a minimum weighted mean square error criterion is proposed to optimize the scaling factors(SFs). Secondly, for two typical iterative algorithms,such as soft cancellation(SCAN) and belief propagation(BP) decoding, genie-aided decoders are proposed as the ideal reference of the practical decoding. Guided by this optimization framework, the optimal SFs of SCAN or BP decoders are obtained. The bit error rate performance of turbo-polar code with the optimal SFs can achieve 0.3 dB or 0.7 dB performance gains over the standard SCAN or BP decoding respectively.展开更多
A reduced-complexity detection algorithm is proposed, which is applied to iterative receivers for multiple-input multiple-output （MIMO） systems. Unlike the exhaustive search over all the possible trans-mitted symbol...A reduced-complexity detection algorithm is proposed, which is applied to iterative receivers for multiple-input multiple-output （MIMO） systems. Unlike the exhaustive search over all the possible trans-mitted symbol vectors of the optimum maximum a posteriori probability （MAP） detector, the new algo-rithm evaluates only the symbol vectors that contribute significantly to the soft output of the detector. The algorithm is facilitated by carrying out the breadth-first search on a reconfigurable tree, constructed by computing the symbol reliability of each layer based on zero-forcing criterion and reordering the symbols according to the symbol reliabilities. Simulations are presented and the good performance of the new algo-rithm over a quasi-static Rayleigh channel even for relatively small list sizes are proved.展开更多
基金supported by the National Natural Science Foundation of China(No.61671080)the National Natural Science Foundation of China(No.61771066)Nokia Beijing Bell Lab
文摘In this paper, we investigate the weighted iterative decoding to improve the performance of turbo-polar code. First of all, a minimum weighted mean square error criterion is proposed to optimize the scaling factors(SFs). Secondly, for two typical iterative algorithms,such as soft cancellation(SCAN) and belief propagation(BP) decoding, genie-aided decoders are proposed as the ideal reference of the practical decoding. Guided by this optimization framework, the optimal SFs of SCAN or BP decoders are obtained. The bit error rate performance of turbo-polar code with the optimal SFs can achieve 0.3 dB or 0.7 dB performance gains over the standard SCAN or BP decoding respectively.
基金Supported by the National Natural Science Foundation of China （No.60332030, 60572157） and the High Technology Research and Development Pro-gramme of China （No.2003AA123310）.
文摘A reduced-complexity detection algorithm is proposed, which is applied to iterative receivers for multiple-input multiple-output （MIMO） systems. Unlike the exhaustive search over all the possible trans-mitted symbol vectors of the optimum maximum a posteriori probability （MAP） detector, the new algo-rithm evaluates only the symbol vectors that contribute significantly to the soft output of the detector. The algorithm is facilitated by carrying out the breadth-first search on a reconfigurable tree, constructed by computing the symbol reliability of each layer based on zero-forcing criterion and reordering the symbols according to the symbol reliabilities. Simulations are presented and the good performance of the new algo-rithm over a quasi-static Rayleigh channel even for relatively small list sizes are proved.
