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Cited by 243Bluetooth and Wireless Communication TechnologiesWireless Body Area NetworksEnergy Efficient Wireless Sensor Networks

Performance Evaluation of Bluetooth Low Energy: A Systematic Review

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Tosi, Jacopo, Taffoni, Fabrizio, Santacatterina, Marco, Sannino, Roberto, Formica, Domenico·2017·Sensors
DOI 10.3390/s17122898PMC PMC5751532
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Abstract

Small, compact and embedded sensors are a pervasive technology in everyday life for a wide number of applications (e.g., wearable devices, domotics, e-health systems, etc.). In this context, wireless transmission plays a key role, and among available solutions, Bluetooth Low Energy (BLE) is gaining more and more popularity. BLE merges together good performance, low-energy consumption and widespread diffusion. The aim of this work is to review the main methodologies adopted to investigate BLE performance. The first part of this review is an in-depth description of the protocol, highlighting the main characteristics and implementation details. The second part reviews the state of the art on BLE characteristics and performance. In particular, we analyze throughput, maximum number of connectable sensors, power consumption, latency and maximum reachable range, with the aim to identify what are the current limits of BLE technology. The main results can be resumed as follows: throughput may theoretically reach the limit of ~230 kbps, but actual applications analyzed in this review show throughputs limited to ~100 kbps; the maximum reachable range is strictly dependent on the radio power, and it goes up to a few tens of meters; the maximum number of nodes in the network depends on connection parameters, on the network architecture and specific device characteristics, but it is usually lower than 10; power consumption and latency are largely modeled and analyzed and are strictly dependent on a huge number of parameters. Most of these characteristics are based on analytical models, but there is a need for rigorous experimental evaluations to understand the actual limits.

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  • BLE can be a more suitable wireless protocol than ZigBee and low-power Wi-Fi for multi-sensor wearable bioelectric signal acquisition systems.

    “Compared with ZigBee and low-power Wi-Fi, Bluetooth Low Energy (BLE) can be a more suitable wireless protocol for such systems.”

    From Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol (2023) · cites this paper as [17]

    The Introduction describes BLE as a candidate for medical body-area networks, including ECG and EMG applications. Section 3.3 reports a lower average current consumption than ZigBee, supporting one reason BLE might be suitable. The paper does not establish that BLE is more suitable than both ZigBee and low-power Wi-Fi specifically for multi-sensor wearable bioelectric signal acquisition. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • BLE has lower power consumption (~1 mA) and a high transmission speed (2 Mbps) compared with low-power Wi-Fi.

    “Compared with low-power Wi-Fi, BLE has lower power consumption of ~1 mA and a high transmission speed of 2 Mbps [17,18,19].”

    From Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol (2023) · cites this paper as [17]

    Section 2.1.1 identifies 2 Mbps as an optional BLE physical-layer data rate, not its typical application throughput. Section 3.3 describes BLE as low-power but reports current consumption that varies with operating conditions; it does not establish ~1 mA or a comparison specifically with low-power Wi-Fi. No page numbers are available in our copy. (LLM, conf=0.90)

    Experimental — accuracy not yet measured

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References 66 · Cited by 243

