QoS-Aware Power Management in LTE-A Networks Under Heterogeneous Traffics

In 3GPP LTE-A releases v.8 and beyond, the plug and play nature of the eNodeBs lets a dense deployment of eNodeBs, thus, causing over-provisioned network infrastructure. Here, while most of the recent studies aim to optimize power consumption on a single traffic type, we provide a novel framework that corresponds both power adjustment and quality of users (QoS) requirements of end-users with multitraffic types. In this manner, we propose a novel energy efficiency coefficient (EEC) considering QoS and channel utilization while reducing power consumption. Moreover, our proposed resource auction module assigns resource blocks to low-utilized cellular networks. Furthermore, the traffic types are modeled with a queuing theoretic approach. We also define an optimization problem that employs novel EEC parameters to determine new power levels (8-levels) for eNodeBs' configurations with less power consumption. To solve this optimization problem, we introduce a novel heuristic called "Multi Level Branch and Bound Algorithm" (MLBB). MLBB algorithm contains two nested branch and bound algorithms that manipulates end-users differently. Consequently, our proposed methodology serves end-users with 67% better QoS than the conventional mechanisms.