Results from a thorough literature survey indicate that the information theoretic distance gls divergence is promising when trying to devise a novel cognitive radio spectrum sensing scheme.
Cognitive radio (CR) is proposed as a promising technology to increase the efficiency of spectrum usage by introducing secondary (unlicensed) users to opportunistically or concurrently access the spectrum allocated to primary (licensed) users.
Baishya, "A Comprehensive Analysis of Spectrum Handoff under Different Distribution Models for Cognitive Radio Networks," Wireless Personal Communications, vol.
Gupta, Thesis Title: Modeling and Simulation of Multi-Gate Multi-Material Transistors, 2013; (2) Brinda Shome (Bhowmick), Thesis Title: Modeling and Simulation of Hetero-gate Dielectric Tunnel FET Structures and Their Mixed-mode Applications, 2014; (3) Niladri Pratap Maity, Thesis Title: Tunneling Current and Interface Charge Densities in Ultra-Thin High-k Dielectric Materials Based MOS Devices, 2015; (4) Wasim Arif, Thesis Title: Investigation and modeling of spectrum sensing and mobility issues in cognitive radio, 2015; (5) Reshmi Maity, Thesis Title: Modeling and Simulation of Capacitive Micromachined Ultrasonic Transducers, 2015; (6) Koushik Guha, Thesis Title: Design and Modeling of RF MEMS Shunt Switch, 2015; (7) Sweta Chander, Thesis Title: Investigation of Heterojunction Silicon-on-Insulator Tunnel Field Effect Transistor in Nanometer Era, 2016; (8) Richik Kashyap, “Distributed Parameter Modeling and Autonomous Charge Extraction of d31 and d33 Mode Piezoelectric Energy Harvesters,” 2016; (9) Achinta Baidya, Thesis Title: Circuit Performance Analysis of Double Gate Junctionless Transistor with High-k Dielectrics and Metal Gates,” 2017
This thesis studies the designs of cooperative spectrum sensing schemes and exploits the spectrum sensing information to improve the performance of the cognitive radio networks (CRNs) in various scenarios.
Spectrum scarcity is one of the biggest challenges that the currentwireless sensor network is facing. With the exciting progress of wirelesssensor network (WSN) within 5 to 10 years, the world will be full of low power wireless sensor devices. Due to the independent design and development, together with the unexpected dynamics during deployment of co-existing networks and devices, the limited frequency spectrum will be extremely crowded. To address this challenge, cognitive radio has emerged as the key technology, which enables opportunistic access to the spectrum.
Ramzi Saifan, Ahmed Kamal, and Yong Guan, "Efficient Spectrum Searching and Monitoring in Cognitive Radio Network", in the Proceedings of the 8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2011), Valencia, Spain, October 17-22, 2011.
In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities.
In this paper one of the spectrum sensing method Energy detection is implemented in MATLAB to determine the availability of vacant spectrum of licensed band. The straight forward method for detecting unknown signals is energy detection. When primary user is assumed to be unknown to the secondary receiver’s detector, it will become an energy detector, also referred to as radiometers. The energy of a received wave form can be measured by squaring the output of band pass filter with a bandwidth W, and then integrating the received power over a time interval T. The output of the integrator is compared with a predefined threshold to determine presence or absence of primary user.
Cognitive radio(CR) based systems and networks are a revolutionary new concept in wireless communications, designed to meet the challenges posed by the proliferation of wireless multimedia applications, which have led to a tremendous increase in the demand for higher data rates in current and upcoming 4G/5G wireless communication systems. The cognitive radio paradigm allows a set of unlicensed/ secondary users to opportunistically access unused spectrum bands licensed to primary users, thus radically improving the efficiency of spectrum usage. These networks can dynamically allocate spectrum to multiple users, thereby easing network congestion.
Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends.
Cognitive radio devices require powerful signal processing capabilities to sense the presence of vacant spectral bands, termed as spectral holes or white spaces. Coupled together with cutting edge wireless technologies such as MIMO-OFDM, cognitive radio technology can meet the growing wireless broadband demands of billions of users worldwide by efficiently utilizing spectrum resources in wireless networks, which are scarce and expensive.
CR is a cutting edge technology for wireless communications and requires the design of novel spectrum sensing schemes which have a high degree of reliability, even at low SNR. This course will comprehensively cover several different aspects of spectrum sensing for CR systems, especially based on MIMO-OFDM technology. Starting from a basic introduction to CR networks and MIMO-OFDM based Physical Layer (PHY) design, the various modules will provide elaborate knowledge of various Spectrum Sensing techniques such as Matched Filtering, Energy Detection, Cooperative Sensing, Eigenvalue-based Sensing, Cyclostationary Sensing and several others. All the classes will be conducted in classroom style towards building up the various theoretical aspects beginning with the fundamentals, together with problem solving sessions to further enhance and consolidate understanding. Also, an interactive MATLAB/ SIMULINK module will introduce the participants to the practical implementation and simulation aspects of spectrum sensing especially for MIMO-OFDM systems. A one-day mini-project will also be conducted (on 24th April, 2017), for interested participants, to provide hands-on training on the latest in MIMO-OFDM cognitive radio research.