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Energy efficiency and area spectral efficiency tradeoff for coexisting wireless body sensor networks

共存无线体域网的能效和区域频效折中

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Abstract

The coexistence of wireless body sensor networks (WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral efficiency are two key performance evaluation metrics for wireless communication networks. In this paper, the fundamental tradeoff between energy efficiency and area spectral efficiency of WBSNs is first investigated under the Poisson point process (PPP) model and Matern hard-core point process (HCPP) model using stochastic geometry. The circuit power consumption is taken into consideration in energy efficiency calculation. The tradeoff judgement coefficient is developed and is shown to serve as a promising complementary measure. In addition, this paper proposes a new nearest neighbour distance power control strategy to improve energy efficiency. We show that there exists an optimal transmit power highly dependant on the density of WBSNs and the nearest neighbour distance. Some important properties are also addressed in the analysis of coexisting WBSNs based on the IEEE 802.15.4 standard, such as the impact of intensity nodes distribution, optimal guard zone, and outage probability. Simulation results show that the proposed power control design can reduce the outage probability and enhance energy efficiency. Energy efficiency and area spectral efficiency of the HCPP model are better than those of the PPP model. In addition, the optimal density of WBSNs coexistence is obtained.

创新点

本文采用随机几何分析方法, 采用了两种随机几何模型: PPP(泊松点过程)模型和HCPP(中心点过程)模型, 提出了共存无线体域网络的能量效率和区域频谱效率的折中关系, 并对在两种模型下的能效和频效关系进行了比较, 得出了在一定共存密度下的可行域。另外, 本文还提出了一种基于邻居节点距离的功率控制方法。通过对无线体域网络共存的性能分析研究, 可对无线体域网的系统设计提供一种参考或依据。

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References

  1. Yang G Z. Body Sensor Networks. London: Springer, 2006. 1–397

    Book  Google Scholar 

  2. Pantelopoulos A, Bourbakis N G. A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans on Syst, 2010, 18: 1–12

    Article  Google Scholar 

  3. Martelli F, Verdone R. Coexistence issues for wireless body area networks at 2.45 GHz. In: Proceedings of European Wireless, Poznan, 2012. 18–20

    Google Scholar 

  4. Deylami M, Jovanov E. Performance analysis of coexisting IEEE 802.15.4-based health monitoring WBSNs. In: Proceedings of 34th Annual International Conference of the IEEE EMBS, San Diego, 2012. 2464–2467

    Google Scholar 

  5. Wang L S, Goursaud C, Nikaein N, et al. Cooperative scheduling for coexisting Body Area Networks. IEEE Trans Wirel Commun, 2012, 12: 123–133

    Article  Google Scholar 

  6. El Sawy H, Hossain E, Haenggi M. Stochastic geometry for modeling, analysis, and design of multi-tier and cognitive cellular wireless networks: a survey. IEEE Commun Surv Tut, 2013, 15: 996–1019

    Article  Google Scholar 

  7. Peng J L, Tang H, Hong P L, et al. Stochastic geometry analysis of energy efficiency in heterogeneous network with sleep control. IEEE Wirel Commun Lett, 2013, 2: 615–618

    Article  Google Scholar 

  8. Cavallari R, Martelli F, Rosini R. A survey on wireless body area networks: technologies and design challenges. IEEE Commun Surv Tut, 2014, 16: 1635–1657

    Article  Google Scholar 

  9. Williams B, Allen B, True H, et al. A real-time, mobile timed up and go system. In: Proceedings of IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, Cambridge, 2015. 9–12

    Google Scholar 

  10. Hata Y, Kobashi S, Kuramoto K, et al. Home care system for aging people confined to bed by detached sensor netork. In: Proceedings of IEEE Workshop on Robotic Intelligence In Informationally Structured Space (RiiSS), Paris, 2011. 1–6

    Google Scholar 

  11. Mitchell E, Ahmadi A, Richter C, et al. Automatically detecting asymmetric running using time and frequency domain features. In: Proceedings of IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, Cambridge, 2015. 1–6

    Google Scholar 

  12. IEEE Computer Society. IEEE 802.15.4 Standard, Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs). IEEE Std 802.15.4-2006. 2006

  13. IEEE Computer Society. IEEE Standard for Local and Metropolitan Area Networks Part 15.6: Wireless Body Area Networks. IEEE Std 802.15.6-2012. 2012

  14. Bluetooth SIG. Specification of the Bluetooth System. Version 4.0. 2010

    Google Scholar 

  15. Park P, Marco D P, Soldati P, et al. In: Proceeding of 6th Interference Conference on Mobile Adhoc and Sensor Systems, Macau, 2009. 130–139

    Google Scholar 

  16. Hesham E, Ekram H, Sergio C. Spectrum-efficient multi-channel design for coexisting IEEE 802.15.4 networks:a stochastic geometry approach. IEEE J Sel Area Commun, 2014, 13: 1611–1624

    Google Scholar 

  17. Zhang C Q, Wang Y L, Liang Y Q, et al. An energy-efficient MAC protocol for medical emergency monitoring body sensor networks. Sensors, 2016, 16: 1–19

