## 3 Related Work
The only scenario that could work is when a phone generates an RF signal that is received at control points with such antennas. There are two positioning systems of note that utilize AoA with Bluetooth and achieve good accuracy. [PERSON] _et al._ showed that a Bluetooth beacon can be located with one to two meters of accuracy [6]. Positioning with 20 cm accuracy was demonstrated by Nokia High Accuracy Indoor Positioning (HAIP), usingBluetooth 4.0 [7]. Unfortunately Bluetooth 4 is currently not found on most smartphones. It is also unclear if and when this technology will be available on smartphones not manufactured by Nokia. Indoor positioning using GSM has some significant limitations. Existing base stations (GSM towers) are spaced far apart and the introduction of new base stations cannot be done independently of a carrier. Five meter accuracy, one of the best results for indoor GSM positioning, was displayed by [PERSON] _et al._ with the help of wide signal-strength fingerprinting [8]. Unfortunately wide signal-strength fingerprinting is impossible on many modern phones due to OS restrictions. Other GSM positioning methods are generally impractical for indoor use due to poor accuracy. Wi-Fi positioning is at least twice as accurate as GSM. It has been thoroughly researched and even implemented by a few companies on a commercial basis. With Google gradually expanding navigation indoors for Google Maps, which comes preinstalled on all Android devices, Wi-Fi fingerprinting is likely to become a _de facto_ standard for mobile indoor positioning [9]. Bluetooth has the shortest range among the three wireless technologies. At the same time Bluetooth hardware is significantly cheaper than Wi-Fi hardware, which makes a dense control point grid affordable. Currently, using RSS measurements with Bluetooth is complicated because it is designed to adjust signal strength when signals become too strong or too weak, making any subsequent distance measurements based on signal strength unreliable. Disabling this feedback loop is discussed by [PERSON] _et al._[10]. An alternative approach is to measure RSS during the inquiry phase, which utilizes static transmission power but results in a lower update rate [11]. Bluetooth AoA however has been used with greater success. Some studies suggest that if the ID of the target Bluetooth device is known, two devices can go straight to the \"paging\" phase and avoid the 10 second long \"discovery\" phase [12, 13]. Otherwise, a user could potentially walk through a beacon's area faster than his phone can establish a connection. Besides electromagnetic waves, smartphones can send and receive sound waves via their onboard speaker(s) and microphone. Compared to electromagnetic (light) waves, sound travels much slower making it more practical to use its time-of-flight for determining position, even on hardware not designed for positioning. [PERSON] _et al._[14] showed that it is possible to utilize sound in order to measure the distance between two mobile phones using synchronized time-of-arrival techniques. Although mobile phone hardware was designed to deal with audible frequencies (below 20 KHz), it is actually capable of producing inaudible frequencies up to 22 KHz. In a study done by [PERSON] _et al._[15] it was shown that an ultrasonic signal can be emitted from a mobile device and successfully captured by a conventional microphone. Limitations of generating ultrasound signals on mobile phones were studied in our previous work [16]. It was observed that all mobile phones tested were able to successfully produce ultrasonic signals without any audible noise as long as speaker volume settings were below a certain threshold, which was unique to each phone. Together, a slow propagation speed and ultrasound support mean noise-free centimeter-level positioning is possible on COTS smartphones and form the basis of our mobile indoor positioning approach.