An improved queuing model for packet retransmission policy and variable latency decoders

The convolutional coding is a very popular channel coding technique for the major reason of mitigating the probability of having many retransmissions because of difficult (noisy) communication channels. Sequential decoding is a type of convolutional codes that becomes of interest in wireless communication since it affords a decoding time that can be adaptive to channel state. In this study, the authors propose an improved queuing model, using discrete-time semi-Markov chain, which represents a modified packet retransmission policy over previously proposed queuing model. The authors queuing model mainly describes the behaviour of the buffer, which belongs to intermediate hops, when sequential decoding is implemented and concerns also about packets being transmitted over erroneous channels. The authors aim after conducting queuing analysis to find a real mathematical form for the average buffer occupancy as a network performance metric. Although the improved queuing model when incorporating the new policy for retransmission is very complicated, we are finally able to derive an expression for that performance metric considering practical assumptions. They further illustrate how the modified queuing model has a better impact on the end-to-end delay of messages, being transmitted without any extra buffering requirements needed, than the other relevant proposed queuing model. They conduct a simulation study using computer programming with the same assumptions used for queuing analysis to validate their analytical explanations and results. Furthermore, they validate the correctness of their closed-form expression through comparing its results with those obtained from expression related to a queuing model which discarded employing any retransmission policy.