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Wireless Signals and Signal Processing

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Wireless Sensing

Part of the book series: Wireless Networks ((WN))

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Abstract

This chapter outlines the wireless signals and signal processing methods used for wireless sensing. We first introduces the preliminary knowledge about how wireless signals are generated and received for sensing. Then, we show different kinds of wireless signals and their characteristics in sensing. Finally, we demonstrate the signal processing methods to deal with the noises and constraints in wireless signals and devices.

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Notes

  1. 1.

    σ = 1∕(2πB−10dB(log10e)2).

  2. 2.

    The single tone signal can be expressed as cos(2πft + ϕ).

  3. 3.

    In Sect. 4.2.1.1, we will explain why the signal amplitude does not perform robustly in distance estimation.

  4. 4.

    AOA estimation will be discussed in detail in Sect. 4.2.1.2.

  5. 5.

    We will discuss in detail about device-free sensing in Sect. 3.2.

  6. 6.

    LNA is widely used in RF receivers. It amplifies a very low-power signal without degrading the signal-to-noise ratio.

  7. 7.

    For RF systems, the number of transmitting and receiving antennas is a key consideration. Existing wireless communication systems are equipped with multiple Tx and Rx antennas to improve the throughput.

  8. 8.

    We will introduce details for AOA estimation in Sect. 4.2.1.2.

  9. 9.

    We use the IQ plane to model the effect of static and dynamic signals. Please refer to Sect. 4.2 for more details about signal modeling in the IQ plane.

  10. 10.

    The spreading factors are SF7, SF8, SF9, SF10, SF11, and SF12.

  11. 11.

    When performing FFT on a signal, the frequency resolution in the FFT result is decided by the time span of the signal. Similarly, for IFFT, the temporal resolution is determined by the bandwidth.

  12. 12.

    The 18–22 KHz frequency range is the commonly used frequency band in acoustic sensing using commodity speakers and microphones because the sound in this range is inaudible to people and cause less disturbance.

  13. 13.

    Coherence time is the time duration during which the channel impulse response does not change.

References

  1. Molisch AF (2012) Wireless communications, vol 34. John Wiley & Sons

    Google Scholar 

  2. Wang W et al (2016) Device-free gesture tracking using acoustic signals. In: Proceedings of the 22nd annual international conference on mobile computing and networking, pp 82–94

    Google Scholar 

  3. Wang Y et al (2020) Push the limit of acoustic gesture recognition. IEEE Trans Mob Comput 21(5):1798–1811

    Article  Google Scholar 

  4. Zheng T et al (2020) V2iFi: in-vehicle vital sign monitoring via compact rf sensing. Proc ACM Interactive Mob Wearable Ubiquitous Technol 4(2):1–27

    Article  Google Scholar 

  5. Cheng H, Lou W (2021) Push the limit of device-free acoustic sensing on commercial mobile devices. In: Proceedings of IEEE conference on computer communications, pp 1–10

    Google Scholar 

  6. Zepernick HJ, Adolf F (2013) Pseudo random signal processing: theory and application. John Wiley & Sons

    Google Scholar 

  7. Haim A (2010) Basics of biomedical ultrasound for engineers. John Wiley & Sons

    Google Scholar 

  8. Cai C et al (2020) AcuTe: acoustic thermometer empowered by a single smartphone. In: Proceedings of the 18th conference on embedded networked sensor systems, pp 28–41

    Google Scholar 

  9. Finkenzeller K (2010) RFID handbook: fundamentals and applications in contactless smart cards, radio frequency identification and near-field communication. John Wiley & Sons

    Book  Google Scholar 

  10. Wang H et al (2016) Human respiration detection with commodity wifi devices: do user location and body orientation matter? In: Proceedings of the ACM international joint conference on pervasive and ubiquitous computing, pp 25–36

    Google Scholar 

  11. Zhang F et al (2018) From fresnel diffraction model to fine-grained human respiration sensing with commodity wi-fi devices. Proc ACM Interactive Mob Wearable Ubiquitous Technol 2(1):1–23

    Google Scholar 

  12. Yang Z et al (2013) From RSSI to CSI: Indoor localization via channel response. ACM Comput Surv 46(2):1–32

    Article  Google Scholar 

  13. Zhang F et al (2020) Exploring lora for long-range through-wall sensing. Proc ACM Interactive Mob Wearable Ubiquitous Technol 4(2):1–27

    Google Scholar 

  14. Zhang F et al (2021) Unlocking the beamforming potential of LoRa for long-range multi-target respiration sensing. Proc ACM Interactive Mob Wearable Ubiquitous Technol 5(2):1–25

