Energy Efficient Resource Allocation in 5G Hybrid Heterogeneous Networks : A Game Theoretic Approach

Munir, Hamnah and Hassan, Syed Ali and Pervaiz, Haris Bin and Ni, Qiang and Musavian, Leila (2016) Energy Efficient Resource Allocation in 5G Hybrid Heterogeneous Networks : A Game Theoretic Approach. In: 2016 IEEE 84th Vehicular Technology Conference (VTC2016-Fall) :. IEEE, CAN, pp. 1-6. ISBN 9781509017027

[thumbnail of 257-35306-review]
PDF (257-35306-review)
257_35306_review.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (370kB)


Millimeter wave (mmWave) technology integrated with heterogeneous networks (HetNets) has emerged as a new wave to overcome the thirst for higher data rates with low transmission powers and severe shortage of spectrum in the wireless industry. In this paper, we consider the uplink of a hybrid heterogeneous network with femtocells overlaid on a macrocell, and formulate a two layer game theoretic framework to maximise the energy efficiency while optimising the network resources. The outer layer non-cooperative game-theoretic approach allows each femtocell access point (FAP) to maximise the data rate of its users by selecting the frequency band either from the sub-6 GHz and the mmWave. The solution to the non-cooperative game can be obtained by using pure strategy Nash equilibrium (PSNE). The inner layer game-theoretic approach ensures the energy efficient user association method subject to the minimum rate and maximum transmission power constraints by using Lagrangian dual decomposition approach. Simulation results show that the proposed hybrid HetNet scheme exploiting the mmWave frequency band improves the sum-rate and energy efficiency in comparison to the scenario where all the networks operate at sub-6 GHz frequency band. The performance of the hybrid HetNet scheme can be further enhanced by incorporating the power control mechanism.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
Deposited By:
Deposited On:
30 Aug 2016 15:18
Last Modified:
10 Jan 2024 00:42