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Enhancing Reliable Communication in Wireless Networks with Non-Binary Joint Network Coding

This study presents Non-Binary Joint Network Coding (NB-JNCC) as a solution for achieving reliable communication in large wireless networks plagued by fading. By integrating network and channel coding in a high-order Galois field, NB-JNCC effectively combats signal degradation. Through simulations, we demonstrate improved diversity and capacity gains, showcasing the benefits of direct transmissions with and without relays. The performance of NB-JNCC is compared against traditional methods, confirming its capability for larger, multi-hop network applications.

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Enhancing Reliable Communication in Wireless Networks with Non-Binary Joint Network Coding

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  1. Non-Binary Joint Network Channel Coding for Reliable Communication in Large Wireless Networks Zheng Guo, Jie Huang, Bing Wang, Jun-Hong Cui and Shengli Zhou UWSN@UCONN

  2. Outline • Motivation • Related Work • System Description • Benefits of NB-JNCC • Performance Study • Conclusions & Discussions UWSN@UCONN

  3. Motivation • Reliable communication in wireless networks • Fading • Add redundancy to combat fading • Inside packet: error-correction coding, channel coding, physical layer. • Cross packets: erasure-correction coding, FEC, network coding, network layer. UbiNet@UCONN

  4. Motivation (cont.) • Large, multiple hop wireless networks • Basic idea: • Joint network and channel coding • Direct combination in high order Galois Field (Non-Binary) • An integrated factor graph UbiNet@UCONN

  5. Related Work • Separate network channel coding • Distributed channel coding • Joint network channel coding • Most related one: X. Bao, and J. Li, " A Unified Channel-Network Coding Treatment for Wireless Ad-Hoc Networks," Proceeding of IEEE International Symposium on Information Theory (ISIT), Seattle, WA, July 2006. UbiNet@UCONN

  6. System Description • Network model • We consider a small topology with two sources, two relays and a sink. This can be treated as a basic component of large network • Channel model • Rayleigh fading where UbiNet@UCONN

  7. Code Construction • Two sources packets and • Channel coding: non-binary LDPC code specified by and • Network coding: random linear network coding UbiNet@UCONN

  8. An Integrated Factor Graph UbiNet@UCONN

  9. Joint Decoding • Iterative decoding through a larger parity check matrix • Layered iterative decoding • Channel decoding • Update soft information through network decoding • Channel decoding • …… UbiNet@UCONN

  10. Benefits of NB-JNCC • We compare four schemes • Direct transmissions w/o relays • Direct transmissions w/ relays • Binary JNCC • Non-Binary JNCC UbiNet@UCONN

  11. Diversity Gain • Direct transmissions w/o relays • Direct transmissions w/ relays • Binary JNCC • Non-Binary JNCC UbiNet@UCONN

  12. Capacity Gain • Direct transmissions w/o relays • Direct transmissions w/ relays • Binary JNCC • Non-Binary JNCC UbiNet@UCONN

  13. Performance Study • Simulation setup • GF(16) • K=800 symbols • Channel code rate 0.8 • Network code rate 0.5 • BPSK UbiNet@UCONN

  14. Overall comparison UbiNet@UCONN

  15. Error Pattern UbiNet@UCONN

  16. Joint Decoding Gain UbiNet@UCONN

  17. Decoding Complexity UbiNet@UCONN

  18. Conclusions • NB-JNCC can be easily extended to large, multiple hop network • We focus on direct combination of channel code and network code on high order Galois Field UbiNet@UCONN

  19. Discussions and Suggestions Thanks UbiNet@UCONN

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