Random linear network coding over compute-and-forward in multi-source multi-relay networks
| Autor: | Yasuo Tan, Rithea Ngeth, Yuto Lim, Brian M. Kurkoski |
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| Rok vydání: | 2017 |
| Předmět: |
Theoretical computer science
Computer science ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS 010102 general mathematics 020206 networking & telecommunications Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology 01 natural sciences law.invention Transmission (telecommunications) Channel state information Relay law Linear network coding 0202 electrical engineering electronic engineering information engineering Overhead (computing) 0101 mathematics Algorithm Decoding methods Multi-source Computer Science::Information Theory Communication channel |
| Zdroj: | IWCMC |
| DOI: | 10.1109/iwcmc.2017.7986388 |
| Popis: | This paper proposes a transmission scheme which applies random linear network coding (RLNC) over compute-and-forward (CF), called RLNC/CF, in multi-source multi-relay networks. Instead of solving the full rank failure at relays, this paper compensates for this overhead to increase the possibility of successfully decoding computed messages at the destination. The concept of the overlapped generations is applied with a proposed computing and storing strategy. This paper provides a compensation based on the estimation of the channel state information (CSI) of the previous generation and a compensation based on the learning data of CSI. By comparing to an orthogonal channel transmission scheme, a performance trade-off is considered. An expression for estimated performances of RLNC/CF in function of the probabilities of the parameters related to CSI is provided to help for the decision of selecting transmission scheme. From the numerical result, RLNC/CF scheme works better than a conventional CF transmission scheme in reducing the transmission latency. |
| Databáze: | OpenAIRE |
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