Browsing by Subject "Software Defined Radio"

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    Digitized Radio broadcast seeker (DRBS)
    (2025) Sithole, Simbisai Mfunani; Winberg, Simon
    The use of Software Defined Radio (SDR) has greatly increased the flexibility and programmability of radio systems due to the implementation of radio functions in software. The transfer of traditionally hardware-based signal processing to the software domain enables web SDR receivers to be hosted on the internet as data streaming services. Hosting SDR receivers online allows many users to tune in and listen to broadcast transmissions simultaneously. While significant advancements have been made in SDR hardware technology and making data easily accessible to users, developer productivity has been lacking. The market lacks a simple software development kit that would enable researchers and developers to experiment and create innovative software applications using existing data and components. The aim of this project is to develop an application framework that provides a collection of pre-built modules, components, code libraries, tools and Application Programmable Interfaces (API) that will allow developers to quickly create innovative applications using broadly available Software Defined Radio (SDR) data by leveraging pre- developed infrastructure. The Digitized Radio Broadcast Seeker (DRBS) application as an implementation of the application framework provides a platform for web streaming that aggregates web SDRs and helps developers search for broadcast transmissions of interest as well as build solutions around the streamed transmissions. The research project demonstrated that DRBS could be used to monitor Morse code signals to detect emergencies such as distress calls, weather alerts and other critical broadcasts. After conducting latency and average server response time performance tests, it was concluded that despite the additional infrastructure layer, the DRBS application did not add significant overhead to the signal processing path and could be considered for additional use cases such as identifying FM radio stations and analyzing spectrum usage across different geographical regions.
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    GSM based Communication-Sensor (CommSense) System
    (2018) Bhatta, Abhishek; Mishra, Amit
    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 reflects off the obstacles within its path. These reflections usually degrade quality of the signal and cause interference to the telecommunication systems. To mitigate the effects 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 Defined 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 different environmental conditions. Then, we performed statistical analysis on the data by means of Probability Density Function (PDF) fitting, a goodness-of-fit 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 classification across a wall. We have presented our findings 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.