Spectrum sensing in satellite cognitive radios: Blind signal detection technique

2016 ◽  
Vol 58 (6) ◽  
pp. 1377-1384 ◽  
Author(s):  
Bilal Muhammad Khan ◽  
Muhammed Mustaqim ◽  
Bilal A. Khawaja ◽  
Syed ShabeehUlHusnain
Keyword(s):  
Signal Detection ◽  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Detection Technique ◽  
Blind Signal

Practical Implementation of Spectrum Sensing and Signal Detection for Satellite Broadcasting Systems

2016 ◽  
Vol E99.B (8) ◽  
pp. 1894-1901
Author(s):  
Hiroyuki KAMATA ◽  
Gia Khanh TRAN ◽  
Kei SAKAGUCHI ◽  
Kiyomichi ARAKI
Keyword(s):  
Signal Detection ◽  
Spectrum Sensing ◽  
Practical Implementation ◽  
Satellite Broadcasting

scholarly journals Novel filter bank-based cooperative spectrum sensing under practical challenges for beyond 5G cognitive radios

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sener Dikmese ◽  
Kishor Lamichhane ◽  
Markku Renfors
Keyword(s):  
Spectrum Sensing ◽  
Filter Bank ◽  
Cooperative Spectrum Sensing ◽  
Minimum Energy ◽  
Cognitive Radios ◽  
Spectrum Management ◽  
Wireless Channel ◽  
First Case ◽  
Channel Effects

AbstractCognitive radio (CR) technology with dynamic spectrum management capabilities is widely advocated for utilizing effectively the unused spectrum resources. The main idea behind CR technology is to trigger secondary communications to utilize the unused spectral resources. However, CR technology heavily relies on spectrum sensing techniques which are applied to estimate the presence of primary user (PU) signals. This paper firstly focuses on novel analysis filter bank (AFB) and FFT-based cooperative spectrum sensing (CSS) techniques as conceptually and computationally simplified CSS methods based on subband energies to detect the spectral holes in the interesting part of the radio spectrum. To counteract the practical wireless channel effects, collaborative subband-based approaches of PU signal sensing are studied. CSS has the capability to relax the problems of both hidden nodes and fading multipath channels. FFT- and AFB-based receiver side sensing methods are applied for OFDM waveform and filter bank-based multicarrier (FBMC) waveform, respectively, the latter one as a candidate beyond-OFDM/beyond-5G scheme. Subband energies are then applied for enhanced energy detection (ED)-based CSS methods that are proposed in the context of wideband, multimode sensing. Our first case study focuses on sensing potential spectral gaps close to relatively strong primary users, considering also the effects of spectral regrowth due to power amplifier nonlinearities. The study shows that AFB-based CSS with FBMC waveform is able to improve the performance significantly. Our second case study considers a novel maximum–minimum energy detector (Max–Min ED)-based CSS. The proposed method is expected to effectively overcome the issue of noise uncertainty (NU) with remarkably lower implementation complexity compared to the existing methods. The developed algorithm with reduced complexity, enhanced detection performance, and improved reliability is presented as an attractive solution to counteract the practical wireless channel effects under low SNR. Closed-form analytic expressions are derived for the threshold and false alarm and detection probabilities considering frequency selective scenarios under NU. The validity of the novel expressions is justified through comparisons with respective results from computer simulations.

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