PROJECT TITLE :

Interference-Aware Energy-Efficient Resource Allocation for OFDMA-Based Heterogeneous Networks With Incomplete Channel State Information

ABSTRACT:

Heterogeneous wireless networks are thought of as promising technologies to boost energy potency. In heterogeneous networks, interference management is very necessary since the interference due to spectrum sharing will significantly degrade overall performance. In the present work, numerous resource allocation methods are proposed to either improve energy efficiency or mitigate interference in orthogonal frequency-division multiple access (OFDMA)-based mostly multicell networks. To the most effective of our information, no research on resource allocation has jointly considered improving energy potency and performing interference management, particularly using interference power constraint methods. Furthermore, most existing work assumes that each one of the channel state data (CSI) is thought completely, which might not be realistic in heterogeneous networks due to the limited capability of the backhaul links and varied ownership of network devices. In this paper, we tend to propose a game-theoretical scheme using energy-efficient resource allocation and interference pricing for an interference-limited setting in heterogeneous networks. We tend to formulate the issues of resource allocation and interference management as a Stackelberg game with incomplete CSI. A backward induction technique is employed to research the proposed game. A closed-kind expression of the Stackelberg equilibrium (SE) is obtained for the proposed game with numerous interference power constraints. Simulation results are presented to show the effectiveness of the proposed scheme.