    Google Scholar 

  15. Xie B et al (2021) Pushing the limits of long range wireless sensing with LoRa. Proc ACM Interactive Mob Wearable Ubiquitous Technol 5(3):1–21

    Article  Google Scholar 

  16. Wang S et al (2020) Demystifying millimeter-wave V2X: Towards robust and efficient directional connectivity under high mobility. In: Proceedings of the 26th annual international conference on mobile computing and networking

    Google Scholar 

  17. Ha U et al (2020) Contactless seismocardiography via deep learning radars. In: Proceedings of the 26th annual international conference on mobile computing and networking, pp 1–14

    Google Scholar 

  18. Li T et al (2015) Human sensing using visible light communication. Proceedings of the 21st annual international conference on mobile computing and networking, pp 331–344

    Google Scholar 

  19. Ma D et al (2019) Solargest: Ubiquitous and battery-free gesture recognition using solar cells. In: The 25th annual international conference on mobile computing and networking, pp 1–15

    Google Scholar 

  20. Zhou Y et al (2017) Perceiving accurate CSI phases with commodity WiFi devices. In: IEEE conference on computer communications, pp 1–9

    Google Scholar 

  21. Zhuo Y et al (2017) Perceiving accurate CSI phases with commodity WiFi devices. In: IEEE conference on computer communications, pp 1–9

    Google Scholar 

  22. Yang Y et al (2018) Wi-count: Passing people counting with COTS WiFi devices. In: 27th International conference on computer communication and networks, pp 1–9

    Google Scholar 

  23. Wang X et al (2017) PhaseBeat: Exploiting CSI phase data for vital sign monitoring with commodity WiFi devices. In: IEEE 37th international conference on distributed computing systems, pp 1230–1239

    Google Scholar 

  24. Wang G et al (2021) Dynamic phase calibration method for CSI-based indoor positioning. In: IEEE 11th annual computing and communication workshop and conference, pp 0108–0113

    Google Scholar 

  25. Foley JT et al (2017) Low-cost antenna positioning system designed with axiomatic design. In MATEC web of conferences, vol 127. EDP Sciences, p 01015

    Google Scholar 

  26. Ivo Mateljan. Making gated-impulse frequency measurements using ARTA. http://marjan.fesb.hr/~mateljan/

  27. Mao W et al (2017) Indoor follow me drone. In: Proceedings of the 15th annual international conference on mobile systems, applications, and services, pp 345–358

    Google Scholar 

  28. Shahi SN et al (2008) High resolution DOA estimation in fully coherent environments. Prog Electromagn Res C 5:135–148

    Google Scholar 

  29. Li X et al (2016) Dynamic-music: accurate device-free indoor localization. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing, pp 196–207

    Google Scholar 

  30. Qian K et al (2017) Enabling phased array signal processing for mobile WiFi devices. IEEE Trans Mob Comput 17(8):1820–1833

    Article  Google Scholar 

  31. Kumar S et al (2014) Accurate indoor localization with zero start-up cost. In: Proceedings of the 20th annual international conference on mobile computing and networking, pp 483–494

    Google Scholar 

  32. Adib F, Katabi D (2013) See through walls with WiFi! In: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM, pp 75–86

    Google Scholar 

  33. Kotaru M et al (2015) Spotfi: Decimeter level localization using wifi. In: Proceedings of the ACM conference on special interest group on data communication, pp 269–282

    Google Scholar 

  34. Zhang F et al (2020) Exploring LoRa for long-range through-wall sensing. Proc ACM Interactive Mob Wearable Ubiquitous Technol 4(2):1–27

    Google Scholar 

  35. Zhang F et al (2021) Unlocking the beamforming potential of LoRa for long-range multi-target respiration sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5(2):1–25

    Google Scholar 

  36. Tan S et al (2019) MultiTrack: Multi-user tracking and activity recognition using commodity WiFi. In: Proceedings of the 2019 CHI conference on human factors in computing systems, pp 1–12

    Google Scholar 

  37. Xie Y et al (2018) Precise power delay profiling with commodity Wi-Fi. IEEE Trans Mob Comput 18(6):1342–1355

    Article  Google Scholar 

  38. Cai C et al (2021) Active acoustic sensing for hearing temperature under acoustic interference. IEEE Trans Mob Comput. Early Access

    Google Scholar 

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Cao, J., Yang, Y. (2022). Wireless Signals and Signal Processing. In: Wireless Sensing. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-08345-7_2

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  • DOI: https://doi.org/10.1007/978-3-031-08345-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08344-0

  • Online ISBN: 978-3-031-08345-7

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