Spectrum‐efficiency enhancement in small cell networks with biasing cell association and eICIC: An analytical framework. (30th September 2014)

• Record Type: Journal Article
• Authors: Wang, Yongbin; Ji, Hong; Zhang, Heli
• Is Part Of: International journal of communication systems. Volume 29:Number 2(2016)
• Page Start: 362
• Page End: 377
• Publication Date: 2014-09-30
• Subjects: small cell networks -- spectrum efficiency -- biasing cell association -- eICIC -- eICIC factor -- biasing factor; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.2838
• Languages: English
• ISSNs: 1074-5351

Abstract

SUMMARY: Load balancing and interference management play crucial roles in small cell network (SCN) capacity and spectrum efficiency (SE) enhancement. By performing load balancing between macrocell and small cells, biasing cell association has attracted great attentions since it is proposed. Additionally, enhanced intercell interference coordination (eICIC) technology is also developed as an efficient interference mitigation method for the biasing cell association‐based SCNs. In this paper, we develop an SE enhancement framework with joint consideration of the eICIC factor and biasing factor. Using the stochastic geometry theory, the network is modeled by spatial Poisson point process. We firstly derive the downlink average rate, which is performed at a typical user. Secondly, the eICIC factor‐related network SE is analyzed by proving the existence of optimal eICIC factor, which maximizes the network SE. For the intractability of the closed‐form expression of optimal eICIC factor, a bisection search‐based algorithm is developed then. At last, numerical results confirm our analysis and show the proposed algorithm performance. Copyright © 2014 John Wiley & Sons, Ltd. Abstract : Based on the previous derivation, our proposed analysis framework can obtain the optimal enhanced intercell interference coordination (eICIC) and biasing factors. As is presented in the figure, the two optimal values are highly correlated, and the optimal factors are also influenced by small cell base station density. Moreover, our proposed bisection search?based eICIC optimization algorithm can obtain the approximate eICIC factor to theory results.