Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth survey on the most recent advances in SS for CR. We start by explaining the Half-Duplex and Full-Duplex paradigms, while focusing on the operating modes in the Full-Duplex. A thorough discussion of Full-Duplex operation modes from collision and throughput points of view is presented. Then, we discuss the use of learning techniques in enhancing the SS performance considering both local and cooperative sensing scenarios. In addition, recent SS applications for CR-based Internet of Things and Wireless Sensors Networks are presented. Furthermore, we survey the latest achievements in Spectrum Sensing as a Service, where the Internet of Things or the Wireless Sensor Networks may play an essential role in providing the CR network with the SS data. We also discuss the utilisation of CR for the 5th Generation and Beyond and its possible role in frequency allocation. With the advancement of telecommunication technologies, additional features should be ensured by SS such as the ability to explore different available channels and free space for transmission. As such, we highlight important future research axes and challenging points in SS for CR based on the current and emerging techniques in wireless communications.

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International audienceDue to the increasing demand of wireless communication services and the limitation in the frequency resources, the Cognitive Radio (CR) has been initially proposed (Mitolal, IEEE Personal Commun 6:13–18, 1999 [1]) in order to solve the spectrum scarcity. CR distinguishes between two types of users, the Primary (PU) and the Secondary (SU) Users. PU has the legal right to use the spectrum bandwidth, while SU is an opportunistic user that can transmit on that bandwidth whenever it is vacant in order to avoid any interference with the signal of PU. Hence the detection of PU becomes a main priority for CR systems. The Spectrum Sensing is performed by CR to monitor PU activities. In actual CR systems (Yucek and Arslan, IEEE Commun Surv Tutorials 11:116–130, 2009 [2]), SU should stop transmitting while Spectrum Sensing is performed. The transmission of SU can be only resumed if PU is still absent. This procedure means that the CR can only operate in a Half-Duplex (HD) mode. Recently, many works have been proposed in order to attend the Full-Duplex (FD) mode. In other words, the Spectrum Sensing should be performed while SU is being active. Our work deals with the HD and FD of CR. First, we develop two Spectrum Sensing algorithms, based on the Cumulative Power Spectral Density (CPSD) of the received signal, dealing with the HD mode. These algorithms outperform the traditional Energy Detector (ED), the well known Cyclostationary Detector (CSD) based on the Generalized Likelihood Ratio Test (GLRT) and the Autocorrelation Detector (ACD). Furthermore, our algorithms are robust against the noise variance, so that the dependence on Noise Uncertainty (NU) presented in ED is avoided. In addition, the proposed algorithms are blind as they don’t require any prior information on the PU’s signal, contrary to Cyclostationary or Waveform detectors. Our algorithms make a decision on the PU presence by comparing the form of CPSD shape to curves depending on the CPSD of the noise. Two algorithms based on hard and soft cooperative schemes are introduced. In these algorithms, the spectrum is divided into two parts. The first part corresponds to negative frequencies, while the second part deals with the positive frequencies. Hence, two test statistics are evaluated, based on the CPSD of each of those two parts, and they are then combined according to the considered scheme. The False Alarm and Detection probabilities of the two proposed algorithms are evaluated analytically under Gaussian and Rayleigh fading channels. We examine our proposed detectors at a low Signal to Noise Ratio. The performance of our detectors is compared to that of ED, CSD and the ACD. Our detectors outperform ED, even at low oversampling rate, where CSD and ACD provide poor performance. Increasing the oversampling rate enhances the performance our algorithms as well as that of ACD and CSD. However, our algorithms remain better than ED, CSD and ACD for all tested values of oversampling rate. Furthermore, our detectors are less sensitive to NU than...

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Interest and need for Wireless Body Area Networks (WBANs) have significantly increased recently. WBAN consists of miniaturized sensors designed to collect and transmit data through wireless network, enabling medical specialists to monitor patients during their normal daily life and providing real time opinions for medical diagnosis. Many wireless technologies have proved themselves in WBAN applications, while others are still under investigations. The choice of the technology to adopt may depend on the disease to monitor and the performance requirements, i.e. reliability, latency and data rate. In addition, the suitable sensor is essential when seeking to extract the data related to a medical measure. This paper aims at surveying the wireless technologies used in WBAN systems. In addition to a detailed survey on the existing technologies, the use of the emerging Low Power Wide Area Network (LPWAN) technologies, and the future 5G, B5G and 6G is investigated, where the suitability of these technologies to WBAN applications is studied from several perspectives. Furthermore, medical applications of WBAN are discussed by presenting their methodologies, the adopted wireless technologies and the used sensors. Given that each medical application requires the appropriate sensor to extract the data, we highlight a wide range of the sensors used in the market for medical systems. Recent and future challenges in WBAN systems are given related to the power consumption, the emergence of the Internet of Things (IoT) technologies in WBAN and others.

This paper presents new spectrum sensing algorithms based on the cumulative power spectral density (CPSD). The proposed detectors examine the CPSD of the received signal to make a decision on the absence/presence of the primary user (PU) signal. Those detectors require the whiteness of the noise in the band of interest. The false alarm and detection probabilities are derived analytically and simulated under Gaussian and Rayleigh fading channels. Our proposed detectors present better performance than the energy (ED) or the cyclostationary detectors (CSD). Moreover, in the presence of noise uncertainty (NU), they are shown to provide more robustness than ED, with less performance loss. In order to neglect the NU, we modified our algorithms to be independent from the noise variance.

In this paper, a simultaneous frequency up- and down-conversion is performed using a cascaded semiconductor optical amplifier Mach–Zehnder interferometers (SOA-MZIs) link for radio-over-fiber (RoF) applications. The intermediate frequency (IF) signal carrying quadratic phase shift keying (QPSK) data at a frequency f 1 is up-converted at the SOA-MZI1 output at n f s ± f 1 , where n is the harmonic rank of the first sampling signal. In addition, this up-converted signal is concurrently up- and down-converted at the SOA-MZI2 output at m f s + n f s ± f 1 and | n f s ± f 1 − m f s | , respectively, where m is the harmonic rank of the second sampling signal. Using the virtual photonics integrated (VPI) simulator, it has been shown that the optical transmission system based on a cascaded SOA-MZIs link has a better efficiency and more endurable quality of the frequency mixing of QPSK signals and the higher frequency range for up- and down-conversions. Positive conversion gains are obtained at the highest mixing frequency of 101.9 and 86.3 GHz for up- and down-conversions, respectively. The best error vector magnitude provided using a cascaded SOA-MZIs link is 15.5% at the mixing frequency of 101.9 GHz for up-conversion and 18% at 86.3 GHz for down-conversion at the bit rate of 40,500 Mbit/s. The maximum bit rates of 40.5, 81, and 121.5 Gbit/s for QPSK, 16-QAM, and 64-QAM modulations, respectively, that meet the forward error correction limit is fulfilled by using a cascaded SOA-MZIs link. Another advantage of using the cascaded SOA-MZIs link is the up- and down-conversion simultaneously achieved at the second stage.