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Mobility-based Time References for Wireless Sensor Networks pp 7–37Cite as

Fully Integrated Radios for Wireless Sensor Networks

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Part of the book series: Analog Circuits and Signal Processing ((ACSP))

Abstract

In the future, technology will be hidden in the environment and invisible to the user but, at the same time, responsive and adaptive to user interaction and environmental variations [1]. For example, smart buildings will become aware of the presence of people and of their needs: thanks to this, temperature and light conditions will be adapted automatically for the best comfort and optimal power consumption. The realization of such a vision requires a technology that can sense, process and respond to external stimuli, both human and environmental, coming from many spots of a large environment, such as a room, a house or a whole building. An answer to such needs may come from Wireless Sensor Networks (WSNs. These are networks that consist of a large number of energy-autonomous nodes deployed into the environment to collect physical data. Each node is equipped with sensors, digital and analog processing units and a radio transceiver [2]. Physical parameters, such as temperature, sound, light conditions, etc., are sensed and processed by each node. The resulting information is transmitted from node to node and propagates through the network, until it is collected by a central data sink or used by the network itself in distributed algorithms. Dense networks, composed of hundreds or thousands of devices, are required to accurately monitor an environment. Consequently, each node must be extremely cheap to limit the cost of the network and make this technology economically feasible. Moreover, the nodes must be small enough to be hidden, in order to be invisible to users and not affect the surrounding environment.

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Notes

  1. 1.

    Depending on the frequency of operation and the required performance, antennas can also be integrated on silicon [11].

  2. 2.

    In the following, the expressions “time reference” and “frequency reference” are interchangeable.

  3. 3.

    Equation (2.1) gives a sufficient condition for enabling communication among all nodes. However, nodes whose timeslots occur shortly after a synchronization beacon can, in principle, have a shorter T wu and consequently a lower power consumption. This case is not analyzed in this work. In the following it is implicitly assumed that T wu is the same for all nodes.

  4. 4.

    For more details on synchronization, see Sect. 2.4.3.

  5. 5.

    Equation (2.9) is not mathematically rigorous; it has been developed considering that n fa is the product of the number of decisions to be taken in a timeslot by ℙ fa and that the number of decisions depends on the difference between the duration of the timeslots and the time used for reception of the preamble caused by false alarms, i.e. \({\mathit{n}}_{fa} = {\mathbb{P}}_{fa}\frac{{T}_{wu}-{\mathit{n}}_{fa}{N}_{\mathit{p}r}/DR} {{T}_{d}}\).

  6. 6.

    The repetition code is a coding scheme in which each data bit is transmitted multiple times over the channel.

  7. 7.

    The power of the transmitted signal is limited by the peak power provided by the energy source and the power management system and the expected efficiency of the transmitter. Note that the spectral mask requirements are still met if less power than 1 mW is emitted and the assumed value is a practical upper bound.

  8. 8.

    Transmitting a signal with higher peak power requires a transmitting chain and, in particular, a power amplifier with higher linearity. Since linearity and power efficiency of a transmitter are contrasting requirements [35], a modulation requiring a lower P peak and consequently a lower CF is preferred.

  9. 9.

    The number of bits in the preamble is chosen large enough to ease the implementation of the synchronization algorithm. At the same time, the choice N pr  = 100 does not affect sensibly the total power consumption (see Sect. 2.3.5).

  10. 10.

    Note that in the following we compute the detected energy of only one sampling, but in case of PPM two samplings per frame are needed. The adopted simplification is possible thanks to the equivalence in terms of energy and BER performance of PPM and OOK.

  11. 11.

    The factor 2 derives from the presence of frequency errors both in transmitter and receiver.

  12. 12.

    Though the analysis was carried on with an AWGN channel, it must be noted that a margin for fading and obstruction has been considered in Sect. 2.4.2. Propagation through a multipath channel only affects the energy received for each pulse, since the delay between successive pulses is much higher than multipath delay expected by typical channel models. The effect of interferers is treated in the next section.

  13. 13.

    Each packet has a duration of 366 μs and the delay between the first and second packet in the burst is 625 μs.

  14. 14.

    The period is adapted to the QoS required for the audio link.

