Journal ArticleDOI
Multiantenna-Assisted Spectrum Sensing for Cognitive Radio
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TLDR
The results show that the proposed GLRT exhibits better performance than other existing techniques, particularly when the number of samples is small, which is particularly critical in vehicular applications.Abstract:
In this paper, we consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, and so, detection based on a small number of samples is particularly advantageous for vehicular applications. Assuming no prior knowledge of the primary user's signaling scheme, the channels between the primary user and the cognitive user, and the variance of the noise seen at the cognitive user, a generalized likelihood ratio test (GLRT) is developed to detect the presence/absence of the primary user. Asymptotic performance analysis for the proposed GLRT is also presented. A performance comparison between the proposed GLRT and other existing methods, such as the energy detector (ED) and several eigenvalue-based methods under the condition of unknown or inaccurately known noise variance, is provided. Our results show that the proposed GLRT exhibits better performance than other existing techniques, particularly when the number of samples is small, which is particularly critical in vehicular applications.read more
Citations
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Journal ArticleDOI
Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances
TL;DR: Cognitive radio is introduced to exploit underutilized spectral resources by reusing unused spectrum in an opportunistic manner and the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier.
Journal ArticleDOI
Cognitive Radio Techniques Under Practical Imperfections: A Survey
Shree Krishna Sharma,Tadilo Endeshaw Bogale,Symeon Chatzinotas,Bjorn Ottersten,Long Bao Le,Xianbin Wang +5 more
TL;DR: This survey paper provides an overview of the enabling techniques for CR communications and discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches toward addressing these imperfections.
Journal ArticleDOI
Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach
TL;DR: A deep reinforcement learning-based method is developed, which the secondary user can use to intelligently adjust its transmit power such that after a few rounds of interaction with the primary user, both users can transmit their own data successfully with required qualities of service.
Journal ArticleDOI
Detection of Rank- $P$ Signals in Cognitive Radio Networks With Uncalibrated Multiple Antennas
TL;DR: This work studies the problem of detecting a Gaussian signal with rank-P unknown spatial covariance matrix in spatially uncorrelated Gaussian noise with unknown covariance using multiple antennas and derived the generalized likelihood ratio test (GLRT).
Journal ArticleDOI
Power Control Based on Deep Reinforcement Learning for Spectrum Sharing
TL;DR: An asynchronous advantage actor critic (A3C)-based power control of SU that is a parallel actor-learners framework with root mean square prop (RMSProp) optimization is proposed that enables the network to converge quickly.
References
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