Abstract
Due to numerous base stations (BSs) being randomly deployed in ultra-dense networks (UDNs), the co-tier interference and cross-tier interference become more and more serious. We propose an interference management scheme based on joint clustering, subchannel allocation and successive cancellation among users for UDN taking all types of interference into consideration. To reduce the co-tier interference, we design a clustering algorithm based on interference graph to divide femto base stations (FBSs) and femto user equipments (FUEs) into FBS clusters and FUE groups respectively. Then a subchannel allocation algorithm is presented for FBS clusters to avoid the cross-tier interference. Moreover, a successive interference cancellation (SIC) detection algorithm is used to abate the interference among users in the same FUE group. Our analysis and simulations show that the proposed scheme outperforms other schemes in terms of system capacity and spectral efficiency in several scenarios. The results also verify that the proposed scheme can not only effectively mitigate the interference, but also have advantages in meeting the requirements of users and improving the network performance.
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References
Bhushan, N., Li, J., Malladi, D., et al: Network densification: the dominant theme for wireless evolution into 5G. IEEE Commun. Mag. 52(2), 82–89 (2014)
Ni, S., Zhao, J., Gong, Y.: Optimal pilot design in massive MIMO systems based on channel estimation. IET Commun. 11(7), 975–984 (2017)
Wang, B., Gao, F., Jin, S., et al: Spatial and frequency wideband effects in millimeter-wave massive MIMO systems. IEEE Trans. Signal Process. 66(13), 3393–3406 (2018)
Niu, C., Li, Y., Hu, R.Q., et al: Fast and efficient radio resource allocation in dynamic ultra-dense heterogeneous networks. IEEE Access 5, 1911–1924 (2017)
Ge, X., Tu, S., Mao, G., et al: 5G ultra-dense cellular networks. IEEE Wirel. Commun. 23(1), 72–79 (2016)
Zhou, Y., Liu, L., Du, H., et al: An overview on intercell interference management in mobile cellular networks: from 2G to 5G. In: 2014 IEEE International Conference on Communication Systems (ICCS), Macau, China, pp. 217–221 (2014)
Ni, S.J., Zhao, J.H., Yang, H.H., Quek, T.Q.S., Gong, Y.: Small cell range expansion with interference mitigation for downlink massive MIMO HetNets. In: 2018 IEEE Global Communications Conference (GLOBECOM) (2018)
Lopez-Perez, D., Guvenc, I., Roche, G.D.L., et al.: Enhanced intercell interference coordination challenges in heterogeneous networks. IEEE Wirel. Commun. 18(3), 22–30 (2011)
Kaimaletu, S., Krishnan, R., Kalyani, S., et al.: Cognitive interference management in heterogeneous femto-macro cell networks. In: 2011 IEEE International Conference on Communications (ICC), Kyoto, Japan, pp. 1–6 (2011)
Hosseini, K., Dahrouj, H., Adve, R.: Distributed clustering and interference management in two-tier networks. In: 2012 IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, USA, pp. 4267–4272 (2012)
Abdelnasser, A., Hossain, E., Dong, I.K.: Clustering and resource allocation for dense FBSs in a two-tier cellular OFDMA network. IEEE Trans. Wirel. Commun. 13(3), 1628–1641 (2014)
Wei, R., Wang, Y., Zhang, Y.: A two-stage cluster-based resource management scheme in ultra-dense networks. In: 2014 IEEE International Conference on Communications in China (ICCC), Shanghai, China, pp. 738–742 (2014)
Liang, L., Wang, W., Jia, Y., et al: A cluster-based energy-efficient resource management scheme for ultra-dense networks. IEEE Access 4, 6823–6832 (2016)
Dai, J., Wang, S.: Clustering-based interference management in densely deployed femtocell networks. Digital Commun. Netw. 2(4), 175–183 (2016)
Nam, W., Bai, D., Lee, J., Kang, I.: Advanced interference management for 5G cellular networks. IEEE Commun. Mag. 52(5), 52–60 (2014)
Chang, Y.J., Tao, Z., Zhang, J., et al.: A graph-based approach to multi-cell OFDMA downlink resource allocation. In: 2008 IEEE Global Telecommunications Conference, New Orleans, LO, USA, pp. 1–6 (2008)
Acknowledgements
This work is supported by the Fundamental Research Funds for the Central Universities (No. 2019YJS009), the National Natural Science Foundation of China (61661021), National Science and Technology Major Project of the Ministry of Science and Technology of China (2016ZX03001014-006), the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2017D14), Beijing Jiaotong University, Shenzhen Science and Technology Program under Grant (No. JCYJ20170817110410346).
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Yang, L., Zhao, J., Gao, F., Gong, Y. (2020). A Cluster-Based Interference Management with Successive Cancellation for UDNs. In: Ye, B., Zhuang, W., Guo, S. (eds) 2nd International Conference on 5G for Ubiquitous Connectivity. 5GU 2018. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-22316-8_5
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DOI: https://doi.org/10.1007/978-3-030-22316-8_5
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