    Article  Google Scholar 

  18. IEEE Computer Society. IEEE 802.15.4, Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs). Revision of IEEE Std 802.15.4-2003. 2006

  19. Otal B, Alonso L, Verikoukis C. Highly reliable energy-saving MAC for wireless body sensor networks in healthcare systems. IEEE J Sel Area Commun, 2009, 27: 553–565

    Article  Google Scholar 

  20. Su H, Zhang X. Battery-dynamics driven TDMA MAC protocols for wireless body-area monitoring networks in healthcare applications. IEEE J Sel Area Commun, 2009, 27: 424–434

    Article  Google Scholar 

  21. Kim T H, Ha J Y, Choi S. Improving spectral and temporal efficiency of collocated IEEE 802.15.4 LR-WPANs. IEEE Trans Mobile Comput, 2009, 8: 1596–1609

    Article  Google Scholar 

  22. Hong X M, 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

    Article  Google Scholar 

  23. Ku I, Wang C X, Thompson J. Spectral-energy efficiency tradeoff in relay-aided cellular networks. IEEE Trans Wirel Commun, 2013, 12: 4970–4982

    Article  Google Scholar 

  24. Ngo H Q, Larsson E G, Marzetta T L. Energy and spectral efficiency of very large multiuser MIMO Systems. IEEE Trans Commun, 2013, 61: 1436–1449

    Article  Google Scholar 

  25. Yao Y W, Cai X D, Giannakis G B. On energy efficiency and optimum resource allocation of relay transmissions in the low-power regime. IEEE Trans Wirel Commun, 2005, 4: 2917–2927

    Article  Google Scholar 

  26. Martelli F, Buratti C, Verdone R. Modeling query-based wireless CSMA networks through stochastic geometry. IEEE Trans Veh Technol, 2014, 63: 2876–2885

    Article  Google Scholar 

  27. Shah-Mansouri H, Pakravan M R, Khalaj B H. Analytical modeling and performance analysis of flooding in CSMAbased wireless networks. IEEE Trans Veh Technol, 2011, 60: 664–679

    Article  Google Scholar 

  28. Kim T S, Kim S L. Random power control in wireless Ad Hoc networks. IEEE Commun Lett, 2005, 9: 1046–1048

    Article  Google Scholar 

  29. Zhang X C, Haenggi M. Random power control in Poisson networks. IEEE Trans Commun, 2012, 60: 2602–2611

    Article  Google Scholar 

  30. Pei Y Y, Liang Y C, Leh K C, et al. Energy-efficient design of sequential channel sensing in cognitive radio networks: optimal sensing strategy, power allocation. IEEE J Sel Area Commun, 2011, 29: 1648–1659

    Article  Google Scholar 

  31. Tang S S, Zhang Y, Zhang L Q, et al. Spectrum-efficient wireless sensor networks. Int J Distrib Sens N, 2015, 11: 1–2

    Google Scholar 

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

    Article  Google Scholar 

  33. Zhang L, Yang H C, Hasna M O. Generalized area spectral efficiency: an effective performance metric for green wireless communications. IEEE Trans Commun, 2014, 62: 5367–5380

    Google Scholar 

  34. Akhtman J, Hanzo L. Power versus bandwidth efficiency in wireless communications: the economic perspective. In: Proceedings of IEEE 70th hicular Technology Conference-Fall, Alaska, 2009. 1–5

    Google Scholar 

  35. Guo W, OFarrell T. Capacity-energy-cost tradeoff in small cell networks. In: Proceedings of IEEE 75th hicular Technology Conference-Spring, Yokohama, 2012. 1–5

    Google Scholar 

  36. Ha J Y, Kim T H, Park H S, et al. An enhanced CSMA-CA algorithm for IEEE 802.15.4 LR-WPANs. IEEE Commun Lett, 2007, 11: 461–463

    Article  Google Scholar 

  37. Baccelli F, Blaszczyszyn B. Stochastic Geometry and Wireless Networks, Volume II: Applications. Paris: Now Press, 2005. 68–88

    MATH  Google Scholar 

  38. Sousa E S, Silvester J. Optimum transmission ranges in a direct- sequence spread-spectrum multihop packet radio network. IEEE J Sel Area Commun, 1990, 8: 762–771

    Article  Google Scholar 

  39. Hasan A, Andrews J G. The guard zone in wireless Ad hoc networks. IEEE Trans Wirel Commun, 2007, 6: 897–906

    Article  Google Scholar 

  40. Haenggi M, On distances in uniformly random networks. IEEE Trans Inf Theory, 2005, 51: 3584–3586

  41. Chiu S N, Stoyan D, Kendall W S, et al. Stochastic Geometry and Its Applications. 3rd ed. UK: Wiley Press, 2013. 35–55

    MATH  Google Scholar 

  42. Busson A, Chelius G, Gorce J. Interference Modeling in CSMA Multi-Hop Wireless Networks. Research Report–6624, INRIA. 2009

    Google Scholar 

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Correspondence to Cheng-Xiang Wang.

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Liu, R., Wang, Y., Wu, S. et al. Energy efficiency and area spectral efficiency tradeoff for coexisting wireless body sensor networks. Sci. China Inf. Sci. 59, 122311 (2016). https://doi.org/10.1007/s11432-016-0320-1

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