Mathematical Model of the Delays Inherent in Communication Using Wireless Networks

Abstract

With the rise of essential electronic applications, intelligent wireless communication will needed, but they have tight constraints on the amount of delays and reliability they can accept. The estimation of the channel's state is essential in this scenario because it allows the sender channel to tailor the coding rate to the characteristics of the channel. Within the context of this research, we characterise the transmission between the length of the estimate queue and the length of the data codeword as, The shorter the channel estimate, the less accurate the estimation will be, and the more errors will occur during decoding; nevertheless, this will free up more time for the actual transmission of the payload. This damage may be mitigated by using lower coding rates; however, this may result in a worsening of the transmitter data backlog. We apply queueing analysis in addition to exact models of the physical layer and based on a new closed-form estimate for the error probability given the rate, we show that selecting the most appropriate method for rate adaptation may be made into a convex issue. This is something that we illustrate. When compared to inferior solutions that do not take into account the application's latency and reliability requirements, the optimal rate adaption strategy and the optimal length of the training sequence can both significantly improve delay performance. This is because inferior solutions do not take into account the application's latency and reliability requirements.