Abstract :
We investigate the calculation approach of the sink bit error probability (BEP) for a network with intermediate node encoding. The network consists of statistically independent noisy channels. The main contributions are, for binary network codes, an error marking algorithm is given to collect the error weight (the number of erroneous bits). Thus, we can calculate the exact sink BEP from the channel BEPs. Then we generalize the approach to nonbinary codes. The coding scheme works on the Galois field 2m, where m is a positive integer. To reduce computational complexity, a subgraph decomposition approach is proposed. In general, it can significantly reduce computational complexity, and the numerical result is also exact. For approximate results, we discuss the approach of only considering error events in a single channel. The results well approximate the exact results in low BEP regions with much lower complexity.
Keywords :
binary codes; error statistics; graph theory; binary network codes; bit error probability; intermediate node encoding; noisy channel networks; subgraph decomposition; Computational complexity; Computer errors; Computer science; Error correction codes; Error probability; Galois fields; Information theory; Materials science and technology; Monte Carlo methods; Network coding; Binary code; bit error probability; network coding; noisy channel; nonbinary code; subgraph decomposition;