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  1. [1]Omre A.H. Keeping S. Bluetooth Low Energy: Wireless Connectivity for Medical Monitoring J. Diabetes Sci. Technol. 2010 4 457 463 20307407 PMC2864182
  2. [2]Fekr A.R. Radecka K. Zilic Z. Design and Evaluation of an Intelligent Remote Tidal Volume Variability Monitoring System in E-Health Applications IEEE J. Biomed. Health Inform. 2015 19 1532 1548 10.1109/JBHI.2015.2445783 26087508 · DOI · Paper page
  3. [3]Fafoutis X. Vafeas A. Janko B. Sherratt R.S. Pope J. Elsts A. Mellios E. Hilton G. Oikonomou G. Piechocki R. Designing Wearable Sensing Platforms for Healthcare in a Residential Environment EAI Endorsed Trans. Pervasive Health Technol. 2017 3 10.4108/eai.7-9-2017.153063 · DOI
  4. [4]Contaldo M. Banerjee B. Ruffieux D. Chabloz J. Roux E.L. Enz C.C. A 2.4-GHz BAW-Based Transceiver for Wireless Body Area Networks IEEE Trans. Biomed. Circuits Syst. 2010 4 391 399 10.1109/TBCAS.2010.2081363 23850756 · DOI
  5. [5]Park Y.J. Cho H.S. Transmission of ECG data with the patch-type ECG sensor system using Bluetooth Low Energy Proceedings of the 2013 International Conference on ICT Convergence (ICTC) Jeju, Korea 14–16 October 2013 289 294
  6. [6]Rachim V.P. Chung W.Y. Wearable Noncontact Armband for Mobile ECG Monitoring System IEEE Trans. Biomed. Circuits Syst. 2016 10 1112 1118 10.1109/TBCAS.2016.2519523 27214910 · DOI
  7. [7]Liu G. Yang H.Y. Design and implementation of a Bluetooth 4.0-based heart rate monitor system on iOS platform Proceedings of the 2013 International Conference on Communications, Circuits and Systems (ICCCAS) Chengdu, China 15–17 November 2013 Volume 2 112 115
  8. [8]Chan A.M. Selvaraj N. Ferdosi N. Narasimhan R. Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Osaka, Japan 3–7 July 2013 6115 6118 24111135
  9. [9]Kuwabara K. Higuchi Y. Ogasawara T. Koizumi H. Haga T. Wearable blood flowmeter appcessory with low-power laser Doppler signal processing for daily-life healthcare monitoring Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Chicago, IL, USA 26–30 August 2014 6274 6277 25571431
  10. [10]Brunelli D. Farella E. Giovanelli D. Milosevic B. Minakov I. Design Considerations for Wireless Acquisition of Multichannel sEMG Signals in Prosthetic Hand Control IEEE Sens. J. 2016 16 8338 8347 10.1109/JSEN.2016.2596712 · DOI
  11. [11]Amaro J.P. Patrão S. Moita F. Roseiro L. Bluetooth low energy profile for MPU9150 IMU data transfers Proceedings of the 2017 IEEE 5th Portuguese Meeting on Bioengineering (ENBENG) Coimbra, Portugal 16–18 February 2017 1 4
  12. [12]Lin J.-R. Talty T. Tonguz O.K. On the potential of bluetooth low energy technology for vehicular applications IEEE Commun. Mag. 2015 53 267 275 10.1109/MCOM.2015.7010544 · DOI
  13. [13]Xia K. Wang H. Wang N. Yu W. Zhou T. Design of automobile intelligence control platform based on Bluetooth low energy Proceedings of the 2016 IEEE Region 10 Conference (TENCON) Singapore 22–25 November 2016 2801 2805
  14. [14]Gentili M. Sannino R. Petracca M. BlueVoice: Voice communications over Bluetooth Low Energy in the Internet of Things scenario Comput. Commun. 2016 89–90 51 59 10.1016/j.comcom.2016.03.004 · DOI
  15. [15]Luan S. Gude D. Prakash P. Warren S. A paraeducator glove for counting disabled-child behaviors that incorporates a Bluetooth Low Energy wireless link to a smart phone Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Chicago, IL, USA 26–30 August 2014 796 799 25570079
  16. [16]Yoon P.K. Zihajehzadeh S. Kang B.S. Park E.J. Adaptive Kalman filter for indoor localization using Bluetooth Low Energy and inertial measurement unit Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Milan, Italy 25–29 August 2015 825 828 26736389
  17. [17]Sherratt R.S. Janko B. Hui T. Harwin W. Diaz-Sanchez D. Dictionary memory based software architecture for distributed Bluetooth Low Energy host controllers enabling high coverage in consumer residential healthcare environments Proceedings of the 2017 IEEE International Conference on Consumer Electronics (ICCE) Las Vegas, NV, USA 8–10 January 2017 406 407
  18. [18]Collotta M. Pau G. A Novel Energy Management Approach for Smart Homes Using Bluetooth Low Energy IEEE J. Sel. Areas Commun. 2015 33 2988 2996 10.1109/JSAC.2015.2481203 · DOI
  19. [19]Collotta M. Pau G. A Solution Based on Bluetooth Low Energy for Smart Home Energy Management Energies 2015 8 11916 11938 10.3390/en81011916 · DOI
  20. [20]Collotta M. Pau G. An Innovative Approach for Forecasting of Energy Requirements to Improve a Smart Home Management System Based on BLE IEEE Trans. Green Commun. Netw. 2017 1 112 120 10.1109/TGCN.2017.2671407 · DOI
  21. [21]Tian J. Liu J. Liang S. Ning Y. Li H. Zhao G. Wireless transmission system for motion sensing game controller based on low power Bluetooth technology Proceedings of the 2016 IEEE 13th International Conference on Signal Processing (ICSP) Chengdu, China 6–10 November 2016 1318 1322
  22. [22]Karani R. Dhote S. Khanduri N. Srinivasan A. Sawant R. Gore G. Joshi J. Implementation and design issues for using Bluetooth low energy in passive keyless entry systems Proceedings of the 2016 IEEE Annual India Conference (INDICON) Bangalore, India 16–18 December 2016 1 6
  23. [23]Koodtalang W. Sangsuwan T. Improving motorcycle anti-theft system with the use of Bluetooth Low Energy 4.0 Proceedings of the 2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Phuket, Thailand 24–27 October 2016 1 5
  24. [24]Basalamah A. Sensing the Crowds Using Bluetooth Low Energy Tags IEEE Access 2016 4 4225 4233 10.1109/ACCESS.2016.2594210 · DOI · Paper page
  25. [25]Alletto S. Cucchiara R. Fiore G.D. Mainetti L. Mighali V. Patrono L. Serra G. An Indoor Location-Aware System for an IoT-Based Smart Museum IEEE Int. Things J. 2016 3 244 253 10.1109/JIOT.2015.2506258 · DOI
  26. [26]Zou H. Jiang H. Luo Y. Zhu J. Lu X. Xie L. BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service Sensors 2016 16 268 10.3390/s16020268 26907295 PMC4801644 · DOI
  27. [27]Lin X.Y. Ho T.W. Fang C.C. Yen Z.S. Yang B.J. Lai F. A mobile indoor positioning system based on iBeacon technology Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Milan, Italy 25–29 August 2015 4970 4973 26737407
  28. [28]Mokhtari G. Zhang Q. Karunanithi M. Modeling of human movement monitoring using Bluetooth Low Energy technology Conf. Proc. IEEE Eng. Med. Biol. Soc. 2015 2015 5066 5069 26737430
  29. [29]Ozer A. John E. Improving the Accuracy of Bluetooth Low Energy Indoor Positioning System Using Kalman Filtering Proceedings of the 2016 International Conference on Computational Science and Computational Intelligence (CSCI) Las Vegas, NV, USA 15–17 December 2016 180 185
  30. [30]Peng Y. Fan W. Dong X. Zhang X. An Iterative Weighted KNN (IW-KNN) Based Indoor Localization Method in Bluetooth Low Energy (BLE) Environment Proceedings of the 2016 International IEEE Conferences on Ubiquitous Intelligence Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld) Toulouse, France 18–21 July 2016 794 800
  31. [31]Viswanathan S. Srinivasan S. Improved path loss prediction model for short range indoor positioning using bluetooth low energy Proceedings of the 2015 IEEE SENSORS Busan, Korea 1–4 November 2015 1 4
  32. [32]Kotanen A. Hannikainen M. Leppakoski H. Hamalainen T.D. Experiments on local positioning with Bluetooth Proceedings of the International Conference on Information Technology: Coding and Computing Las Vegas, NV, USA 28–30 April 2003 297 303
  33. [33]Bae H. Oh J. Lee K. Oh J.H. Low-cost indoor positioning system using BLE (bluetooth low energy) based sensor fusion with constrained extended Kalman Filter Proceedings of the 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO) Qingdao, China 3–7 December 2016 939 945
  34. [34]Lee C.H. Location-Aware Speakers for the Virtual Reality Environments IEEE Access 2017 5 2636 2640 10.1109/ACCESS.2017.2672556 · DOI
  35. [35]Apoorv R. Mathur P. Smart attendance management using Bluetooth Low Energy and Android Proceedings of the 2016 IEEE Region 10 Conference (TENCON) Singapore 22–25 November 2016 1048 1052
