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A power adjustment based eICIC algorithm for hyper-dense HetNets considering the alteration of user association

用户关联变化情况下一种基于功率调整的超密集异构网干扰协调算法

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Abstract

This paper evaluates power adjustment based enhanced inter-cell interference coordination (eICIC) problem in the hyper-dense HetNet under the practical serving cell selection rule where each user selects the base station with the strongest received signal power as its serving cell while the alteration of the serving cell happens during the power adjusting process. In this paper, the eICIC problem is solved by cooperatively adjusting the transmission power of all small cells. A power adjustment method based on modified particle swarm optimization (MPSO) is proposed to tackle the NP-hard eICIC problem caused by the alteration of the serving cell, and considering the drawbacks of MPSO, an improved MPSO is proposed for effective algorithm. Local search and multi-restart process are introduced in the improved MPSO based eICIC algorithm to guarantee the local and then global optimality, and the convergence conditions and the global optimality are proved by mathematical deduction to guide the selection of the parameters. Simulations show that, while considering the fifty-picocell case as an example, the proposed improved MPSO based eICIC algorithm can increase the system throughput by 66.0% compared with the full power transmission, and compared with the existing schemes which do not alter the serving cells, the proposed algorithm can improve the system throughput by 32.2%. By improving MPSO, the consequent algorithm costs less iteration time to achieve higher system throughput, and it is effective and feasible to solve the eICIC problem in the hyper-dense HetNet.

创新点

在用户关联服务小区随基站发送功率变化的情况下, 研究超密集异构网中基于微微站功率调整的增强型小区间干扰协调问题。首先,提出基于改进粒子群优化 (MPSO) 的功率调整算法来解决由服务小区随功率变化来带的NP-hard问题。然后改进MPSO, 提升算法的性能, 保证算法的局部乃至全局最优性, 并证明算法收敛条件和全局最优性。最后, 通过仿真实验验证所提算法性能。

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References

  1. Hwang I, Song B, Somiman S S, et al. A holistic view on hyperdense heterogeneous and small cell networks. IEEE Commun Mag, 2013, 51: 20–27

    Article  Google Scholar 

  2. Xu Z Z, Qin W D, Tang Q Y, et al. Energy-efficient cognitive access approach to convergence communications. Sci China Inf Sci, 2014, 57: 042305

    Google Scholar 

  3. Nakamura T, Nagata S, Benjebbour A, et al. Trends in small cell enhancements in LTE advanced. IEEE Commun Mag, 2013, 51: 98–105

    Article  Google Scholar 

  4. Guvenc I, Quek T Q S, Kountouris M, et al. Heterogeneous and small cell networks: part 1. IEEE Commun Mag, 2013, 51: 34–35

    Article  Google Scholar 

  5. Bhushan N, Li J Y, Malladi D, et al. Network densification: the dominant theme for wireless evolution into 5G. IEEE Commun Mag, 2014, 52: 82–89

    Article  Google Scholar 

  6. Deb S, Monogioudis P, Miernik J, et al. Algorithms for enhanced inter-cell interference coordination (eICIC) in LTE HetNets. IEEE/ACM Trans Netw, 2014, 22: 137–150

    Article  Google Scholar 

  7. Peng Y, Qin F. Exploring Het-Net in LTE-advanced system: interference mitigation and performance improvement in macro-pico scenario. In: Proceedings of IEEE International Conference on Communications Workshops (ICC), Kyoto, 2011. 1–5

    Google Scholar 

  8. Hu R Q, Qian Y, Li W. On the downlink time, frequency and power coordination in an LTE relay network. In: Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), Houston, 2011

    Google Scholar 

  9. Xu Y H, Wang J L, Wu Q H, et al. Opportunistic spectrum access in cognitive radio networks: global optimization using local interaction games. IEEE J Sel Top Signal Process, 2012, 6: 180–194

    Article  MathSciNet  Google Scholar 

  10. Xu Y H, Wu Q H, Wang J L, et al. Opportunistic spectrum access using partially overlapping channels: graphical game and uncoupled learning. IEEE Trans Commun, 2013, 61: 3906–2918

    Article  Google Scholar 

  11. Jiang H L, Wang H, Zhu W X, et al. Carrier aggregation based interference coordination for LTE-A macro-pico Het-Net. In: Proceedings of IEEE Vehicular Technology Conference (VTC Spring), Dresden, 2013. 1–6

    Google Scholar 

  12. Ngo D T, Khakurel S, Le-Ngoc T. Joint subchannel assignment and power allocation for OFDMA femtocell networks. IEEE Trans Wirel Commun, 2014, 13: 342–355

    Article  Google Scholar 

  13. Li W, Delicatob F C, Pires P F, et al. Efficient allocation of resources in multiple heterogeneous Wireless Sensor Networks. J Parallel Distrib Comput, 2014, 74: 1775–1788

    Article  Google Scholar 

  14. Chen J M, Wang P, Zhang J. Adaptive soft frequency reuse scheme for in-building dense femtocell networks. China Commun, 2013, 10: 44–55

    Google Scholar 

  15. Nagaraj S, Raghavendra M R, Fleming P J, et al. Multi-cell distributed interference cancelation for co-operative pico-cell clusters. In: Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), Anaheim, 2012. 4193–9199

