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International Journal of Antennas and Propagation
Volume 2014 (2014), Article ID 215803, 10 pages
http://dx.doi.org/10.1155/2014/215803
Research Article

Capacity Analysis and Optimization in Heterogeneous Network with Adaptive Cell Range Control

1Beijing University of Posts and Telecommunications, Beijing 100876, China
2Beijing Key Lab of New Generation Broadband Wireless Mobile Communication Technology, Standard and Verification, China Academy of Telecommunication Research, Beijing 100191, China

Received 20 February 2014; Revised 7 April 2014; Accepted 8 April 2014; Published 29 April 2014

Academic Editor: Xiang Zhang

Copyright © 2014 Xinyu Gu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

As an attractive means of expanding mobile network capacity, heterogeneous network is regarded as an important direction of mobile network evolution. To increase the capacity of, for example, hot spots, a typical scenario in heterogeneous network is that the coverage areas of low power nodes (LPNs) are overlapped with macrocell. To increase the utilization of small cells generated by LPNs, cell range extension (CRE) is used to extend the coverage of the small cells by adding cell specific offset (CSO) to small cells during cell selection procedure. The value of CSO, however, needs to be set carefully. In this paper, the capacity of users in macrocells, users in small cells, and users in range extension areas is analyzed thoroughly in conditions with and without CRE. Based on the analysis, an adaptive CSO updating algorithm is proposed. The proposed algorithm updates the CSO value periodically by predicting the overall capacity and a new CSO value is selected which can give the optimal overall capacity. The proposed algorithm is evaluated by system-level simulations. Simulation results indicate that the proposed algorithm can ensure a nearly optimal performance in all tested traffic load situations.