Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge

Abstract

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.

Keywords: 5G; B5G; Interference Sensing; channel sensing; cognitive radio; full-duplex; half-duplex; internet of things; machine learning; spectrum sensing; wireless sensor network.

Figure 1

Cognitive Radio (CR) access paradigms.

Figure 2

The two main functioning modes of SU activity. Listen-before-Talk (LBT): SU remains silent during the sensing period and no sensing is performed during the transmission. Listen and Talk (LAT): sensing and transmission are made concurrently.

Figure 3

Spectrum Sensing processes under LBT and LAT. For LBT, no Self-Interference Cancellation (SIC) module is required since there is no simultaneous Transmit-Sense (TS), and the Test Statistic may be directly applied to the received signal. By contrast, SIC is applied before evaluating the Test Statistic in LBT to reduce the effect of SI on the Spectrum Sensing (SS) performance.

Figure 4

The communication mechanism in asynchronous Transmit-Receive (TR) mode. A delay of $T_s$ is made in order to reduce the collision time between the secondary and the primary transmissions.

Figure 5

Spatial Dimension of CR application: SU is able to exploit the spatial dimension by transmitting in a non-overlapping direction with the PU transmission. Here, SU should be able to estimate/know the PU beam in order to avoid the interference.