Publication | Closed Access
Power-Delay Tradeoff With Predictive Scheduling in Integrated Cellular and Wi-Fi Networks
59
Citations
18
References
2016
Year
Wireless CommunicationsCross-layer OptimizationEngineeringDynamic Resource AllocationEnergy EfficiencyPower ControlPower-delay TradeoffWireless SystemsEnergy-efficient CommunicationGlobal Mobile TrafficMobile Data OffloadingComputer EngineeringWireless NetworkingMobile ComputingPredictive SchedulingDevice-to-devicePower ConsumptionWireless Cooperative NetworkIntegrated CellularEnergy ManagementBusinessResource AllocationResource OptimizationEnergy-efficient Networking
The explosive growth of global mobile traffic has led to rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in cellular and Wi-Fi networks, while taking into account the traffic delay of mobile users. Based on the two-timescale Lyapunov optimization technique, we first design an online Energy-Aware Network Selection and Resource Allocation (ENSRA) algorithm, which yields a power consumption within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O\left({\frac{1}{V}} \right)$</tex-math></inline-formula> bound of the optimal value, and guarantees an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O\left(V \right)$</tex-math></inline-formula> traffic delay for any positive control parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V$</tex-math></inline-formula> . Motivated by the recent advancement in the accurate estimation and prediction of user mobility, channel conditions, and traffic demands, we further develop a novel predictive Lyapunov optimization technique to utilize the predictive information, and propose a Predictive Energy-Aware Network Selection and Resource Allocation (P-ENSRA) algorithm. We characterize the performance bounds of P-ENSRA in terms of the power-delay tradeoff theoretically. To reduce the computational complexity, we finally propose a Greedy Predictive Energy-Aware Network Selection and Resource Allocation (GP-ENSRA) algorithm, where the operator solves the problem in P-ENSRA approximately and iteratively. Numerical results show that GP-ENSRA significantly improves the power-delay performance over ENSRA in the large delay regime. For a wide range of system parameters, GP-ENSRA reduces the traffic delay over ENSRA by 20–30% under the same power consumption.
| Year | Citations | |
|---|---|---|
Page 1
Page 1