A novel dynamic cell configuration scheme in next-generation situation-aware CDMA networks

In next-generation CDMA networks, due to random user mobility and time-varying multimedia traffic activity, the system design of coverage and capacity is a challenging issue. To utilize radio resources efficiently, it is crucial for future cellular networks to be aware of the system situation and configures cell coverage and capacity dynamically to balance traffic loads over all cells. In this paper, we propose a novel dynamic cell configuration scheme in multimedia CDMA networks via reinforcement-learning, which takes into account pilot, soft handoff, and maximum link power allocations as well as call admission control mechanisms. Simulation results demonstrate the effectiveness of the proposed scheme in situation-aware CDMA networks.