References

  1. Weber W, Rabaey JM, Aarts E (eds) (2005) Ambient intelligence. Springer, New York

    Google Scholar 

  2. Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114. DOI 10.1109/MC.2002.1024422

    Article  Google Scholar 

  3. Chong CY, Kumar SP (2003) Sensor networks: evolution, opportunities and challenges. Proc IEEE 91(8):1247–1256

    Article  Google Scholar 

  4. EnOcean GmbH (2008) STM110 datasheet, Oberhaching, Germany, Sept. 2008. http://www.enocean.com. Accessed 4 Aug 2009

  5. Crossbow Technology, Inc. (2009) XM2110CA datasheet, San Jose, CA. http://www.xbow.com. Accessed 4 Aug 2009

  6. Dust Networks, Inc. (2009) M2600 datasheet, Hayward, CA. http://www.dustnetworks.com. Accessed 4 Aug 2009

  7. Romer K, Mattern F (2004) The design space of wireless sensor networks. IEEE Wireless Comm 11(6):54–61. DOI 10.1109/MWC.2004.1368897

    Article  Google Scholar 

  8. Weber W, Braun C, Dienstuhl J, Glaser R, Gsottberger Y, Knoll B, Lauterbach C, Leitner D, Shi M, Schnell M, Savio D, Stromberg G, Verbeck M (2005) Disappearing electronics and the return of the physical world. In: Symp. VLSI Circuits Dig. Tech. Papers, pp 45–48. DOI 10.1109/VTSA.2005.1497076

    Google Scholar 

  9. Warneke B, Last M, Liebowitz B, Pister K (2001) Smart dust: communicating with a cubic-millimeter computer. Computer 34(1):44–51. DOI 10.1109/2.895117

    Article  Google Scholar 

  10. Rabaey J, Ammer M, da Silva J JL, Patel D, Roundy S (2000) Picoradio supports ad hoc ultra-low power wireless networking. Computer 33(7):42–48. DOI 10.1109/2. 869369

    Article  Google Scholar 

  11. O KK, Kim K, Floyd BA, Mehta JL, Yoon H, Hung C-M, Bravo D, Dickson TO, Guo X, Li R, Trichy N, Caserta J, Bomstad WR II, Branch J, Yang D-J, Bohorquez J, Seok E, Gao L, Sugavanam A, Lin J-J, Chen J, Brewer JE (2005) On-chip antennas in silicon ICs and their application. IEEE Trans Electron Dev 52(7):1312–1323. DOI 10.1109/TED.2005.850668

    Google Scholar 

  12. Bryzek J, Roundy S, Bircumshaw B, Chung C, Castellino K, Stetter J, Vestel M (2006) Marvelous MEMS. IEEE Circ Dev Mag 22(2):8–28

    Article  Google Scholar 

  13. Frank M, Kuhl M, Erdler G, Freund I, Manoli Y, Mller C, Reinecke H (2009) An integrated power supply system for low-power 3.3V electronics using on-chip polymer electrolyte membrane (PEM) fuel cells. In: ISSCC Dig. Tech. Papers, vol 1, pp 292–293

    Google Scholar 

  14. Al-Karaki J, Kamal A (2004) Routing techniques in wireless sensor networks: a survey. IEEE Wireless Comm 11(6):6–28. DOI 10.1109/MWC.2004.1368893

    Article  Google Scholar 

  15. Epson Toyocom Corporation (2009) FC-12M datasheet, Tokyo, Japan. http://www.epsontoyocom.co.jp. Accessed 23 Aug 2009

  16. SiTime Corporation (2009) SiT8003XT datasheet, Sunnyvale, CA. http://www.sitime.com. Accessed 23 Aug 2009

  17. Discera Inc. (2009) DSC1018 datasheet, San Jose, CA. http://www.discera.com. Accessed 23 Aug 2009

  18. Daly DC, Chandrakasan AP (2007) An energy-efficient OOK transceiver for wireless sensor networks. IEEE J Solid State Circ (5):1003–1011

    Article  Google Scholar 

  19. Pletcher N, Gambini S, Rabaey J (2007) A 65μW, 1.9 GHz RF to digital baseband wakeup receiver for wireless sensor nodes. CICC Dig. Tech. Papers, pp 539–542

    Google Scholar 

  20. Le T, Mayaram K, Fiez T (2008) Efficient far-field radio frequency energy harvesting for passively powered sensor networks. IEEE J Solid State Circ 43(5):1287–1302. DOI 10.1109/JSSC.2008.920318

    Article  Google Scholar 

  21. Yoo J, Yan L, Lee S, Kim Y, Kim H, Kim B, Yoo HJ (2009) A 5.2mW self-configured wearable body sensor network controller and a 12μW 54.9% efficiency wirelessly powered sensor for continuous health monitoring system. In: ISSCC Dig. Tech. Papers, pp 290–291

    Google Scholar 

  22. O’Driscoll S, Poon A, Meng T (2009) A mm-sized implantable power receiver with adaptive link compensation. In: ISSCC Dig. Tech. Papers, pp 294–295

    Google Scholar 

  23. Roundy S, Strasser M, Wright PK (2005) Powering ambient intelligent networks. In: Weber W, Rabaey JM, Aarts E (eds) Ambient intelligence. Springer, New York

    Google Scholar 

  24. Paradiso J, Starner T (2005) Energy scavenging for mobile and wireless electronics. IEEE Pervasive Comput 4(1):18–27. DOI 10.1109/MPRV.2005.9

