WmA-MiFN: A Weighted Majority and Auction Game Based Green Ultra-Dense Micro-Femtocell Network System

Power optimization and interference management in ultra-dense small cell based fifth-generation mobile networks are critical issues. This paper proposes a two-tier micro-femtocell based heterogeneous ultra-dense cellular network system, where femtocell allocation takes place inside the microcell based on user density. The femtocells form groups according to the adjacency and the leader selection of each group is performed using weighted majority game. Dedicated frequency allocation is performed for micro- and femtocell users though the leader of each femtocell group allocates frequencies to its follower femtocells based on auction game. Agilent EXG vector signal generator N5172B, EXA vector signal analyzer 9010A, and Agilent signal studio software are used for experimental purpose for performance evaluation of the proposed network. According to the simulation results, the proposed network decreases power transmission by 23%–41%, improves signal-to-interference-plus-noise ratio by 12%–39% and spectral efficiency by 10%–37% than the existing competing heterogeneous cellular network systems.

[1]  Alagan Anpalagan,et al.  Min–Max Energy-Efficiency Analysis of Green Multiuser Wireless Systems , 2015, Wirel. Pers. Commun..

[2]  Li-Chun Wang,et al.  Self-Organizing Ultra-Dense Small Cells in Dynamic Environments: A Data-Driven Approach , 2019, IEEE Systems Journal.

[3]  Debashis De,et al.  User velocity based hand-off prediction in micro-femtocell clustered network , 2018, Comput. Electr. Eng..

[4]  Jun Cai,et al.  Joint User Association and Power Allocation for Hybrid Half-Duplex/Full-Duplex Relaying in Cellular Networks , 2019, IEEE Systems Journal.

[5]  Tarik Taleb,et al.  Feedback Suppression in Multicast Satellite Networks Using Game Theory , 2012, IEEE Systems Journal.

[6]  Mehmet Fatih Tüysüz,et al.  Energy-Efficient Vertical Handover Parameters, Classification and Solutions over Wireless Heterogeneous Networks: A Comprehensive Survey , 2017, Wirel. Pers. Commun..

[7]  Hong Wen,et al.  Energy-Efficient Precoded Coordinated Multi-Point Transmission With Pricing Power Game Mechanism , 2017, IEEE Systems Journal.

[8]  Junyi Li,et al.  Network densification: the dominant theme for wireless evolution into 5G , 2014, IEEE Communications Magazine.

[9]  Wen-Hsing Kuo,et al.  QoS-aware cooperative power control and resource allocation scheme in LTE femtocell networks , 2017, Comput. Commun..

[10]  Debashis De,et al.  5G-ZOOM-Game: small cell zooming using weighted majority cooperative game for energy efficient 5G mobile network , 2018, Wireless Networks.

[11]  Debashis De,et al.  Femtocell based green power consumption methods for mobile network , 2013, Comput. Networks.

[12]  Gang Feng,et al.  Energy-Efficient Downlink Resource Allocation in Heterogeneous OFDMA Networks , 2017, IEEE Transactions on Vehicular Technology.

[13]  Jeffrey G. Andrews,et al.  Are we approaching the fundamental limits of wireless network densification? , 2015, IEEE Communications Magazine.

[14]  Yihao Zhang,et al.  Energy-Efficient User Scheduling and Power Control for Multi-Cell OFDMA Networks Based on Channel Distribution Information , 2018, IEEE Transactions on Signal Processing.

[15]  Jinsong Wu,et al.  Survey of Strategies for Switching Off Base Stations in Heterogeneous Networks for Greener 5G Systems , 2016, IEEE Access.

[16]  Song Guo,et al.  Achieve Sustainable Ultra-Dense Heterogeneous Networks for 5G , 2017, ArXiv.

[17]  Debashis De,et al.  Energy and Spectrum Optimization for 5G Massive MIMO Cognitive Femtocell Based Mobile Network Using Auction Game Theory , 2019, Wireless Personal Communications.

[18]  Liesbet Van der Perre,et al.  Challenges and enabling technologies for energy aware mobile radio networks , 2010, IEEE Communications Magazine.

[19]  Yang Xu,et al.  A Stackelberg game-based spectrum allocation scheme in macro/femtocell hierarchical networks , 2013, Comput. Commun..

[20]  Debashis De,et al.  Interference management in macro-femtocell and micro-femtocell cluster-based long-term evaluation-advanced green mobile network , 2016, IET Commun..

[21]  Hanna Bogucka,et al.  Dynamic spectrum aggregation for future 5G communications , 2015, IEEE Communications Magazine.

[22]  Mohammad S. Obaidat,et al.  GTCharge: A game theoretical collaborative charging scheme for wireless rechargeable sensor networks , 2016, J. Syst. Softw..

[23]  Feng Zhao,et al.  Group buying spectrum auction algorithm for fractional frequency reuse cognitive cellular systems , 2017, Ad Hoc Networks.

[24]  Yanjiao Chen,et al.  Macro-femto heterogeneous network deployment and management: from business models to technical solutions , 2011, IEEE Wireless Communications.

[25]  Dushantha Nalin K. Jayakody,et al.  An Analytical View of ASE for Multicell OFDMA Networks Based on Frequency-Reuse Scheme , 2020, IEEE Systems Journal.

[26]  Charles Clancy,et al.  An Optimal Strategy for Determining True Bidding Values in Secure Spectrum Auctions , 2019, IEEE Systems Journal.

[27]  Youngju Kim,et al.  Performance Analysis of Two-Tier Femtocell Networks with Outage Constraints , 2010, IEEE Transactions on Wireless Communications.

[28]  Sami Tabbane,et al.  Win-win relationship between macrocell and femtocells for spectrum sharing in LTE-A , 2014, IET Commun..

[29]  Zhisheng Niu,et al.  Toward dynamic energy-efficient operation of cellular network infrastructure , 2011, IEEE Communications Magazine.

[30]  Mehdi Fereydooni,et al.  Analytical evaluation of heterogeneous cellular networks under flexible user association and frequency reuse , 2018, Comput. Commun..