Special Issue "Cognitive Radio: Use the Spectrum in a More Efficient Way"

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A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: 15 May 2014

Special Issue Editors

Guest Editor
Dr. Sanqing Hu
Stevens Institute of Technology, Hoboken, NJ 07030, USA
E-Mail: shu1@stevens.edu
Interests: cognitive radio; MAC protocols; cellular networks; machine learning

Guest Editor
Dr. Lian Zhao
Electrical and Computer Engineering Department, Ryerson University, 350 Victoria St., Toronto, Canada M5B 2K3
Website: http://www.ee.ryerson.ca/~lzhao/
E-Mail: lzhao@ee.ryerson.ca
Phone: (416) 979-5000 Ext. 6101, Fax: (416) 979-5280
Interests: wireless communications, radio resource management for complicated systems; cooperative and cognitive systems; green communication and smart grid technologies; cross-layer resource optimization

Guest Editor
Dr. Nazanin Rahnavard
Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA
Website: http://eecs.ucf.edu/~nazanin/
E-Mail: nazanin@eecs.ucf.edu
Interests: cognitive radio networks; wireless ad-hoc and sensor networks; compressive sensing: new designs and applications; modern channel coding techniques and their applications

Special Issue Information

Dear Colleagues,

The emergence and development of new wireless communication systems leads to a significant increase in the demand for radio resources, resulting in a spectrum shortage. Meanwhile, according to the Federal Communications Commission records, a large portion of the spectrum resources allocated to licensed network users are underutilized. Cognitive radio (CR) is a promising technology to mitigate the spectrum scarcity issue because it helps wireless communication systems to utilize the spectrum in a dynamic and more efficient way. In the CR paradigm, cognitive radio users are allowed to access the frequency bands that have been allocated to licensed network users but are not used at a particular time. Therefore, the cognitive radio users should have the ability to locate and utilize the unused frequency bands, and meanwhile be aware of the existence of the licensed users when they are occupying the spectrum. Currently, there are still a lot of technical as well as economic challenges that need to be addressed before the full deployment of cognitive radio.

This Special Issue is intended to present novel and high-quality research papers and reviews in the field of cognitive radio.

Dr. