GSM based Communication-Sensor (CommSense) System

Abstract

Using communication signals for radar applications has been a major area of

research in radar engineering. In the recent years, due to the widely available

wireless signals, a new area of research called commensal radars has emerged.

Commensal radars use available wireless Radio Frequency (RF) signals to detect

and track targets of interest. This is achieved by placing two antennas, one

towards the transmitting base station and the other towards the surveillance

area. The signal received by these two antennas are correlated to determine the

location and velocity of the target.

When a signal passes through a channel, it reects o_ the obstacles within its

path. These reections usually degrade quality of the signal and cause interference

to the telecommunication systems. To mitigate the e_ects of the channel

on a signal these systems transmit a known bit sequence within each frame.

Our goal, with this thesis, is to design and implement a working prototype of a

novel architecture for the commensal radar system, which uses these known bit

sequences to extract the channel information and determine events of interest.

The major novelties of the system are as follows. Firstly, this system will be

built upon existing communication systems using Software De_ned Radio (SDR)

technology. Secondly, this design eliminates the need for a reference antenna,

which reduces the cost of the system and creates an opportunity to make the

system portable. We name this system Communication-Sensing (CommSense).

Since, our plan is to use Global System for Mobile Communication (GSM) as

the parent system for the prototype development, we decide to update the name

to GSM based Communication-Sensing (GSM-CommSense) system.

This thesis begins with theoretical analysis of the feasibility of the GSM-CommSense

system. First of all, we perform a link budget analysis to determine the power

requirements for the system. Then we calculate the ambiguity function and

Cram_er-Rao Lower Bound (CRLB) for a two-path received signal model. With

encouraging theoretical results, we design a prototype of the system that can

capture real GSM base station broadcast signals. After the design of the GSMCommSense

system, we capture channel data from multiple locations with varying

environmental conditions. The aim for this set of experiment is to be able

to distinguish between di_erent environmental conditions. Then, we performed

statistical analysis on the data by means of Probability Density Function (PDF)

_tting, a goodness-of-_t test called chi-square test and a clustering algorithm

called Principal Components Analysis (PCA). We have presented the results

from each analysis and discussed them in detail. Upon, receiving positive results

in each step we have decided to move towards using learning algorithms

to categorise the data captured by the system. We have compared two widely

accepted supervised learning algorithms, called Support Vector Machines (SVM)

and Multi-Layer Perceptron (MLP). The results showed that with the current

hardware capabilities of the system and the amount of data available per GSM

frame, the performance of SVM is better than MLP. Thus, we have used SVM

to classify two events of detection and classi_cation across a wall. We have

presented our _ndings and discussed the results in detail.

We conclude our current work and provide scope for future work in development

and analysis of the GSM-CommSense system.