NEAR REAL-TIME SPECTRUM ANALYZER

Abstract

Pakistan’s critical wireless communication depends heavily on the band 175MHz-225MHz thus making it necessary to effectively monitor and manage this spectrum. It is for this reason that our team is working on the development of a real-time spectrum analyzer, tailored specifically for this critical band.This system will probe 51 discrete channels that fall within the specified frequency range. In its heart lies a programmable clock generator called LMK03328. Such a device allows accurate tuning of the center frequency enabling the system to zoom into exact channels where detailed scrutiny can be done. Moreover, there is an ESP32 microcontroller that automatically switches between the 51 channels. The MPSOC Genesys Zynq UltraScale+ provides the core functionality of the analyzer. This powerful System-on-Chip has enough processing power to handle real-time signal processing tasks. At its core, Fast Fourier Transform (FFT) computations are used by the system to convert captured signals from time domain into frequency domain which is then subjected to spectrum analysis. A user-friendly operator console built with QT technology forms an excellent platform through which users can interact with the spectrum analyser in a seamless manner. With such a console, users are able to exactly choose specific channels which they may want to carry out more in depth analyses,visualize the received frequency spectrum in real-time and look at the noise levels within each of the 51 channels. This information allows us to know which channels are crowded, where interference is coming from and eventually improve the quality of communication. The uses for this spectrum analyzer go way beyond mere monitoring. Spectrum Management by regulatory bodies can use it to aid in efficient allocation of channels as well as identifying unauthorized transmissions. By using it, cellular network operators can identify congested 7 channels and offload traffic to frequencies with lower noise level to optimize their network performance. Also, this could be a powerful instrument for detecting and mitigating interference, hence enhancing overall reliability and security of communication. As this project moves forward, there is great potential for its future development. The system may be made smarter so that it can also understand what kind of interference signal it is. Artificial Intelligence incorporation would enable identification of noisy sources via computer programs while suggesting remedial measures taken through machine learning methods. Lastly, operator console could be transformed into a web-based platform making it possible to monitor/control remotely thereby increasing the scope/efficiency of this innovative spectrum analyser.