Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks. (February 2018)

• Record Type: Journal Article
• Authors: Huo, Liuwei; Jiang, Dingde; Lv, Zhihan
• Is Part Of: Computers & electrical engineering. Volume 66(2018)
• Page Start: 316
• Page End: 331
• Publication Date: 2018-02
• Subjects: Soft frequency reuse -- Energy efficiency -- Fractional program -- Successive convex appropriate -- Multi-cell networks; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.09.009
• Languages: English
• ISSNs: 0045-7906

Abstract

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.