Overlapped x domain multiplexing(OVXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing inter-symbol interference(ISI) intelligently. However, the computational complexity of maximum ...Overlapped x domain multiplexing(OVXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing inter-symbol interference(ISI) intelligently. However, the computational complexity of maximum likelihood sequence detection(MLSD) increases exponentially with the growth of spectral efficiency in OVXDM, which is unbearable for practical implementations. In this paper, based on a novel path metric associating adjacent symbols, we propose a multi-bit sliding stack decoding(Multi-Bit SSD) algorithm to achieve multiple-bit decoding simultaneously in OVXDM. Theoretical analysis is provided for the algorithm, which indicates the relationship between the performance and parameters including multiplexing waveform, overlapping fold and sliding window size. Simulation results show that the proposed algorithm can achieve better decoding performance and higher spectral efficiency than conventional fast decoding algorithms.展开更多
基金supported by the Fundamental Research Funds for the Central Universities under grant 2016XD-01
文摘Overlapped x domain multiplexing(OVXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing inter-symbol interference(ISI) intelligently. However, the computational complexity of maximum likelihood sequence detection(MLSD) increases exponentially with the growth of spectral efficiency in OVXDM, which is unbearable for practical implementations. In this paper, based on a novel path metric associating adjacent symbols, we propose a multi-bit sliding stack decoding(Multi-Bit SSD) algorithm to achieve multiple-bit decoding simultaneously in OVXDM. Theoretical analysis is provided for the algorithm, which indicates the relationship between the performance and parameters including multiplexing waveform, overlapping fold and sliding window size. Simulation results show that the proposed algorithm can achieve better decoding performance and higher spectral efficiency than conventional fast decoding algorithms.
