Low-Complexity Channel Allocation Scheme for URLLC Traffic

In this paper, we consider the downlink transmission of URLLC packets requiring very low latency and ultra-reliability. Because of the low latency constraint, the Base Station may not have enough time to acquire the instantaneous Channel State Information (CSI) of the corresponding device and has then to transmit urgent packets immediately in the absence of CSI. To enhance reliability, we explore frequency diversity where a packet can be simultaneously sent over multiple channels. Using a Markov Decision Process framework, we address the problem of dynamic channel allocation to the URLLC devices in absence of instantaneous CSI. More precisely, we define a multi-agent MDP wherein the state of each device is the packet loss rate experienced in the previous time slots and the decision variable is how to split the available orthogonal channels across the devices. We design a new low-complexity algorithm which avoids the exhaustive enumeration of all possible resource allocations and enables significant computational savings compared to the Value Iteration algorithm. We investigate the gap between our proposed low complexity algorithm and the Value Iteration policy. We provide numerical performance results and show that our algorithm can achieve more than 80% of the optimal reward with substantial computational complexity reduction.