Low-complexity multiple-signal joint decoding for overlapped x domain multiplexing signalling

作者：Lin, Peng; Wang, Yafeng^*; Li, Daoben

来源：IET Communications, 2018, 12(11): 1273-1282.

DOI：10.1049/iet-com.2017.1402

• AWGN channels
• error statistics
• maximum likelihood estimation
• AWGN
• fading channels
• maximum likelihood detection
• computational complexity
• decoding
• OFDM modulation
• signal detection
• low-complexity multiple-signal
• overlapped x domain
• multiplexing waveform
• shifting symbols
• weighted symbols
• (OVXDM) encoding scheme
• high spectral efficiency
• low signal-to-noise ratio
• maximum likelihood sequence detection decoders
• optimal decoding performance
• multiple-signal joint decoding algorithm

By multiplexing waveform mapped with shifting and weighted symbols, overlapped x domain multiplexing (OVXDM) encoding scheme can obtain high spectral efficiency under a low signal-to-noise ratio. Though the maximum likelihood sequence detection decoders can obtain the optimal decoding performance, their computational complexities which increase exponentially with spectral efficiency in OVXDM are unbearable for practical implementations. In this study, a low-complexity multiple-signal joint decoding (MSJD) algorithm for OVXDM signalling is proposed over additive white Gaussian noise (AWGN) channel and extended to frequency selective fading (FSF) channel. Based on a novel joint information-based metric, the proposed algorithm utilises information of each transmitted symbol contained in multiple received signals, and selects the proper number of received signals for decoding to achieve performance maximisation. Moreover, theoretical analysis is provided for the proposed algorithm in both AWGN and FSF channels, which indicates the relationship between performance and number of received signals under different OVXDM encoding parameters including multiplexing waveform and overlapping fold. Simulation results confirm the superior performance of the MSJD algorithm in terms of decoding performance and computational complexity compared with the present approaches.

• 出版日期2018-7-17
• 单位北京邮电大学