5G green cellular networks considering power allocation schemes

基于功率分配的5G绿色蜂窝网络

Abstract

It is important to assess the effect of transmit power allocation schemes on the energy consumption on random cellular networks. The energy efficiency of 5G green cellular networks with average and water-filling power allocation schemes is studied in this paper. Based on the proposed interference and achievable rate model, an energy efficiency model is proposed for MIMO random cellular networks. Furthermore, the energy efficiency with average and water-filling power allocation schemes are presented, respectively. Numerical results indicate that the maximum limits of energy efficiency are always there for MIMO random cellular networks with different intensity ratios of mobile stations (MSs) to base stations (BSs) and channel conditions. Compared with the average power allocation scheme, the water-filling scheme is shown to improve the energy efficiency of MIMO random cellular networks when channel state information (CSI) is attainable for both transmitters and receivers.

创新点

本文提出一种基于MIMO随机蜂窝网的能量效率评估模型,进而依托该模型分析了平均功率分配和注水分配方案下的蜂窝网能量效率,并给出了能效所能达到的最优仿真结果。上述研究成果对于优化多天线蜂窝网能效设计具有一定的价值。

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References

  1. 1

    Cisco. Cisco visual networking index: global mobile data traffic forecast update, 2013-2018. http: //www.cisco.com/ c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white paper c11-520862.html. 2014

  2. 2

    Chen T, Kim H, Yang Y. Energy efficiency metrics for green wireless communications. In: Proceedings of 2010 International Conference on Wireless Communications and Signal Processing (WCSP), Suzhou, 2010. 1–6

    Google Scholar 

  3. 3

    Alfano G, Chong Z, Jorswieck E. Energy-efficient power control for MIMO channels with partial and full CSI. In: Proceedings of International ITG Workshop on Smart Antennas, Dresden, 2012. 332–337

    Google Scholar 

  4. 4

    Liu L, Miao G, Zhang J. Energy-efficient scheduling for downlink multi-user MIMO. In: Proceedings of IEEE International Conference on Communications (ICC), Ottawa, 2012. 4394

    Google Scholar 

  5. 5

    Jiang J, Dianati M, Imran M A, et al. Energy-efficiency analysis and optimization for virtual-MIMO systems. IEEE Trans Veh Tech, 2014, 63: 2272–2283

    Article  Google Scholar 

  6. 6

    Chen L, Yang Y, Chen X, et al. Energy-efficient link adaptation on Rayleigh fading channel for OSTBC MIMO system with imperfect CSIT. IEEE Trans Veh Tech, 2013, 62: 1577–1585

    Article  Google Scholar 

  7. 7

    Jiang C, Cimini L J. Energy-efficient transmission for MIMO interference channels. IEEE Trans Wirel Commun, 2013, 12: 2988–2999

    Article  Google Scholar 

  8. 8

    Jiang C, Cimini L J. Antenna selection for energy-efficient MIMO transmission. IEEE Wirel Commun Lett, 2012, 1: 577–580

    Article  Google Scholar 

  9. 9

    Garcia V, Chen C S, Lebedev N, et al. Self-optimized precoding and power control in cellular networks. In: Proceedings of IEEE 22nd International Symposium on Personal Indoor and Mobile Radio Communications, Toronto, 2011. 81–85

    Google Scholar 

  10. 10

    Chong Z, Jorswieck E. Energy-efficient power control for MIMO time-varying channels. In: Proceedings of IEEE Online Conference on Green Communications (GreenCom), New York, 2011. 92–97

    Google Scholar 

  11. 11

    Joung J, Sun S. Energy efficient power control for distributed transmitters with ZF-based multiuser MIMO precoding. IEEE Commun Lett, 2013, 17: 1766–1769

    Article  Google Scholar 

  12. 12

    Davaslioglu K, Ayanoglu E. Quantifying potential energy efficiency gain in green cellular wireless networks. IEEE Commun Surv Tut, 2014, 16: 2065–2091

    Article  Google Scholar 

  13. 13

    Hasan Z, Boostanimehr H, Bhargava V K. Green cellular networks: a survey, some research issues and challenges. IEEE Commun Surv Tut, 2011, 13: 524–540

    Article  Google Scholar 

  14. 14

    Zou Y, Zhu J, Zhang R. Exploiting network cooperation in green wireless communication. IEEE Trans Commun, 2013, 61: 999–1010

    Article  Google Scholar 

  15. 15

    Han T, Ansari N. On greening cellular networks via multicell cooperation. IEEE Wirel Commun, 2013, 20: 82–89

    Article  Google Scholar 

  16. 16

    Li C, Zhang J, Letaief K. Throughput and energy efficiency analysis of small cell networks with multi-antenna base stations. IEEE Trans Wirel Commun, 2014, 13: 2505–2517

    Article  Google Scholar 

  17. 17

    Nguyen T M, Shin H, Quek T Q S. Network throughput and energy efficiency in MIMO femtocells. In: Proceedings of 18th European Wireless Conference, Poznan, 2012. 1–5

    Google Scholar 

  18. 18

    Soh Y S, Quek T Q S, Kountouris M, et al. Energy efficient heterogeneous cellular networks. IEEE J Sel Area Commun, 2013, 31: 840–850

    Article  Google Scholar 

  19. 19

    Karray M K. Spectral and energy efficiencies of OFDMA wireless cellular networks. In: Proceedings of IFIP Wireless Days, Venice, 2010. 1–5

    Google Scholar 

  20. 20

    Xiang L, Ge X, Wang C X, et al. Energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption. IEEE Trans Wirel Commun, 2013, 12: 961–973

    Article  Google Scholar 

  21. 21

    Chen M, Zhang Y, Li Y, et al. EMC: emotion-aware mobile cloud computing in 5G. IEEE Netw, 2015, 29: 32–38

    Article  Google Scholar 

  22. 22

    Chen M, Hao Y, Li Y, et al. On the computation offloading at Ad Hoc cloudlet: architecture and service models. IEEE Commun, 2015, 53: 18–24

    Article  Google Scholar 

  23. 23

    Chen M, Zhang Y, Hu L, et al. Cloud-based wireless network: virtualized, reconfigurable, smart wireless network to enable 5G technologies. ACM/Springer Mobile Netw Appl, 2015, 20: 704–712

    Article  Google Scholar 

  24. 24

    Wang C-X, Haider F, Gao X, et al. Cellular architecture and key technologies for 5G wireless communication networks. IEEE Commun Mag, 2014, 52: 122–130

    Article  Google Scholar 

  25. 25

    Yang X, Petropulu A P. Co-channel interference modeling and analysis in a Poisson field of interferers in wireless communications. IEEE Trans Signal Process, 2003, 51: 64–76

    MathSciNet  Article  MATH  Google Scholar 

  26. 26

    Ferenc J S, Néda Z. On the size distribution of Poisson Voronoi cells. Phys A: Stat Mech Appl, 2007, 385: 518–526

    Article  Google Scholar 

  27. 27

    Stoyan D, Kendall W S. Stochastic Geometry and Its Applications. 2nd ed. Hoboken: Wiley, 1996

    Google Scholar 

  28. 28

    Al-Ahmadi S, Yanikomeroglu H. On the approximation of the generalized-K PDF by a Gamma PDF using the moment matching method. In: Proceedings of IEEE Wireless Communications and Networking Conference, Budapest, 2009. 1–6

    Google Scholar 

  29. 29

    Kostic I M. Analytical approach to performance analysis for channel subject to shadowing and fading. IEEE Proc Commun, 2005, 152: 821–827

    Article  Google Scholar 

  30. 30

    Bithas P S, Sagias N C, Mathiopoulos P T, et al. On the performance analysis of digital communications over generalized-K fading channels. IEEE Commun Lett, 2006, 10: 353–355

    Article  Google Scholar 

  31. 31

    Simon M K, Alouini M S. Digital Communication over Fading Channels: a Unified Approach to Performance Analysis. Hoboken: Wiley, 2000

    Google Scholar 

  32. 32

    Dai L, Wang Z, Yang Z. Time-frequency training OFDM with high spectral efficiency and reliable performance in high speed environments. IEEE J Sel Area Commun, 2012, 30: 695–707

