Performance of wireless network coding: motivating small encoding numbers

Abstract: This paper focuses on a particular transmission scheme called local network coding, which has been reported to provide significant performance gains in practical wireless networks. The performance of this scheme strongly depends on the network topology and thus on the locations of the wireless nodes. Also, it has been shown previously that finding the encoding strategy, which achieves maximum performance, requires complex calculations to be undertaken by the wireless node in real-time. Both deterministic and random point pattern are explored and using the Boolean connectivity model we provide upper bounds for the maximum coding number, i.e., the number of packets that can be combined such that the corresponding receivers are able to decode. For the models studied, this upper bound is of order of $\sqrt{N}$, where $N$ denotes the (mean) number of neighbors. Moreover, achievable coding numbers are provided for grid-like networks. We also calculate the multiplicative constants that determine the gain in case of a small network. Building on the above results, we provide an analytic expression for the upper bound of the efficiency of local network coding. The conveyed message is that it is favorable to reduce computational complexity by relying only on small encoding numbers since the resulting expected throughput loss is negligible.