The increase in channel bandwidth and peak-to-average power ratio (PAPR) of modern communication standards poses a serious challenge to performing channel power (CP) and complementary cumulative distribution function (CCDF) measurements in real-time using standard measurement solutions based on spectrum analyzers (SA). Recently, Software Defined Radio (SDR) technology has become a viable alternative to the conventional real-time spectrum monitoring approach based on SA due to its reduced cost. Therefore, in this paper, we propose a novel, innovative, agile and cost-effective solution to enable both CP and CCDF measurements on a state-of-the-art SDR platform. The proposed solution exploits the ability of the SDR equipment to access signal samples in the time domain and defines both CP and CCDF-type measurements. The two measurement functions are software implemented in GNU Radio by designing customized blocks and integrated into a graphical user interface. The proposed system was first tested and parameterized in a controlled environment using emitted signals specific to the IEEE 802.11ax family of wireless local area networks. After parameterization, the SDR-based system was used for over-the-air measurements of signals emitted in the 4G+, 5G and 802.11ax communication standards. By performing the measurement campaign, we have demonstrated the capabilities of the measurement system in performing real-time measurements on broadband channels (up to 160 MHz for IEEE 802.11ax). Altogether, we have proved the usability of CP and CCDF measurement functions in providing valuable insights into the power distribution characteristics of signals emitted by the latest communication standards. By exploiting the versatility of SDR technology, we have enabled a cost-effective solution for advanced real-time statistical measurements of modern broadband signals.
ChatGPT is a type of language model that uses machine learning algorithms to generate responses to natural language input. Its advanced technology can revolutionize the way humans interact with machines by creating more natural and intuitive communication. However, the accuracy of ChatGPT’s responses may be compromised by biased or inaccurate data, which highlights the importance of carefully evaluating its output. Furthermore, early versions of ChatGPT were found to produce academic papers with missing references, which may compromise the credibility of research in the academic publishing industry. This underscores the need to establish regulations and guidelines that ensure the ethical and transparent use of these technologies, and to avoid relying solely on automated tools like ChatGPT without thoroughly reviewing the literature. In order to minimise the potential for inaccurate information in the classroom, an intuitive application based on the AI language (OpenAI - also used by ChatGPT) has been implemented. The application has been designed in such a way that it does not use internet databases as a search source and the answers to the questions are based on pre-established documentation that has been checked/certified by the educational institution/professors. The developed application can be installed either locally on a personal computer or on a file server/online library etc. and does not require access to a reliable Internet connection as in the case of ChatGPT.
The use of electromagnetic spectrum monitoring for military emissions is essential due to the mobility and diversity of military operations. A tactical communications system used in the military domain includes encrypted and unencrypted data, voice and video communications using wideband and narrowband waveforms. This research focuses on the development of a high capability monitoring system based on Software-Defined Radio (SDR) technology for monitoring military waveforms. The implemented system has been tested for its ability to detect both wideband military waveforms and narrowband frequency hopping waveforms. The proposed SDR-based system provides a cost-effective solution for military waveform monitoring that can be used for real-time monitoring and analysis of the electromagnetic spectrum.
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