# Real-Time Statistical Measurement of Wideband Signals Based on Software Defined Radio Technology
## 2 Advanced Electromagnetic Spectrum Measurement Capabilities
APD defines the probability of an amplitude occurring within a defined bandwidth and time interval [31]. The statistical description of the power levels of the signal, as in the case of APD measurements, is achieved by using time domain data, with the note that for a complete description of the signal characteristics, it is necessary to evaluate the CCDF curve. However, the interest in peak values and signal power statistics makes CCDF statistical measurements very important and not to be neglected in the quasi-stochastic characterization of new signals. Many studies approach the technique of PAPR reduction of OFDM signals using statistical CCDF measurements [32; 33; 34], but to analyze this parameter in detail, a statistical analysis of its evolution in time is required. CCDF curves are also important in the design of power amplifiers due to the nonlinear nature of some components, as well as for testing and debugging devices to assess compression effects [35]. The motivation for this study stems from the authors' interest in implementing various applications on SDR platforms (both low-cost and higher-cost) to highlight their capabilities in terms of performance, cost, and configuration flexibility. The SDR platforms match and even exceed the performance of real-time spectral analyzers, considering that the price of these instruments increases significantly for real-time monitoring of larger bandwidths. Given the need to address the latest standards, such as 5G and IEEE 802.11 ax, and to perform multiple measurements, there are few instruments on the market that are affordable. For higher-order statistical analysis, the acquisition bandwidth must be equal to the channel bandwidth, and for technologies such as 4G, 5G, 802.11 ac/ax, this is difficult to achieve. This means that we need a system with high acquisition bandwidth, and traditional spectrum analyzers are not capable of analyzing such statistical measurements, and those that do have these capabilities come at a particularly high price. To implement CCDF and APD statistical analysis, the acquisition bandwidth must be equal to the channel bandwidth. This is a significant limitation even for high-performance analyzers. A real-time bandwidth of 160 MHz is a critical parameter. For this, the cost of the analyzer becomes very high and the SDR solution is a viable alternative at an acceptable cost. Therefore, we propose a cost-effective, real-time, large bandwidth, SDR-based measurement system with integrated CP and CCDF measurement capabilities. Both CP and CCDF measurements are implemented in software and the proposed system is tested using a traditional SA and signal generator-based setup. After parameterization, the measurement system is applied to 4G/5G and Wi-Fi signals, demonstrating the versatility, scalability and adaptability of SDR platforms to modern communication standards through software reconfiguration. This research makes some notable contributions to the existing literature. Specifically, it focuses on the use of SDR platforms for spectrum monitoring and analysis, providing a cost-effective and efficient alternative to traditional spectrum analyzers. This approach allows for flexibility and customization in the implementation of measurement functions. The research presents the design and implementation of an SDR-based real-time spectrum monitoring system capable of monitoring extended frequency bands while incorporating channel power (CP) measurements and complementary cumulative distribution function (CCDF). This integrated feature set enables comprehensive analysis of signal quality and statistical parameters. In addition, the research includes performance evaluations comparing the SDR system to a high-performance spectrum analyzer, highlighting the potential, capabilities and limitations of SDR platforms in spectrum monitoring. As a result, this research provides new insights and practical implementation strategies that differentiate it from existing published material in this area.