Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge

Abbass Nasser , Hussein Al Haj Hassan , Jad Abou Chaaya , Ali Mansour (1, 2) , Koffi-Clément Yao

1 Lab-STICC_SI3 - Equipe Security, Intelligence and Integrity of Information
2 ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne

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.

Domaines: Traitement du signal et de l'image [eess.SP]

Abbass Nasser, Hussein Al Haj Hassan, Jad Abou Chaaya, Ali Mansour, Koffi-Clément Yao. Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge. Sensors, 2021, 21 (7), pp.2408. ⟨10.3390/s21072408⟩. ⟨hal-03212440⟩