Detection of OFDM modulations based on the characterization in the phase diagram domain

Signal modulation identification is of high interest for applications in military communications, but is not limited only to this specific field. Some possible applications are related to spectrum surveillance, electronic warfare, quality services, and cognitive radio. Distinguishing between multi-carrier signals, such as orthogonal frequency division multiplexing (OFDM) signals, and single-carrier signals is very important in several applications. Conventional methods face a stalemate in which the classification accuracy process is limited, and, therefore, new descriptors are needed to complement the existing methods. Another drawback is that some features cannot be extracted using conventional feature extraction techniques in practical OFDM systems. This paper introduces a new signal detection algorithm based on the phase diagram characterization. First, the proposed algorithm is described and implemented for simulated signals in MATLAB. Second, the algorithm performance is verified in an experimental scenario by using long-term evolution OFDM signals over a software-defined radio (SDR) frequency testbed. Our findings suggest that the algorithm provides good detection performance in realistic noisy environments

SDR-Enabled Multichannel Real-Time Measurement System for In Situ EMF Exposure Evaluation

The spatial and temporal variability of the signals emitted by modern communication devices produced a paradigm shift in approaching the human exposure to electromagnetic fields (EMF). This inherent variability requires in situ, agile EMF measurement solutions capable of performing real-time isotropic measurements. The aim of this paper is to describe a new real-time, highly flexible multichannel EMF measurement system that consists of a sensor connected to state-of-the-art software-defined radio (SDR) equipment. In this paper an electric field sensor is proposed, but we also provide information on the extension of the probe to electric and magnetic fields. In the receiver section, the proposed solution is compared in terms of performances (sensitivity and accuracy), costs, and requirements, with standard solutions based on spectrum analyzers or a digital oscilloscope. Finally, the proposed solution was tested considering the signals emitted in various operating scenarios by a mobile device operating in the LTE-A and IEEE 802.11ax mobile communication standards. The results confirm the versatility and efficiency of the proposed solution for in situ EMF measurements of signals emitted by the new generation communication devices

Detection of OFDM modulations based on the characterization in the phase diagram domain

International audienceSignal modulation identification is of high interest for applications in military communications, but is not limited only to this specific field. Some possible applications are related to spectrum surveillance, electronic warfare, quality services, and cognitive radio. Distinguishing between multi-carrier signals, such as orthogonal frequency division multiplexing (OFDM) signals, and single-carrier signals is very important in several applications. Conventional methods face a stalemate in which the classification accuracy process is limited, and, therefore, new descriptors are needed to complement the existing methods. Another drawback is that some features cannot be extracted using conventional feature extraction techniques in practical OFDM systems. This paper introduces a new signal detection algorithm based on the phase diagram characterization. First, the proposed algorithm is described and implemented for simulated signals in MATLAB. Second, the algorithm performance is verified in an experimental scenario by using long-term evolution OFDM signals over a software-defined radio (SDR) frequency testbed. Our findings suggest that the algorithm provides good detection performance in realistic noisy environments