    Article  Google Scholar 

  33. 33

    Annapureddy V S, Veeravalli V V. Sum capacity of MIMO interference channels in the low interference regime. IEEE Trans Inf Theory, 2011, 57: 2565–2581

    MathSciNet  Article  Google Scholar 

  34. 34

    Win M Z, Pinto P C, Shepp L. A mathematical theory of network interference and its applications. Proc IEEE, 2009, 97: 205–230

    Article  Google Scholar 

  35. 35

    Ge X, Huang K, Wang C X, et al. Capacity analysis of a multi-cell multi-antenna cooperative cellular network with co-channel interference. IEEE Trans Wirel Commun, 2011, 10: 3298–3309

    Article  Google Scholar 

  36. 36

    Alouini M S, Goldsmith A J. Area spectral efficiency of cellular mobile radio systems. IEEE Trans Veh Tech, 1999, 48: 1047–1066

    Article  Google Scholar 

  37. 37

    Abdi A, Kaveh M. K distribution: an appropriate substitute for Rayleigh-lognormal distribution in fading-shadowing wireless channels. Electron Lett, 1998, 34: 851–852

    Article  Google Scholar 

  38. 38

    Gradshteyn I S, Ryzhik I M. Table of Integrals, Series, and Products. New York: Academic Press, 2007

    Google Scholar 

  39. 39

    Chong Z, Jorswieck E. Analytical foundation for energy efficiency optimisation in cellular networks with elastic traffic. Mobile Lightweight Wirel Syst, 2012, 81: 18–29

    Article  Google Scholar 

  40. 40

    Arnold O, Richter F, Fettweis G, et al. Power consumption modeling of different base station types in heterogeneous cellular networks. In: Proceedings of IEEE Future Network and Mobile Summit, Florence, 2010. 1–8

    Google Scholar 

  41. 41

    Yu H, Zhong L, Sabharwal A. Power management of MIMO network interfaces on mobile systems. IEEE Trans Very Large Scale Integration (VLSI) Syst, 2012, 20: 1175–1186

    Article  Google Scholar 

  42. 42

    Silva A P, Mateus G R. Performance analysis for data service in third generation mobile telecommunication networks. In: Proceedings of 35th Annual IEEE Simulation Symposium, San Deigo, 2002. 227–234

    Google Scholar 

  43. 43

    Dighe P, Mallik R K, Jamuar S S. Analysis of transmit-receive diversity in Rayleigh fading. IEEE Trans Commun, 2003, 51: 694–703

    Article  Google Scholar 

  44. 44

    Khoshnevisan M, Laneman J N. Power allocation in multi-antenna wireless systems subject to simultaneous power constraints. IEEE Trans Commun, 2012, 60: 3855–3864

    Article  Google Scholar 

  45. 45

    Lu Y, Zhang W. Water-filling capacity analysis in large MIMO systems. In: Proceeding of IEEE Computing, Communications and IT Applications Conference (ComComAp), Hong Kong, 2013. 186–190

    Google Scholar 

  46. 46

    Xu J, Qiu L. Energy efficiency optimization for MIMO broadcast channels. IEEE Trans Wirel Commun, 2013, 12: 690–701

    Article  Google Scholar 

  47. 47

    Hong X, Jie Y, Wang C-X, et al, Energy-spectral efficiency trade-off in virtual MIMO cellular systems. IEEE J Sel Area Commun, 2013, 31: 2128–2140

  48. 48

    Chen R, Andrews J G, Jr Heath R W, et al. Uplink power control in multi-cell spatial multiplexing wireless systems. IEEE Trans Wirel Commun, 2007, 6: 2700–2711

    Article  Google Scholar 

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Correspondence to Jing Zhang.

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Ge, X., Chen, J., Wang, CX. et al. 5G green cellular networks considering power allocation schemes. Sci. China Inf. Sci. 59, 1–14 (2016). https://doi.org/10.1007/s11432-015-5502-8

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Keywords

  • energy efficiency
  • cellular networks
  • MIMO
  • achievable rate model
  • power allocation scheme

Keywords

  • 022308

关键词

  • 能量效率
  • 蜂窝网络
  • MIMO
  • 可达速率模型
  • 功率分配方案