CoSchd: Coordinated Scheduling With Channel and Load Awareness for Alleviating Cellular Congestion

Abstract

Although cellular networks can be provisioned according to the peak demand, they usually experience large fluctuations in both channel conditions and traffic load level. Scheduling with both channel and load awareness allows us to exploit the delay tolerance of data traffic to alleviate network congestion, and thus reduce the peak. However, solving the optimal scheduling problem leads to a large-scale Markov decision process (MDP) with extremely high complexity. In this paper, we propose a scalable and distributed approach to this problem, called Coordinated Scheduling (CoSchd). CoSchd decomposes the large-scale MDP problem into many individual MDP problems, each of which can be solved independently by each user under a limited amount of coordination signals from the base station (BS). We show that CoSchd is close to optimal when the number of users becomes large. Furthermore, we propose an approximation of CoSchd that iteratively updates the scheduling policy based on online measurements. Simulation results demonstrate that exploiting channel and load awareness with CoSchd can effectively alleviate cellular network congestion.