  36. [36]Filippoupolitis A. Oliff W. Loukas G. Bluetooth Low Energy Based Occupancy Detection for Emergency Management Proceedings of the 2016 15th International Conference on Ubiquitous Computing and Communications and 2016 International Symposium on Cyberspace and Security (IUCC-CSS) Granada, Spain 14–16 December 2016 31 38
  37. [37]Kumar B.G.A. Bhagyalakshmi K.C. Lavanya K. Gowranga K.H. A Bluetooth low energy based beacon system for smart short range surveillance Proceedings of the 2016 IEEE International Conference on Recent Trends in Electronics, Information Communication Technology (RTEICT) Bangalore, India 20–21 May 2016 1181 1184
  38. [38]Varela P.M. Ohtsuki T.O. Discovering Co-Located Walking Groups of People Using iBeacon Technology IEEE Access 2016 4 6591 6601 10.1109/ACCESS.2016.2615863 · DOI
  39. [39]Palattella M.R. Dohler M. Grieco A. Rizzo G. Torsner J. Engel T. Ladid L. Internet of Things in the 5G Era: Enablers, Architecture, and Business Models IEEE J. Sel. Areas Commun. 2016 34 510 527 10.1109/JSAC.2016.2525418 · DOI · Paper page
  40. [40]Wang H. Xi M. Liu J. Chen C. Transmitting IPv6 packets over Bluetooth low energy based on BlueZ Proceedings of the 2013 15th International Conference on Advanced Communication Technology (ICACT) PyeongChang, Korea 27–30 January 2013 72 77
  41. [42]Raza S. Misra P. He Z. Voigt T. Bluetooth smart: An enabling technology for the Internet of Things Proceedings of the 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) Abu Dhabi, United Arab Emirates 19–21 October 2015 155 162
  42. [43]Tabish R. Mnaouer A.B. Touati F. Ghaleb A.M. A comparative analysis of BLE and 6LoWPAN for U-HealthCare applications Proceedings of the 2013 7th IEEE GCC Conference and Exhibition (GCC) Doha, Qatar 17–20 November 2013 286 291
  43. [47]Marco P.D. Skillermark P. Larmo A. Arvidson P. Chirikov R. Performance Evaluation of the Data Transfer Modes in Bluetooth 5 IEEE Commun. Stand. Mag. 2017 1 92 97 10.1109/MCOMSTD.2017.1700030 · DOI
  44. [49]Heydon K. Architecture Bluetooth Low Energy—The Developer’s Handbook Goodwin B. Prantice Hall-Pearson Education, Inc. Upper Saddle River, NJ, USA 2012 40 51
  45. [54]Heydon K. The Host/Controller Interface Bluetooth Low Energy—The Developer’s Handbook Goodwin B. Prantice Hall- Pearson Education, Inc. Upper Saddle River, NJ, USA 2012 131 163
  46. [55]Heydon K. The Physical Layer Bluetooth Low Energy—The Developer’s Handbook Goodwin B. Prantice Hall-Pearson Education, Inc. Upper Saddle River, NJ, USA 2012 59 69
  47. [56]Heydon K. Basic Concepts Bluetooth Low Energy—The Developer’s Handbook Goodwin B. Prantice Hall-Pearson Education, Inc. Upper Saddle River, NJ, USA 2012 28 39
  48. [60]Tsimbalo E. Fafoutis X. Piechocki R.J. CRC Error Correction in IoT Applications IEEE Trans. Ind. Inform. 2017 13 361 369 10.1109/TII.2016.2605628 · DOI
  49. [61]Harris A.F. III Khanna V. Tuncay G. Want R. Kravets R. Bluetooth Low Energy in Dense IoT Environments IEEE Commun. Mag. 2016 54 30 36 10.1109/MCOM.2016.1600546CM · DOI
  50. [63]León J. Dueñas A. Iano Y. Makluf C.A. Kemper G. A Bluetooth Low Energy mesh network auto-configuring Proactive Source Routing protocol Proceedings of the 2017 IEEE International Conference on Consumer Electronics (ICCE) Las Vegas, NV, USA 8–10 January 2017 348 349
  51. [64]Darroudi S.M. Gomez C. Bluetooth Low Energy Mesh Networks: A Survey Sensors 2017 17 1467 10.3390/s17071467 28640183 PMC5539726 · DOI
  52. [65]Gomez C. Demirkol I. Paradells J. Modeling the Maximum Throughput of Bluetooth Low Energy in an Error-Prone Link IEEE Commun. Lett. 2011 15 1187 1189 10.1109/LCOMM.2011.092011.111314 · DOI
  53. [70]Tei R. Yamazawa H. Shimizu T. BLE power consumption estimation and its applications to smart manufacturing Proceedings of the 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) Hangzhou, China 28–30 July 2015 148 153
  54. [73]Rheinländer C.C. Wehn N. Precise synchronization time stamp generation for Bluetooth low energy Proceedings of the 2016 IEEE SENSORS Orlando, FL, USA 30 October–3 November 2016 1 3
