Dynamic Clustering of Coordinated Multi-point Transmission Based on Friends Algorithm

HENG Wei; LIANG Tian; MENG Chao; LI Shihuan; LU Xiaowen

doi:10.1049/cje.2015.04.032

Volume 24 Issue 2

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HENG Wei, LIANG Tian, MENG Chao, et al., “Dynamic Clustering of Coordinated Multi-point Transmission Based on Friends Algorithm,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 414-418, 2015, doi: 10.1049/cje.2015.04.032

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HENG Wei, LIANG Tian, MENG Chao, et al., “Dynamic Clustering of Coordinated Multi-point Transmission Based on Friends Algorithm,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 414-418, 2015, doi: 10.1049/cje.2015.04.032

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Dynamic Clustering of Coordinated Multi-point Transmission Based on Friends Algorithm

doi: 10.1049/cje.2015.04.032

National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61471115), the National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2014ZX03003010-002), the General Program of Natural Science Foundation of Jiangsu Province (No.BK20131299), the Program of Postgraduate Scientific Research and Innovation Projects of Jiangsu Province (No.CXZZ130099), the Research Fund of National Mobile Communications Research Laboratory, Southeast University (No.2014A02).

Publish Date: 2015-04-10

Abstract

Abstract

Coordinated multi-point (CoMP) transmission has been regarded as a fascinating technology for 4G wireless communication systems. In this paper, the CoMP dynamic clustering problem is studied, a Friends algorithm (F-A) is proposed based on the procedure of making friends in human society, and then a dynamic clustering scheme is proposed based on F-A. The mutual interference among cells of the network is considerate in this algorithm, which can be obtained by CSI feedback. Compared to Traversal search (T-S) algorithm, the proposed algorithm has lower computational complexity, and the performance is almost equal. Simulation results show the proposed scheme is effective for dynamic clustering.
- Coordinated multi-point (CoMP),
- Static clustering,
- Dynamic clustering,
- Friends algorithm

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References(11)

References

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