Modelling and Optimization of DRX in Cellular IoT Networks: an MDP Approach

Due to the exponential growth of endpoints in the Internet of Things (IoT), new protocols have been proposed to utilize cellular infrastructures, allowing a large amount of IoT devices to communicate through them. These novel protocols make up the Cellular IoT (C-IoT). In C-IoT, the energy efficiency of endpoints is essential in order to reduce both operational cost and required maintenance. One method of energy reduction is Discontinuous Reception (DRX). DRX allows a device's Radio Frequency (RF) circuitry to turn off for brief periods of time. While off, the device experiences a tradeoff between saving energy and an increase in expected latency, which can be tuned by how long the device spends asleep. In this paper, we model DRX as a Markov Decision Process (MDP). This MDP is solved using a dynamic programming approach and verified through simulation. Further, the energy-latency tradeoff is explored by varying the device's priority on either energy or network performance in addition to varying the traffic intensity.