Maximum-minimum energy detection for spatial spectrum sensing

Author(s):  
Reena Yadav ◽  
N. P. Singh
Author(s):  
Heba A.Tag El-Dien ◽  
Rokaia M. Zaki ◽  
Mohsen M. Tantawy ◽  
Hala M. Abdel-Kader

Detecting the presence or absence of primary user is the key task of cognitive radio networks. However, relying on single detector reduces the probability of detection and increases the probability of missed detection. Combining two conventional spectrum sensing techniques by integrating their individual features improves the probability of detection especially under noise uncertainty. This paper introduces a modified two-stage detection technique that depends on the energy detection as a first stage due to its ease and speed of detection, and the proposed Modified Combinational Maximum-Minimum Eigenvalue based detection as a second stage under noise uncertainty and comperes it with the case of using Maximum-Minimum Eigenvalue and  Combinational Maximum-Minimum Eigenvalue as a second stage.


2017 ◽  
Vol 57 (4) ◽  
pp. 235 ◽  
Author(s):  
Hikmat Najem Abdullah ◽  
Hadeel Sami Abed

Cognitive radio (CR) is a wireless technology developed to improve the usage in the spectrum frequency. Energy consumption is considered as a big problem in this technology, especially during a spectrum sensing. In this paper, we propose an algorithm to improve the energy consumption during the spectrum sensing. The theoretical analysis to calculate the amount of energy consumption, using the proposed method during sensing stage as well as the transmission stage during transmitting a local decision to the fusion center FC, are derived. The proposed algorithm is using energy detection technique to detect the presence or absence of the primary user (PU). The proposed algorithm consists of two stages: the coarse sensing stage and fine sensing stage. In the coarse sensing stage, all the channels in the band are sensed shortly and the channel that have maximum (or minimum) energy is identified to make a dense fine sensing for confirming the presence of the PU signal (or hole). The performance of the proposed algorithm is evaluated in two scenarios: non-cooperative, and cooperative in both the AWGN and Rayleigh fading channels. The simulation results show that the proposed method improves the energy consumption by about 40% at a low SNR values, when compared with the traditional methods based on a single sensing stage and more advanced method based on censoring and sequential censoring algorithms.


Author(s):  
Sener Dikmese ◽  
Kishor Lamichhane ◽  
Markku Renfors

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.


Author(s):  
Mark S. Oude Alink ◽  
Andre B. J. Kokkeler ◽  
Eric A. M. Klumperink ◽  
Gerard J. M. Smit ◽  
Bram Nauta

Author(s):  
F. Penna ◽  
C. Pastrone ◽  
M. A. Spirito ◽  
R. Garello

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