Traffic-aware data and signaling resource management for green cellular networks

The increasing traffic demands bring heavy load to both the data and control planes of cellular networks, along with substantial energy consumption. To solve the issue, new network architecture that separates signaling and data has been proposed in literature for future green cellular networks. In this paper, we analyze the data and signaling resource configuration problem in this new network architecture. We find the optimal resource partitioning parameters to optimize the blocking performance and to minimize the overall network power consumption with a blocking probability constraint. More specifically, we adopt traffic-aware resource allocation between the data and signaling base stations (BSs) to improve network access capability while reducing the overall network power consumption. Two types of resource partitioning patterns, complete partitioning and partial partitioning, are studied. Numerical results show that great energy-saving gain can be achieved compared with the traditional fixed and traffic-proportional resource partitioning patterns. Moreover, power consumption and blocking performance tradeoffs are explored, based on which the appropriate resource partitioning pattern can be chosen according to different quality of service (QoS) requirements.