Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks

Abstract This paper studies the optimization problem of energy efficiency in multi-cell networks with multiple users such as 5G network. However, the spectrum allocation and inter-cell interference (ICI) in multi-cell networks are the important challenges. The Soft Frequency Reuse (SFR) scheme which manages the spectrum and reduces ICI is used to build SFR-cellular networks. We take the global energy efficiency of the SFR-cellular network as the objective function of the optimal problem to obtain the maximum energy efficiency. Unfortunately, the objective function is a non-concave function, which is significantly difficult to be solved directly. Therefore, we utilize the fractional program, successive convex approximation, Lagrange dual, and Karush–Kuhn–Tucker (KKT) conditions to transform the objective function into a concave function. In such case, we could solve the problem with the convex optimization method. Finally, based on SFR, we propose a global energy efficiency optimization algorithm to search for the optimal energy efficiency of networks. Simulation results show that the proposed algorithm holds the better performance.

[1]  Khairi Ashour Hamdi,et al.  On the energy efficiency of fractional frequency reuse techniques , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[2]  Vijay K. Bhargava,et al.  Green Cellular Networks: A Survey, Some Research Issues and Challenges , 2011, IEEE Communications Surveys & Tutorials.

[3]  Geoffrey Ye Li,et al.  Energy-Efficient Small Cell With Spectrum-Power Trading , 2016, IEEE Journal on Selected Areas in Communications.

[4]  Branka Vucetic,et al.  Adaptive Soft Frequency Reuse Scheme for Wireless Cellular Networks , 2015, IEEE Transactions on Vehicular Technology.

[5]  Sinh Cong Lam,et al.  Analytical Coverage Probability of a Typical User In Heterogeneous Cellular Networks , 2016, J. Networks.

[6]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[7]  Geoffrey Ye Li,et al.  A survey of energy-efficient wireless communications , 2013, IEEE Communications Surveys & Tutorials.

[8]  Tao Li,et al.  An energy-efficient multicast algorithm with maximum network throughput in multi-hop wireless networks , 2016, Journal of Communications and Networks.

[9]  Jamie S. Evans,et al.  SCALE: A Low-Complexity Distributed Protocol for Spectrum Balancing in Multiuser DSL Networks , 2009, IEEE Transactions on Information Theory.

[10]  Jiaheng Wang,et al.  Energy-Efficient Resource Assignment and Power Allocation in Heterogeneous Cloud Radio Access Networks , 2014, IEEE Transactions on Vehicular Technology.

[11]  Wenhui Zhao,et al.  An optimization-based robust routing algorithm to energy-efficient networks for cloud computing , 2016, Telecommun. Syst..

[12]  Yi Li,et al.  Energy-efficient power control for Fractional Frequency Reuse , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[13]  Donghyun Kim,et al.  Strengthening barrier-coverage of static sensor network with mobile sensor nodes , 2016, Wirel. Networks.

[14]  Dingde Jiang,et al.  An energy-efficient cooperative multicast routing in multi-hop wireless networks for smart medical applications , 2017, Neurocomputing.

[15]  Jiandong Li,et al.  CoSFR: coordinated soft frequency reuse for OFDMA-based multi-cell networks with non-uniform user distribution , 2017, Wirel. Networks.

[16]  Suman Kumar,et al.  Optimal design parameters for coverage probability in fractional frequency reuse and soft frequency reuse , 2015, IET Commun..

[17]  Giovanni Giambene,et al.  Soft frequency reuse schemes for heterogeneous LTE systems , 2015, 2015 IEEE International Conference on Communications (ICC).

[18]  Khairi Ashour Hamdi,et al.  A Unified Framework for the Analysis of Fractional Frequency Reuse Techniques , 2014, IEEE Transactions on Communications.

[19]  Cong Xiong,et al.  Energy-Efficient Resource Allocation for OFDMA-Based Multi-RAT Networks , 2014, IEEE Transactions on Wireless Communications.

[20]  Geoffrey Ye Li,et al.  Energy-Efficient User Association and Resource Allocation for Multistream Carrier Aggregation , 2016, IEEE Transactions on Vehicular Technology.