Published: Jan. 1, 2023

In mobile cellular design, one important quality-of-service metric is the blocking probability. Using computer simulation for studying probability quite time-consuming. Furthermore, existing teletraffic models such as Information Exchange Surrogate Approximation (IESA) only give a rough estimate of Another common approach, direct evaluation using neural networks (NN), performs poorly when extrapolating to network conditions outside training set. This paper addresses shortcomings and NN-based approaches by combining both approaches, creating what we call IESA-NN. IESA-NN, an NN used tuning parameter, which in turn via modified IESA approach. other words, approach still forms core with techniques improve accuracy parameter. Simulation results show that IESA-NN better than previous based on or theory alone. particular, even cannot produce good value example not experienced set, final generally accurate due bounds set underlying theory.

Language: Английский