    Article  Google Scholar 

  25. Chalasani S, Conrad J (2008) A survey of energy harvesting sources for embedded systems. IEEE Southeastcon pp 442–447. DOI 10.1109/SECON.2008.4494336

    Google Scholar 

  26. Cook BW, Lanzisera S, Pister KSJ (2006) SoC issues for RF smart dust. Proc IEEE 94(6):1177–1196

    Article  Google Scholar 

  27. Ammer J, Burghardt F, Lin E, Otis B, Shah R, Sheets M, Rabaey JM (2005) Ultra low-power integrated wireless nodes for sensor and actuator networks. In: Weber W, Rabaey JM, Aarts E (eds) Ambient intelligence. Springer, New York

    Google Scholar 

  28. Rabaey JM, Ammer J, Karalar T, Suetfei L, Otis B, Sheets M, Tuan T (2002) PicoRadios for wireless sensor networks: the next challenge in ultra-low power design. In: ISSCC Dig. Tech. Papers, vol 1, pp 200–201

    Google Scholar 

  29. Enz CC, El-Hoiydi A, Decotignie JD, Peiris V (2004) Wisenet: an ultralow-power wireless sensor network solution. Computer, 37(8)

    Google Scholar 

  30. Pletcher N, Gambini S, Rabaey J (2009) A 52 μW wake-up receiver with -72 dBm sensitivity using an uncertain-IF architecture. IEEE J Solid State Circ 44(1):269–280. DOI 10.1109/JSSC.2008.2007438

    Article  Google Scholar 

  31. Drago S, Sebastiano F, Breems L, Leenaerts D, Makinwa K, Nauta B (2009) Impulse-based scheme for crystal-less ULP radios. IEEE Trans Circ Syst I 56(5):1041–1052

    Article  MathSciNet  Google Scholar 

  32. Enz CC, Scolari N, Yodprasit U (2005) Ultra low-power radio design for wireless sensor networks. In: Proc. 2005 IEEE International Workshop on Radio-Frequency Integration Technology, pp 1–17

    Google Scholar 

  33. van Dam T, Langendoen K (2003) An adaptive energy-efficient MAC protocol for wireless sensor networks. In: Proc. First ACM Conference on Embedded Networked Sensor Systems (SenSys), pp 171–180

    Google Scholar 

  34. Ryckaert J, Desset C, Fort A, Badaroglu M, De Heyn V, Wambacq P, Van der Plas G, Donnay S, Van Poucke B, Gyselinckx B (2005) Ultra-wide-band transmitter for low-power wireless body area networks: design and evaluation. IEEE Trans Circ Syst I 52(12):2515–2525. DOI 10.1109/TCSI.2005.858187

    Article  Google Scholar 

  35. Lee TH (2004) The design of CMOS radio-frequency integrated circuits, 2nd edn. Cambridge University Press, Cambridge

    Google Scholar 

  36. Hashemi H (1993) The indoor radio propagation channel. Proc IEEE 81(7):943–968. DOI 10.1109/5.231342

    Article  Google Scholar 

  37. Couch LW II (1992) Digital and analog communication systems. Prentice Hall, NJ

    Google Scholar 

  38. Cook BW, Berny A, Molnar A, S L, Pister KSJ (2006a) Low-power 2.4-GHz transceiver with passive RX front-end and 400-mV supply. IEEE J Solid State Circ 41(12):2757–2766. DOI 10.1109/JSSC.2006.884801

    Google Scholar 

  39. Razavi B (1998) RF microelectronics. Prentice-Hall, NJ

    Google Scholar 

  40. Bluetooth Special Interest Group (2007) Specifications of the bluetooth system, Rev. 2.1, July 2007

    Google Scholar 

  41. Drago S, Leenaerts DMW, Sebastiano F, Breems LJ, Makinwa K, Nauta B (2010) A 2.4GHz 830pJ/bit duty-cycled wake-up receiver with − 82dBm sensitivity for crystal-less wireless sensor nodes. In: ISSCC Dig. Tech. Papers, pp 224–225

    Google Scholar 

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Authors and Affiliations

  1. NXP Semiconductors, High Tech Campus 32, Eindhoven, Netherlands

    Fabio Sebastiano & Lucien J. Breems

  2. Delft University of Technology, Mekelweg 4, Delft, Netherlands

    Kofi A. A. Makinwa

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  1. Fabio Sebastiano
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  2. Lucien J. Breems
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  3. Kofi A. A. Makinwa
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Sebastiano, F., Breems, L.J., Makinwa, K.A.A. (2013). Fully Integrated Radios for Wireless Sensor Networks. In: Mobility-based Time References for Wireless Sensor Networks. Analog Circuits and Signal Processing. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3483-2_2

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