An intelligent scheduling scheme for real-time traffic management using Cooperative Game Theory and AHP-TOPSIS methods for next generation telecommunication networks

- An Intelligent scheduling scheme is proposed for LTE-A networks.
- Game theory and AHP-TOPSIS methods are integrated to optimize the scheduling.
- It fairly allocate resources among user equipment.
- Active state of the user equipment is decided based on load and channel conditions.
- Results show that consumption of battery life and transmission delay are reduced.

The emerging and exponential growth of telecommunication networks have developed a variety of smart and powerful devices to handle a wide range of multimedia applications such as Voice over IP (VoIP), video streaming, etc. 3GPP introduced Long Term Evolution (LTE) in release 8 and LTE-Advanced (A) in release 10 to support multimedia traffic as these technologies offers high data rate, high bandwidth, and low latency. It also created new challenges to handle resource allocation and power optimization of User Equipment (UE). The paper explores radio resource allocation and power consumption problem of UE in LTE environment. An intelligent scheduling scheme developed is based on Cooperative Game Theory (CGT) method and AHP-TOPSIS method. It distributes resources in a fair way among a number of applications and UE are prioritized based on certain criteria like delay, throughput history, UE buffer space and channel conditions and preferences. In LTE, Discontinuous Reception (DRX) has been adopted to conserve the battery life of UE. DRX periodically switches off the radio interfaces to conserve the battery life but it may breach Quality of Service (QoS). Therefore, the DRX parameters need to be further optimized to satisfy QoS and minimize power consumption of UE. DRX parameters are dynamically adjusted on the basis of current load and channel condition of the network. Power saving operations are numerically analyzed. Simulation results show that the expert and an intelligent system can distribute resources in a fair way among UE, improves the battery consumption of UE up to 85% and packets transmission delay by 10% as compared to existing scheme for real-time applications.