  55. [74]Habbal M. Bluetooth low energy–assessment within a competing wireless world Proceedings of the Wireless Congress 2012-Systems & Applications Munich, Germany 14–15 November 2012
  56. [75]Want R. Schilit B. Laskowski D. Bluetooth LE Finds Its Niche IEEE Pervasive Comput. 2013 12 12 16 10.1109/MPRV.2013.60 · DOI
  57. [76]Liu J. Chen C. Ma Y. Xu Y. Energy Analysis of Device Discovery for Bluetooth Low Energy Proceedings of the 2013 IEEE 78th Vehicular Technology Conference (VTC Fall) Las Vegas, NV, USA 2–5 September 2013 1 5
  58. [78]Jeon W.S. Dwijaksara M.H. Jeong D.G. Performance Analysis of Neighbor Discovery Process in Bluetooth Low-Energy Networks IEEE Trans. Veh. Technol. 2017 66 1865 1871 10.1109/TVT.2016.2558194 · DOI
  59. [79]Liu J. Chen C. Ma Y. Modeling Neighbor Discovery in Bluetooth Low Energy Networks IEEE Commun. Lett. 2012 16 1439 1441 10.1109/LCOMM.2012.073112.120877 · DOI
  60. [80]Kim J. Han K. Backoff scheme for crowded Bluetooth low energy networks IET Commun. 2017 11 548 557 10.1049/iet-com.2016.0462 · DOI
  61. [84]Feng Z. Mo L. Li M. Analysis of low energy consumption wireless sensor with BLE Proceedings of the 2015 IEEE SENSORS Busan, Korea 1–4 November 2015 1 4
  62. [85]Giovanelli D. Milosevic B. Farella E. Bluetooth Low Energy for data streaming: Application-level analysis and recommendation Proceedings of the 2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI) Gallipoli, Italy 18–19 June 2015 216 221
  63. [87]Aguilar S. Vidal R. Gomez C. Opportunistic Sensor Data Collection with Bluetooth Low Energy Sensors 2017 17 159 10.3390/s17010159 28124987 PMC5298732 · DOI
  64. [88]Cho K. Park W. Hong M. Park G. Cho W. Seo J. Han K. Analysis of Latency Performance of Bluetooth Low Energy (BLE) Networks Sensors 2014 15 59 78 10.3390/s150100059 25545266 PMC4327007 · DOI
  65. [89]Cho K. Jung C. Kim J. Yoon Y. Han K. Modeling and analysis of performance based on Bluetooth Low Energy Proceedings of the 2015 7th IEEE Latin-American Conference on Communications (LATINCOM) Arequipa, Peru 4–6 November 2015 1 6
  66. [90]Liu J. Chen C. Ma Y. Modeling and performance analysis of device discovery in Bluetooth Low Energy networks Proceedings of the 2012 IEEE Global Communications Conference (GLOBECOM) Anaheim, CA, USA 3–7 Decemer 2012 1538 1543
  67. [91]Contreras D. Castro M. de la Torre D.S. Performance evaluation of bluetooth low energy in indoor positioning systems Trans. Emerg. Telecommun. Technol. 2017 28 10.1002/ett.2864 · DOI
  68. [92]Kajikawa N. Minami Y. Kohno E. Kakuda Y. On Availability and Energy Consumption of the Fast Connection Establishment Method by Using Bluetooth Classic and Bluetooth Low Energy Proceedings of the 2016 Fourth International Symposium on Computing and Networking (CANDAR) Hiroshima, Japan 22–25 November 2016 286 290
  69. [93]Buckley J. Aherne K. O’Flynn B. Barton J. Murphy A. O’Mathuna C. Antenna performance measurements using wireless sensor networks Proceedings of the 56th Electronic Components and Technology Conference 2006 San Diego, CA, USA 30 May–2 June 2006 6

Authors
Tosi, J., Taffoni, F., Santacatterina, M., Sannino, R., & Formica, D.
Affiliations
  • Università Campus Bio-Medico (IT)
  • STMicroelectronics (Italy) (IT)
Corresponding author
Tosi, Jacopo
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2017-12-13
Volume
17
Issue
12
Pages
2898
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s17122898
PMC
PMC5751532
OpenAlex
W2773526096
Cited by
243
References
66
Citations by year
2026: 22 · 2025: 48 · 2024: 35 · 2023: 34 · 2022: 30 · 2021: 25 · 2020: 29 · 2019: 14 · 2018: 6
FWCI
13.97
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Bluetooth and Wireless Communication Technologies
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
Keywords
Bluetooth Low Energy, wireless sensor networks, embedded sensors, throughput, power consumption, latency, network range, wireless communication protocols, wearable devices, e-health, home automation

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