    Google Scholar 

  16. Pateromichelakis E, Shariat M, Quddus A, et al. Dynamic clustering framework for multi-cell scheduling in dense small cell networks. IEEE Commun Lett, 2013, 17: 1802–1805

    Article  Google Scholar 

  17. Abdelnasser A, Hossain E, Dong I K. Clustering and resource allocation for dense femtocells in a two-tier cellular OFDMA network. IEEE Trans Wirel Commun, 2014, 13: 1628–1641

    Article  Google Scholar 

  18. Yang L, Wen P P. Location based autonomous power control for ICIC in LTE-A heterogeneous networks. In: Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), Houston, 2011

    Google Scholar 

  19. Li Q C, Wu G, Hu R Q. Analytical study on network spectrum efficiency of ultra dense networks. In: Proceedings of IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), London, 2013. 2764–2768

    Google Scholar 

  20. Li Q, Hu R Q, Xu Y R, et al. Optimal fractional frequency reuse and power control in the heterogeneous wireless networks. IEEE Trans Wirel Commun, 2013, 12: 2658–2668

    Article  Google Scholar 

  21. Duy T N, Long B L, Le-Ngoc T. Distributed pareto-optimal power control for utility maximization in femtocell networks. IEEE Trans Wirel Commun, 2012, 11: 3434–3446

    Article  Google Scholar 

  22. Liang L, Feng G. A game-theoretic framework for interference coordination in OFDMA relay networks. IEEE Trans Veh Technol, 2012, 61: 321–332

    Article  Google Scholar 

  23. Simsek M, Czylwik A. Improved decentralized fuzzy Q-learning for interference reduction in heterogeneous LTEnetworks. In: Proceedings of 17th International OFDM Workshop, Essen, 2012. 1–6

    Google Scholar 

  24. Han S J, Young J S, Xia P, et al. Heterogeneous cellular networks with flexible cell association: a comprehensive downlink SINR analysis. IEEE Trans Wirel Commun, 2012, 11: 3484–3495

    Article  Google Scholar 

  25. Shi Y, Eberhart R. A modified particle swarm optimizer. In: Proceedings of IEEE World Congress on Computational Intelligence, Anchorage, 1998. 69–73

    Google Scholar 

  26. Zhang H J, Llorca J, Davis C, et al. Nature-inspired self-organization, control, and optimization in heterogeneous wireless networks. IEEE Trans Mob Comput, 2012, 11: 1207–1222

    Article  Google Scholar 

  27. Ghazzai H, Yaacoub E, Alouini M, et al. Optimized smart grid energy procurement for LTE networks using evolutionary algorithms. IEEE Trans Veh Technol, 2014, 99: 1–12

    Google Scholar 

  28. Li Y L, Shao W, You L, et al. An improved PSO algorithm and its application to UWB antenna design. IEEE Antenn Wirel Propag Lett, 2013, 12: 1236–1239

    Article  Google Scholar 

  29. Li Z H, Wang H, Pan Z W, et al. QoS and channel state aware load balancing in 3GPP LTE multi-cell networks. Sci China Inf Sci, 2013, 56: 042309

    MathSciNet  Google Scholar 

  30. Wang H, Liu N, Wu P, et al. Three novel opportunistic scheduling algorithms in CoMP-CSB scenario. Sci China Inf Sci, 2013, 56: 082301

    MathSciNet  Google Scholar 

  31. Stephen B, Lieven V. Convex Optimization. Cambridge: Cambridge University Press, 2009. 136–146

    Google Scholar 

  32. van den Bergh F. An Analysis of Particle Swarm Optimizers. Dissertation for the Doctoral Degree. Pretoria: University of Pretoria, 2006

    Google Scholar 

  33. Yang X M, Yuan J S, Yuan J Y, et al. A modified particle swarm optimizer with dynamic adaptation. Appl Math Comput, 2007, 189: 1205–1213

    Article  MathSciNet  Google Scholar 

  34. 3GPP. 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Further Advancements for E-UTRA Physical Layer Aspects (Release 9). Technical Report 3GPP TR 36.814 V9.0.0. 2010

    Google Scholar 

  35. Kim K, Shin Y. An improved power allocation scheme using particle swarm optimization in cooperative wireless communication systems. In: Proceedings of Asia-Pacific Conference on Communications, Sabah, 2011. 654–658

    Chapter  Google Scholar 

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Authors and Affiliations

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

    HuiLin Jiang, En Tong, ZhiHang Li, Nhu Quan Phan, ZhiWen Pan, Nan Liu & XiaoHu You

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  1. HuiLin Jiang
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  2. En Tong
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  3. ZhiHang Li
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  4. Nhu Quan Phan
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  5. ZhiWen Pan
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  6. Nan Liu
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  7. XiaoHu You
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Correspondence to ZhiWen Pan.

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Jiang, H., Tong, E., Li, Z. et al. A power adjustment based eICIC algorithm for hyper-dense HetNets considering the alteration of user association. Sci. China Inf. Sci. 58, 1–15 (2015). https://doi.org/10.1007/s11432-014-5204-7

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  • DOI: https://doi.org/10.1007/s11432-014-5204-7

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