Signal processing techniques for sustainable cognitive radio communications
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Signal processing techniques for sustainable cognitive radio communications Arulmurugan Ramu1 • Mu-Yen Chen2 • Sri Devi Ravana3 • Anandakumar Haldorai4 Accepted: 9 November 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
The growing devices and capacity requirements of wireless systems bring increasing demand for RF spectrum. Cognitive radio (CR) system is an emerging concept to increase the spectrum efficiency. CR system aims to enable opportunistic usage of the RF bands that are not occupied by their primary licensed users in spectrum overlay approach. This approach is especially important in signal and image processing, where sets of sensors, large and heterogeneous, provide large amounts of data, usually noisy and corrupted with various sources of interference. From a methodological point of view, cognitive communication is concerned with multi-dimensional and statistical signal processing, especially with problems such as detection, estimation, and optimization. In addition to classical sensing, detection, supervised, reinforcement and learning methods include Bayesian modeling, Markov models, support vector machines, and kernel methods. It spans a broad area of applications, such as military, industrial, medical, transportation and other fields like error control, error detection, adaptive filtering, computer vision, managing data, sensor control, data fusion, blind and semiblind source separation, sparse analysis, brain-computer
& Arulmurugan Ramu [email protected] Mu-Yen Chen [email protected] Sri Devi Ravana [email protected] Anandakumar Haldorai [email protected] 1
Presidency University, Bangalore, Karnataka, India
2
National Taichung University of Science and Technology, Taichung, Taiwan
3
University of Malaya, Kuala Lumpur, Malaysia
4
Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India
interfaces, signal processing and radio communication. The intelligent system for the cognitive communication is a collection of intelligent terminals with signal processing and mobile capabilities. Among them, each intelligent terminal carries out signal transmission and distributed processing with other intelligent terminals. However, most existing communication architectures, including their signal processing protocols and control algorithms, are designed for centralized networks by default. This issue aims to gather latest research and development achievements in this area and to promote their applications in all important fields with society needs. This issue features eight selected papers with high quality. The first article, ‘‘Salp Swarm Algorithm and Phasor Measurement Unit Based Hybrid Robust Neural Network Model for Online Monitoring of Voltage Stability’’, presents the online monitoring of voltage stability method. The proposed model is based on Salp Swarm Algorithm based Artificial Neural Network (SSA-ANN). The prime considerations in this model is the use of real time data. The
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