Quasi-linear Network Coding

We present a heuristic for designing vector non-linear network codes for non-multicast networks, which we call quasi-linear network codes. The method presented has two phases: finding an approximate linear network code over the reals, and then quantizing it to a vector non-linear network code using a fixed-point representation. Apart from describing the method, we draw some links between some network parameters and the rate of the resulting code

From Instantly Decodable to Random Linear Network Coding

Our primary goal in this paper is to traverse the performance gap between two linear network coding schemes: random linear network coding (RLNC) and instantly decodable network coding (IDNC) in terms of throughput and decoding delay. We first redefine the concept of packet generation and use it to partition a block of partially-received data packets in a novel way, based on the coding sets in an IDNC solution. By varying the generation size, we obtain a general coding framework which consists of a series of coding schemes, with RLNC and IDNC identified as two extreme cases. We then prove that the throughput and decoding delay performance of all coding schemes in this coding framework are bounded between the performance of RLNC and IDNC and hence throughput-delay tradeoff becomes possible. We also propose implementations of this coding framework to further improve its throughput and decoding delay performance, to manage feedback frequency and coding complexity, or to achieve in-block performance adaption. Extensive simulations are then provided to verify the performance of the proposed coding schemes and their implementations.Comment: 30 pages with double space, 14 color figure

Quantum linear network coding as one-way quantum computation

Network coding is a technique to maximize communication rates within a network, in communication protocols for simultaneous multi-party transmission of information. Linear network codes are examples of such protocols in which the local computations performed at the nodes in the network are limited to linear transformations of their input data (represented as elements of a ring, such as the integers modulo 2). The quantum linear network coding protocols of Kobayashi et al [arXiv:0908.1457 and arXiv:1012.4583] coherently simulate classical linear network codes, using supplemental classical communication. We demonstrate that these protocols correspond in a natural way to measurement-based quantum computations with graph states over over qudits [arXiv:quant-ph/0301052, arXiv:quant-ph/0603226, and arXiv:0704.1263] having a structure directly related to the network.Comment: 17 pages, 6 figures. Updated to correct an incorrect (albeit hilarious) reference in the arXiv version of the abstrac

Random Linear Network Coding for 5G Mobile Video Delivery

An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio