WiFi networks are universally used in our everyday lives. It provides wireless connectivity for a wide range of mobile networking devices. All digital devices can connect to the internet via a wireless network access point that has a range of about 20 meters indoors such as homes and offices and a greater range outdoors such as parks, schools and shopping centers. As Internet users become reliant on WiFi access points (APs) to connect their smartphones, tablets and laptops, the availability and performance of tomorrow’s networks will depend on well tuned and managed access points. A key part of managing access points is the ability to locate individual access points based on their signal. Current techniques (RSS Grandient, Signal Map, Directional Antenna) to locate outdoor WiFi access points require extensive wardriving measurements and low accuracy, determined by significant offline computation or complex hardware components that would cost several thousand dollars. In order to solve this problem, there is a commercial need for a cost and time-efficient alternative way to accurate outdoor WiFi AP location.
2. A key insight for Accurate AP location
A potential solution that focus on cost and time-efficient using common off-the-shelf hardware would make it available to home users and small business managing their local hotspots. So we propose a way to locate APs in real-time using smartphones. Our insight is that by rotating a standard wireless receiver (smartphone) around a blocking object, we can effectively emulate the sensitivity and functionality of a directional antenna. By “rotating” the receiver’s position with respect to the obstacle, and observing the received signal strength, we can determine the approximate direction of the transmitter. This process can be recognized as directional analysis. We assume that a user can accurately locate WiFi APs using common-off-the-shelf smartphones as receivers, and her own body as the blocking obstacle. To perform a directional analysis operation, she slowly rotates her body around 360 degrees, while keeping the smartphone in front of her and performing periodic received signal strength (RSS) measurements. The observed RSS should be at its lowest point when the user’s body is directly between the smartphone and the wireless AP. The hypothesis has extensive feasibility that we can detect these signal strength artifacts on different kinds of smartphone platforms (e.g.: Android, Windows mobile, Apple Iphone4) for a variety of outdoor environments (e.g.: Simple Line-of-Sight, Complex LOS, No LOS ). The main idea of insight is that we can develop a model for detecting signal dips
caused by blocking obstacles, and use it to produce a directional analysis technique that accurately predicts the direction of AP with an associated confidence value.
3. Blocking Obstacle Effect
According to mentioned above, it’s necessary to describe our simple problem scene that a user who hold a smartphone would like to find the physical location of a WiFi AP through its BSSID, with the purpose of locating a transmitting AP rather than determining his own location. We focus on Received Signal Strength (RSS) as the physical modality to locate a transmitter. We apply the insight for a consumption on our context of smartphone based AP location. It’s obvious the body of a user holding a smartphone will block a portion of incoming WiFi signal. The closer the user is to being on the straight line between the smartphone and the AP, the weaker the signal perceived by the phone. This effect of human body has been observed based on a variety of frequencies and radio hardware, including indoor environments as well.
Figure1 Figure1 shows that when facing the AP (1), the body is not an obstacle while on the other side, his back is towards the AP (2),...