Abstract
A novel LBG-based user clustering algorithm is proposed to reduce interference efficiently in Ultra-Dense Network (UDN). There are two stages, weight design and user clustering. Because a user could interfere and be interfered by other users at the same time, a balanced cooperative transmission strategy is utilized in weight design. The improved LBG algorithm is used for user clustering, which overcomes the shortcoming of local optimum of conventional LBG. Moreover, this algorithm is superior to conventional LBG in computational complexity. Simulation results show that the sum rate of cell-edge users increases a lot compared to the reference algorithm, and the average system throughput gets higher obviously.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yunas, S., Valkama, M., Niemela, J.: Spectral and energy efficiency of Ultra-Dense Networks under different eployment strategies. IEEE Commun. Mag. 53(1), 90–100 (2015)
Wang, C., Hu, B., Chen, S., et al.: Joint dynamic access points grouping and resource allocation for coordinated transmission in user-centric UDN. Trans. Emerg. Telecommun. Technol. 29(3), e3265 (2017)
Kunitaka, M., Tomoaki, O.: Orthogonal beamforming using Gram-Schmidt orthogonalization for downlink CoMP system. ITE Tech. Rep. 36(10), 17–20 (2012)
Bu, H.W., Xu, Y.H., Yuan, Z., Hu, Y.J., Yi, H.Y.: An efficient method for managing CoMP cooperating set based on central controller in LTE-A systems. Appl. Mech. Mater. 719–720, 721–726 (2015)
Bassoy, S., Farooq, H., Imran, M.A., Imran, A.: Coordinated multi-point clustering schemes: a survey. IEEE Commun. Surv. Tutor. 19(2), 743–764 (2017)
Grebla, G., Birand, B., van de Ven, P., Zussman, G.: Joint transmission in cellular networks with CoMP-stability and scheduling algorithms. Perform. Eval. 91(C), 38–55 (2015)
Du, T., Qu, S., Liu, F., Wang, Q.: An energy efficiency semi-static routing algorithm for WSNs based on HAC clustering method. Inf. Fusion 21(1), 18–29 (2015)
Xu, D., Ren, P., Du, Q., Sun, L.: Joint dynamic clustering and user scheduling for downlink cloud radio access network with limited feedback. China Commun. 12(12), 147–159 (2015)
Ali, S.S., Saxena, N.: A novel static clustering approach for CoMP. In: IEEE 7th International Conference on Computing and Convergence Technology (ICCCT), Seoul, South Korea, pp. 757–762. IEEE Press (2012)
Wan, Q.: Research on multi-cell clustering cooperative technology in CoMP scene. Beijing University of Posts and Telecommunications, Beijing (2015)
Meng, N., Zhang, H.T., Lu, H.T.: Virtual cell-based mobility enhancement and performance evaluation in Ultra-Dense Networks. In: IEEE Wireless Communications and Networking Conference, Doha, Qatar, pp. 1–6. IEEE Press (2016)
Kurras, M., Fahse, S., Thiele, L.: Density based user clustering for wireless massive connectivity enabling Internet of Things. In: Globecom Workshops (GCWkshps), San Diego, CA, USA, pp. 1–6. IEEE Press (2015)
Patané, G., Russo, M.: The enhanced LBG algorithm. Neural Netw. Off. J. Int. Neural Netw. Soc. 14(9), 1219 (2001)
Wang, J., Tang, S., Sun, C.: Resource allocation based on user clustering in ultra-dense small cell networks. J. Xi’an Univ. Posts Telecommun. 21(1), 16–20 (2016)
Gong, J., Zhou, S., Niu, Z., et al.: Joint scheduling and dynamic clustering in downlink cellular networks. In: Global Telecommunications Conference (Globecom), Houston, Texas, USA, pp. 1–5. IEEE Press (2011)
Ho, Z.K.M., Gesbert, D.: Balancing egoism and altruism on interference channel: the MIMO case. In: International Conference on Communications (ICC), Cape Town, South Africa, pp. 1–5. IEEE Press (2010)
Jindal, N., Rhee, W., Vishwanath, S., et al.: Sum power iterative water-filling for multi-antenna Gaussian broadcast channels. IEEE Trans. Inf. Theory 51(4), 1570–1580 (2015)
Acknowledgement
This work was supported by National Science and Technology Major Project of the Ministry of Science and Technology of China (ZX201703001012-005), National Natural Science Foundation of China (61501371), Shaanxi STA International Cooperation and Exchanges Project (2017KW-011) and the Department of Education Shaanxi Province, China, under Grant 2013JK1023.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Liang, Y. et al. (2019). An Improved LBG Algorithm for User Clustering in Ultra-Dense Network. In: Krömer, P., Zhang, H., Liang, Y., Pan, JS. (eds) Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2018. Advances in Intelligent Systems and Computing, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-03766-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-03766-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03765-9
Online ISBN: 978-3-030-03766-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)