Analytical Model for LTE Downlink Scheduler with D2D Communication for Throughput Estimation

Abstract

Device-To-Device (D2D) communication is expected to be an essential component of the next generation cellular network. Although this promising technology has already demonstrated its ability to increase network throughput. The need for an accurate, fast- computing model of throughput estimation is essential. In this paper, an analytical model for LTE (Long Term Evolution) scheduler- supported D2D communication is presented. The model is based on two-dimensional Continues- Time Markov Chain and is utilized for estimating network throughput. Also, a closed formula is obtained for determining the expected number of D2D users in dedicated and reuse modes. Two scheduled algorithms, Round Robin and Max signal-to-interference-plus-noise ratio, were used for estimating throughput. Analytical model results were closely aligned with simulations and demonstrated that the analytical model is very accurate and time efficient.