The major challenge for accurate fingerprint-based indoor localization is the design of robust and discriminative wireless signatures. Even though WiFi RSSI signatures are widely available indoors, they vary significantly over time and are susceptible to human presence, multipath, and fading due to the high operating frequency. To overcome these limitations, we propose to use FM broadcast radio signals for robust indoor fingerprinting. Because of the lower frequency, FM signals are less susceptible to human presence, multipath and fading, they exhibit exceptional indoor penetration, and according to our experimental study they vary less over time when compared to WiFi signals. In this work, we demonstrate through a detailed experimental study in 3 different buildings across the US, that FM radio signal RSSI values can be used to achieve roomlevel indoor localization with similar or better accuracy to the one achieved by WiFi signals. Furthermore, we propose to use additional signal quality indicators at the physical layer (i.e., SNR, multipath etc.) to augment the wireless signature, and show that localization accuracy can be further improved by more than 5%. More importantly, we experimentally demonstrate that the localization errors of FM andWiFi signals are independent. When FM and WiFi signals are combined to generate wireless fingerprints, the localization accuracy increases as much as 83% (when accounting for wireless signal temporal variations) compared to when WiFi RSSI only is used as a signature.
Camera Ready: http://research.microsoft.com/pubs/163038/sys029fp-Chen.pdf
Public Review uploaded by RomitRoyChoudhury:
Indoor localization has been a long-standing problem, and becoming increasingly important due to the explosion in location based applications. An ideal solution calls for a continuous, high-accuracy, low-energy, zero-calibration, infrastructure-less system, that is robust to changing indoor environments. Clearly, this is a high bar, and perhaps explains why the research community has been aggressively pursuing this problem (and the need for more).
While most recent papers have investigated techniques with known/established tools, this paper adds to the toolkit by systematically showing that FM radio signals are amenable to indoor localization. The higher FM wavelengths are less affected by humans and obstructions (offering better stability), while penetrating quite well into walls and ceilings (extending good coverage). Authors also show that the FM signals are independent of WiFi, and thereby their combination can lead
to a richer fingerprint. Systematic measurements demonstrate high accuracy against dynamism in the environment.
The contribution in the paper lies in shining light on a direction that was relatively unexplored to this point, and then performing a thorough investigation of the opportunities/pitfalls in this direction. Of course, this paper is not the last one on this topic, and is expected to spawn other ideas that optimize or build on them. For instance, the temporal properties of the signals need to be characterized over long durations; can the fingerprinting overhead be reduced, perhaps by exploiting
spatial correlation on the signals; how much of environmental changes are necessary before the fingerprints begin to change; even at a given location, what is the limit of accuracy with FM; what is the limit of accuracy with WiFi and how do they compare; are there other frequency bands (e.g., TV) on which similar fingerprints are feasible.
The review committee believes that making FM receivers double as a localization module can be useful/enabling, and this paper gets the credit for bringing this to light. Of course, more research is needed before it becomes a reality.
Authors are in complete agreement with the review summary provided by Romit Roy Choudhury. This paper is not going to be the last paper in indoor localization as there are still a lot of open issues to be researched in detail, such as exploiting spatial signal correlation, and reducing fingerprinting just to mention a few. However, we strongly believe that this work opens up a new direction in indoor localization as it is the first systematic study that demonstrates how currently available FM signals can be leveraged for accurate indoor localization. The implications of this finding, as the review panel already hinted, go beyond just FM signals and touch on the overall growing field of whitespace networking. Our work shows that as whitespace signals (FM/AM/TV signals) are rapidly getting converted to a networking medium, they could also be double purposed to enable accurate indoor localization. The importance of this new direction is also amplified by our finding that FM signals, and most probably other whitespace signals, are complementary to existing WiFi signals in the sense that their localization errors are independent.