Abstract-Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. The drawbacks associated with it are the complexity of the decoding and the overhead resulting from the encoding vector. Increasing the field size and generation size presents a fundamental trade-off between packetbased throughput and operational overhead. On the one hand, decreasing the probability of transmitting redundant packets is beneficial for throughput and, consequently, reduces transmission energy. On the other hand, the decoding complexity and amount of header overhead increase with field size and generation length, leading to higher energy consumption. Therefore, the optimal trade-off is system and topology dependent, as it depends on the cost in energy of performing coding operations versus transmitting data. We show that moderate field sizes are the correct choice when trade-offs are considered. The results show that sparse binary codes perform the best, unless the generation size is very low.
For example, REF explores the trade-off between field size and generation (hence encoding vector) size.
On Code Parameters and Coding Vector Representation for Practical RLNC
2011 IEEE International Conference on Communications (ICC)
2011 IEEE International Conference on Communications (ICC)
Computer Science