Abstract
With the advent of Sixth Generation (6G) telecommunication systems already envisioned, increased effort is made to further develop current communication technologies, so they can be incorporated together with the novel ones, to deliver uninterrupted and satisfactory service for any application in every location on the ground, underwater, in the air, or in space. One such technology is Cognitive Radio (CR) which has received much attention due to its potential for increase of utilization, especially in the bands below 6 GHz. The main enabler for CR is spectrum sensing because it provides the opportunity for dynamic assessment of the radio environment to identify unused channels. This functionality has been the object of many research works for that very reason. In spite of this, the provision of accurate and fast spectrum characterization in time, frequency and space has proven to be a non-trivial task. This paper presents a detailed review of probabilistic spectrum sensing methods classified by the feature they extract from the received signal samples, to provide accurate detection of the primary user (PU) signal. The main design characteristics (such as probability of detection, robustness to noise and fading, signal/noise model assumptions, and computational complexity), strengths and weaknesses for each type are also summarized. Based on current concepts for 6G networks and applications, a framework for human-centric cognition-based wireless access is presented, which specifies the role of spectrum sensing-based CR in future networks.
Highlights
For over two decades, the application of Cognitive Radio (CR) and softwaredefined radio (SDR) based devices has been established as a significant and ever-expanding field in wireless communications
Increased spectrum utilization has been established that the static spectrum assignment of most current and legacy networks is quite inefficient because a significant portion of the expensive frequency resource is not used at all times in many regions covered by a wireless system
This paper provides an in-depth survey of the main types of probabilistic local spectrum sensing methods, according to the features they extract to determine the spectrum occupancy
Summary
The application of CR and softwaredefined radio (SDR) based devices has been established as a significant and ever-expanding field in wireless communications. The authors in [28] present a prominent survey of the general types of spectrum sensing approaches including narrow and wideband methods together with their standard limitations in terms of the a priori information (such as the PU signal’s parameters or noise fluctuations) required for efficient detection. ADVANCES IN FEATURE-BASED PROBABILISTIC LOCAL SPECTRUM SENSING This section surveys a broad range of sensing methods for which the emphasis is on accurate detection of the PU signal for an individual CR device They are categorized according to the feature they extract from the acquired measurement samples in order to determine whether the spectrum band is occupied or not.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
