Energy Efficient Price Based Power Allocation in a Small Cell Network by Using a Stackelberg Game

Small cell networks are playing a pivotal role in increasing coverage and capacity of cellular networks which are extensively in last few years. However, the limited number of methods for optimal control of cross-layer interference and energy efficiency issues are paramount challenges of these networks. In this paper, a novel approach for an energy efficient communication in a two-tier small cell network is proposed. We have suggested pricing on interference and controlling transmit power to mitigate cross-layer interference and improve energy efficiency. In order to formulate the problem, the macrocell base station (MBS) and femtocell base stations (FBSs) act as leader and followers of a Stackelberg game, respectively. The MBS uses the pricing on the amount of the received interference to protect itself against the interference caused by FBSs. The FBSs goal is to maximize their energy efficiency and minimize the amount of price that should be paid to MBS by using a power control under the maximum allowable transmit power constraint. Maximizing energy efficiency is a non-linear fractional programming which is transformed to a subtractive form, and thus, it can be solved by using the iterative power allocation algorithm. The efficiency of the proposed algorithm is investigated through simulation results.

[1]  Zhu Han,et al.  Game Theory in Wireless and Communication Networks , 2008 .

[2]  Geoffrey Ye Li,et al.  Distributed Interference-Aware Energy-Efficient Power Optimization , 2011, IEEE Transactions on Wireless Communications.

[3]  Mehul Motani,et al.  Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach , 2012, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[4]  Werner Dinkelbach.  On Nonlinear Fractional Programming , 1967 .

[5]  Tony Q. S. Quek,et al.  Small Cell Networks: Deployment, PHY Techniques, and Resource Management , 2013 .

[6]  Yongming Huang,et al.  Decentralized Energy-Efficient Coordinated Beamforming for Multicell Systems , 2014, IEEE Transactions on Vehicular Technology.

[7]  Walid Saad,et al.  Distributed power allocation and interference mitigation in two-tier femtocell networks: A game-theoretic approach , 2015, 2015 International Wireless Communications and Mobile Computing Conference (IWCMC).

[8]  Walid Saad,et al.  Transmission Rate Maximization in Self-Backhauled Wireless Small Cell Networks , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[9]  Bo Rong,et al.  Game theory based multi-tier spectrum sharing for LTE-A heterogeneous networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[10]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in Multi-Cell OFDMA Systems with Limited Backhaul Capacity , 2012, IEEE Trans. Wirel. Commun..

[11]  Xiaohu You,et al.  Energy-efficient downlink transmission in multi-cell coordinated beamforming systems , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[12]  Lei Li,et al.  Energy-efficient resource allocation in heterogeneous network with cross-tier interference constraint , 2013, 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops).

[13]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[14]  B. Martos.  The Direct Power of Adjacent Vertex Programming Methods , 1965 .

[15]  Zhu Han,et al.  Game Theory in Wireless and Communication Networks: Theory, Models, and Applications , 2011 .