Smartphone Used as Antenna to Accurate Outdoor Ap Location

1. Background

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), the user's body becomes an obstacle and blocks the signals from reaching the smartphone. We make the user rotates himself in place (c), the received signal on phone displays an interesting phenomenon, there will be a peak when he faces the AP and a dip when his back faces the AP. So a user can gain a hint of which direction points towards the AP by measuring signal strength at different rotational angles.

There are detailed smartphone experiments that not only confirm the assumption, but also study the impact the body act as an obstacle has the signal on strength as the user rotates himself. The experiments also help to understand the impact on results based on different causes such as propagation environment (LOS, Complex LOS, No LOS), phone hardware (Droid, G1, IPhone, Windows Mobile) and WiFi standards (802.11b/g, 802.11n). From the experiments results we can get the two key observations (Shown as Figure2). First, the position of the user's body can importantly affect the smartphone's received WiFi signal strength. When the user makes his back facing the AP, His body becomes an obstacle and degrades the received signal strength. Second, we use BF (Back facing AP) to mark the opposite AP direction where the blocking effect should be at its strongest. And it's clear that an accurate AP location system can't simply rely on finding the angle with lowest signal strength, should use more sophisticated techniques to indicate the AP direction.

Figure2. Two observations

4. Accurate Access Point location using Borealis System

According to our observations, we develop Borealis , a new AP localization system for commodity smartphones that makes signal strength artifacts to compute the direction of an AP. Borealis uses off-the-shelf smartphones and produces real-time results with a few of measurements. And Borealis users can perform robust directional analysis by turning their bodies on a 360oaxis.

Borealis has two critical requirements. First, Borealis must use minimal energy and computational resource in its directional analysis since the resources on smartphones is limited. Second, Borealis must