Energy-Delay Optimization for Ultra-Reliable Low Latency Communication

The fifth generation (5G) has been proposed to enable diverse services with different and strict requirements on data-rate, latency, availability and so on. However, providing services of ultra-reliable low-latency communication (URLLC) by limited-resources networks, in terms of energy, delay and channel availability, is foreseen as a challenging problem. This paper addresses this challenge of providing ultra-low latency services for the resources-limited devices operating on 5G networks. In order to tackle this challenge, we propose an energy-delay management framework (EDMF) to minimize the energy consumption subject to constraints on delay and bit error rate. The EDMF is formulated as constrained partially observable Markov decision process (CPOMDP) in order to obtain the optimal policy that optimizes the energy consumption, delay and bit error rate. Due to the high level of computational complexity of CPOMDP, the problem formulation of the proposed EDMF is transformed into belief constraint Markov decision process (CMDP) and solved by using mixed integer linear programming (MILP).