Optimal decoding of convolutional-coded physical-layer network coding

Author

Qing Yang ; Soung Chang Liew

Author_Institution

Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Hong Kong, China

fYear

2014

fDate

6-9 April 2014

Firstpage

364

Lastpage

369

Abstract

This paper investigates the decoding process of convolutional-coded physical-layer network coding (PNC) systems. Specifically, we put forth a joint channel-decoding network coding (Jt-CNC) algorithm, based on belief propagation (BP), for convolutional-coded PNC. Previously proposed XOR and channel decoding (XOR-CD) algorithm and reduced-state Viterbi algorithm are not optimal. Our Jt-CNC decoder is BER-optimal with feasible computational complexity. Simulations show that Jt-CNC outperforms XOR-CD and reduced-state Viterbi by 2dB. Furthermore, Jt-CNC is more resilient to phase offset.

Keywords

channel coding; computational complexity; convolutional codes; decoding; maximum likelihood estimation; network coding; phase coding; BER-optimal; BP; Jt-CNC algorithm; PNC; XOR-CD algorithm; belief propagation; channel decoding algorithm; computational complexity; convolutional-coded PNC; convolutional-coded physical-layer network coding; gain 2 dB; joint channel-decoding network coding algorithm; optimal decoding process; reduced-state Viterbi algorithm; Complexity theory; Convolution; Convolutional codes; Decoding; Network coding; Relays; Viterbi algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications and Networking Conference (WCNC), 2014 IEEE

Conference_Location

Istanbul

Type

conf

DOI

10.1109/WCNC.2014.6952035

Filename

6952035