This document discusses space awareness technologies for mobile computing service discovery. It begins with an overview of space awareness and then discusses alternative non-RF sensing technologies like light, sound, pedestrian dead reckoning using IMUs, and assistive technologies using magnetic fields and heat. It then covers various RF-related technologies for space awareness including WiFi, RFID, Bluetooth, UWB, and mmWave. Specific techniques are discussed for each such as WiFi RTT, fingerprinting, and UWB FMCW localization. The document analyzes the accuracy, range, energy efficiency, and compatibility of different approaches. It concludes that while laser-based solutions offer best accuracy, WiFi remains the most approachable solution currently and that UWB has good

1. Space Awareness Technologies for
Service Discovery in Mobile Computing
Yurong (Kevin) Xu

2. 1.Overview of Space Awareness
2. Space Awareness Technologies in Alternative(Non-RF) Sensing
Capabilities:
a. Light (Laser-based)
b. Sound (Ultrasound-based)
c. PDR (IMU-based Pedestrian Dead Reckoning)
d. (Assistive) Magnetic Field
e. (Assistive) Heat
3. RF-related Space Awareness Technologies:
• Wifi/RFID/Bluetooth/UWB/mmWave based Space Awareness
Technologies

3. 2. Non-RF Space Awareness-Light
• Light Laser sensor:
ToF-based method:
• Infrared or Visible light-based,
• Accuracy: in cm range
• Range: up to 400cm
• Reaction time: in us range
Challenges:
• Emitter time synchronization
• Sunlight interference
• Existing NLOS problem
pulsed
continuous-wave
Do, T.H.; Yoo, M. An in-Depth Survey of Visible Light Communication Based Positioning Systems. Sensors 2016, 16, 678.

4. 2. Non-RF Space Awareness-Sound
• Ultrasonic sensor:
ToF-based:
• Accuracy: in 10 cm range
• Range: up to 400cm
• Reaction time: in ms range
Challenges:
• Sound speed is affected by
temperature and humidity
• Interference of bouncing
pulses
• Existing NLOS problem.
Velocity detection
Distance detection
https://radiologykey.com/physical-principles-of-doppler-ultrasound/

5. 2. PDR (IMU-based PDR) in Space Awareness
• PDR in space awareness
PDR in smart phone or device,
and need to be hold by hand or in
particular body position:
• Pros: only 9axis IMU needed,
• Cons: requires initialization
• Accuracy: about 2.5m in research
• Reaction time: in 100 ms range

6. 2. Assistive technologies for Space Awareness
- Magnetic field
• Magnetic proximity Position (IndoorAtlas
(acquired by Baidu)):
• Based on earth
• Magnetic field,
• Accuracy: low
• Reaction time: ms
Challenges:
• Need fingerprint DB
before distance
estimation.
Assistive technology, didn’t measure distance directly, usually
combines with other space awareness technologies
Step 2: Mapping buildings
Step 3: match magnetic field for
localization
Step 1: Adding floor plans

7. 2. Assistive technologies for Space Awareness - Heat
• Heat proximity sensor (PIR sensor)
• Accuracy: low
• Range: up to 10m
• Measurement: thermal
radiation variability
• Could be a supplemental
method for space awareness
Challenge:
• Sensitive to sunlight,
• Not good for distance measurement.
An example of gesture detection with PIR sensor
Sensitive to thermal radiation variability upon body movements
J Gong, Y Zhang, X Zhou, XD Yang, Pyro: Thumb-tip gesture recognition using pyroelectric infrared sensing, UIST, 2017.

8. 3.1 Wi-Fi-based Localization
• Frequency spectrum of Wifi: between 2Ghz-5Ghz
• Wifi-based methods usually rely on AP (either single AP or multiple APs)
• Measurement range for Wifi-based methods: from 50m-100m
• Methods covered here:
1. RTT-based Wifi Localization
2. Cell of Origin (CoO)-based Wifi Localization
3. Fingerprint-based Wifi Localization

9. 3.1 Wi-Fi-based Localization
• Wifi RTT (Round Trip Time)
• Adopted by Wifi 802.11mc Standard,
core idea is based on RTT
• Accuracy: 2-5m
• Range: up to 100m
• Reaction time: ms
• no NLOS
• Supported by Android 9.0&up
G Guo, R Chen, F Ye, X Peng, Z Liu, Y Pan, Indoor Smartphone Localization: A Hybrid WiFi RTT-RSS Ranging Approach, IEEE Access, 2019.

10. 3.1 Wi-Fi-based Localization
• Cell of origin (CoO) Wifi localization
• Mostly used for WAN (such as AT&T Wi-Fi networks)
pick the location of a AP with RSSI threshold,
Accuracy: 50m
Range: a couple of km
Reaction time: ms
1. Ideal coverage of APs
2. Voronoi diagram (VD) is created
to calculate Handover Point (HOP)3. Handover Point (HOP) calculation to get RSSI threshold

11. 3.1 Wi-Fi-based Localization
• Fingerprint-based Wifi localization
• Compatible with Wifi 802.11 standard (Google
has the biggest commercial Wifi fingerprint DB)
Fingerprint tuple: (RSSI, AP)
• Accuracy: 1-5m
• Range: up to 100m
• Reaction time: ms
• minial NLOS problem
• need offline calibration
Intro
Step 1: generate offline fingerprint dB
Step 2: sense RSSI fingerprint from APs
Step3: compare with FP DB to get location estimation
R. Chen, L. Pei, and J. Liu. Using inquiry-based Bluetooth RSSI probability distributions for indoor positioning. JGPS 9, 2 (2010), 122–130.

12. 3.2 Passive RFID localization:
• Passive RFID localization
Passive RFID or Battery-less!
RF band: LF(134khz), HF(13.5Mhz), UHF(868Mhz)
Method: Communication boundary angle/range;
• Accuracy: 10-30cm
• Range: up to 2m
• Reaction time: ms
• Distance sensing is based MIMO
antenna scanning.
RFID is the only PASSIVE method: anchor node(RFID tag) need no power
Step 1: adjust reader power to sense
range,
Step 2: switch MIMO antenna in
reader to measure angle.

13. 3.2 Assistive technologies -- BT(iBeacon) Localization:
• BT localization relies on iBeacon
• iBeacon (Apple) and BT solutions
• based on iBeacon (anchor) hardware,
• RSSI + IMU are contributed
• Accuracy: 1-5m
• Range: up to 100m
• Reaction time: ms
BT localization relies on pre-deployed anchors(iBeacon)

14. 3.2 Bluetooth Fingerprint-based Localization:
• Bluetooth fingerprint localization relies on
Bluetooth Access Point as infrastructure
• Training data is a must before location estimation
• Accuracy: about 1-2m
• Range: up to 100m
• Reaction time: ms
R. Chen, L. Pei, and J. Liu. Using inquiry-based Bluetooth RSSI probability distributions for indoor positioning. JGPS 9, 2 (2010), 122–130.
Experiment result
System architecture
Two phase deployment

15. 3.3 UWB-based Localization
• Frequency spectrum of UWB: between 3.1Ghz-10Ghz, 60-80Ghz
• Measurement range for UWB-based methods: from 50m-100m
• Benefits: Higher frequency contributes to more accurate measurement
• Methods covered here:
1. UWB Anchors
2. UWB Fingerprinting
3. UWB FMCW (Frequency Modulated Continuous Wave)

16. 3.3 UWB-based Localization
• UWB Anchor-based Localization (
Decowave)
ToA based virtual anchor technology:
• Need accurate time synchronization;
• Accuracy: 10cm-1m
• Range: 50-100m
• Reaction time: ms
UWB translates larger bandwidth into higher resolution in localization
Step 1: Receiver listens to multiple
paths with reflected signals
Step 2: time synchronization separates
multiple paths as virtual anchors
Step 3: point-in-triangulation calculation
Decowave, Ultra Wideband Wireless Positioning Systems, white paper, 2014

17. 3.3 UWB-based Localization
• UWB Fingerprint-based Localization (by Kröll and Steiner’research)
CIR( Channel Impulse Response)based fingerprint
• Accuracy: up to 2cm
• Range: 50-100m:
• Reaction time: ms
• Need to create fingerprint DB in adv.
Here, CIR as h(t),
UWB Fingerprint localization is to march fingerprint (CIR) assigned with location
Harald Kröll ; Christoph Steiner, Indoor ultra-wideband location fingerprinting, IPIN, 2010.

18. 3.3 UWB-based Localization
• UWB FMCW-based Localization (by TI etc… )
FMCW (Frequency-Modulated Continuous-Wave) -based:
• Accuracy: up to 10cm
• Range: 50-100m
• Reaction time: ms
• tracks both distance & velocity
for multiple objects
simultaneously.
.
The fundamentals of millimeter wave, Texas Instruments, 2016.

19. 3.3 UWB-based Localization
• UWB FMCW-based Localization (by TI etc… )
FMCW (Frequency-Modulated Continuous-Wave) -based:
How to track 1. distance, 2.multiple objects, 3. velocity:
Texas Instruments, The fundamentals of millimeter wave, White book 2016.

20. 3.3 UWB-based Localization
• UWB FMCW-based Localization (by TI etc… )
FMCW (Frequency-modulated continuous-wave) -based:
How to track 2.multiple objects, 3. velocity:
two objects in same
distance, but both with
different displacements
This is the phase difference
between C and F
Small displacements in the
objects leads to phase difference

21. Which are the Hottest in the Space Awareness Research
• Word cloud for cited research papers for space awareness
21
Top research words:
WiFi
Light
PDR
UWB
Magnetic
Sound
RFID
Vision
The above research key words
represents HOT research
directions for space awareness
and should be paid attention to
for potential breakthroughs.
GM Mendoza-Silva, J Torres-Sospedra, J Huerta, A meta-review of indoor positioning systems, Sensors, 2019.

22. 4. Usage for Spatial Awareness Projects
• Laser-base solution is the best in
accuracy, but not fit for general smart
device spatial topology measurement:
NLOP problem and additional hardware
component.
• RF-based solution, especial Wifi-base
solution, is the most approachable
solution in current solution:
Commercial availability and flexibility to
extend.
22

23. Wifi RFID BT UWB
Accuracy 1-5m 1m 1-5m 10cm-1m
Energy
efficiency
0.1w-1w 0.1w-1w 1mw-0.1w 1mw-0.1w
Scalability wide
support on
device/AP
limited
support in
device/AP
limited
support in
AP
limited
support in
device/AP
Compatible
with 5G
No. No. No. similar
frequency
range
4. Usage for Spatial Awareness Projects
• Potential: With the increasing
popularity of 5G
deployment, UWB/mmWave
offers better potential
for spatial awareness application
• UWB use similar range of
frequency spectrum with 5G.
• UWB is more accurate and energy
efficient than Wifi/RFID/BT
• Cost will come down when mass
deployment of 5G devices
23
5G: [3.3, 4.2]GHz, [25,100) Ghz licensed bands
UWB:[3.1, 10.6] GHz [24,100) Ghz unlicensed bands
So, UWB shares similar frequency spectrum with 5G.

24. 24
Thank You