Comparative study of Radio Mobile and ICS Telecom propagation prediction models for DVB-T

In this paper, a comparative study between the results of a measurement campaign conducted in northern Greece and simulations performed with Radio Mobile and ICS Telecom radio planning tools is performed. The DVB-T coverage of a transmitting station located near the city of Thessaloniki is estimated using three empirical propagation models (NTIA-ITS Longley Rice, ITU-R P.1546 and Okumura-Hata-Davidson) and one deterministic model (ITU-R 525/526). The best results in terms of minimum average error and standard deviation are obtained using the deterministic model and the NTIA-ITS Longley Rice empirical model. In order to improve the results, the tuning options available in the ICS Telecom software are used on the Okumura-Hata-Davidson model, leading to a significant increase in accuracy

Three-Event Energy Detection with Adaptive Threshold for Spectrum Sensing in Cognitive Radio Systems

Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one iteration. The proposed algorithm is analyzed and illustrated with numerical results obtained from simulations that closely match the theoretical results and show that it outperforms the conventional ED (CED) algorithm for spectrum sensing

EXIT charts analysis for turbo-TCM schemes using non-binary RSC encoders

International audienc

A New ML Detector for Trellis-Coded Spatial Modulation Using Hard and Soft Estimates

International audienceIn this paper we propose a new detector for the spatial modulation (SM) receiver. In trellis coded spatial modulation (TCSM) schemes, the joint detection is used for identifying both the antenna index and the transmitted symbol. We define a hybrid maximum-likelihood (ML) SM detector, which determines the transmit antenna index soft estimate and the transmitted symbol hard estimate. The antenna indexes soft estimates are decoded using the logarithmic maximum a posteriori probability (log-MAP) algorithm. It is shown that for at least four receive antennas, the hybrid ML-SM detector offers a coding gain of at least 2 dB over the hard-output solutions in spatially correlated (SC) channels. The proposed detector is less complex than soft-output one, with a negligible bit error rate (BER) performance decrease. The BER is estimated by simulation for QPSK-TCSM transmissions over stationary Rayleigh and SC fading channels with additive white Gaussian noise (AWGN)

A New ML Detector for Trellis-Coded Spatial Modulation Using Hard and Soft Estimates

International audienceIn this paper we propose a new detector for the spatial modulation (SM) receiver. In trellis coded spatial modulation (TCSM) schemes, the joint detection is used for identifying both the antenna index and the transmitted symbol. We define a hybrid maximum-likelihood (ML) SM detector, which determines the transmit antenna index soft estimate and the transmitted symbol hard estimate. The antenna indexes soft estimates are decoded using the logarithmic maximum a posteriori probability (log-MAP) algorithm. It is shown that for at least four receive antennas, the hybrid ML-SM detector offers a coding gain of at least 2 dB over the hard-output solutions in spatially correlated (SC) channels. The proposed detector is less complex than soft-output one, with a negligible bit error rate (BER) performance decrease. The BER is estimated by simulation for QPSK-TCSM transmissions over stationary Rayleigh and SC fading channels with additive white Gaussian noise (AWGN)

Drone Detection and Defense Systems: Survey and a Software-Defined Radio-Based Solution

With the decrease in the cost and size of drones in recent years, their number has also increased exponentially. As such, the concerns regarding security aspects that are raised by their presence are also becoming more serious. The necessity of designing and implementing systems that are able to detect and provide defense actions against such threats has become apparent. In this paper, we perform a survey regarding the different drone detection and defense systems that were proposed in the literature, based on different types of methods (i.e., radio frequency (RF), acoustical, optical, radar, etc.), with an emphasis on RF-based systems implemented using software-defined radio (SDR) platforms. We have followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines in order to provide a concise and thorough presentation of the current status of the subject. In the final part, we also describe our own solution that was designed and implemented in the framework of the DronEnd research project. The DronEnd system is based on RF methods and uses SDR platforms as the main hardware elements