Optimization of a Random Linear Network Coding System with Newton Method for Wireless Systems
Roberto Torre, Sreekrishna Pandi, Giang T. Nguyen, Frank H. P. Fitzek
Abstract
Roberto Torre, Sreekrishna Pandi, Giang T. Nguyen, Frank H. P. Fitzek
Abstract
Random Linear Network Coding (RLNC) is widely considered a key enabler for 5G networks. It compensates for lost and corrupted packets by sending redundant coding packets. Despite the considerable attention RLNC received from the research community, the impact of the number of redundant coded packets on the network performance is poorly understood. An excessive number of redundancies would pollute the network with useless packets that give no additional information, and an insufficient number of redundancies would not provide enough packet loss resilience. We introduce a novel formal model for predicting the number of losses a system would have when RLNC is applied, by optimizing simulation results with the Newton-Raphson method. The model allows the sender to set the minimum amount of RLNC redundancies needed to keep the packet loss under a certain threshold. We validate our model against simulations by calculating the MSE between simulation results and our model.
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Random Linear Network Coding (RLNC) is widely considered a key enabler for 5G networks. It compensates for lost and corrupted packets by sending redundant coding packets. Despite the considerable attention RLNC received from the research community, the impact of the number of redundant coded packets on the network performance is poorly understood. An excessive number of redundancies would pollute the network with useless packets that give no additional information, and an insufficient number of redundancies would not provide enough packet loss resilience. We introduce a novel formal model for predicting the number of losses a system would have when RLNC is applied, by optimizing simulation results with the Newton-Raphson method. The model allows the sender to set the minimum amount of RLNC redundancies needed to keep the packet loss under a certain threshold. We validate our model against simulations by calculating the MSE between simulation results and our model.
Key concepts: Linear network coding, Computer science, Network packet, Coding (social sciences), Resilience (materials science), Computer network, Wireless, Communication source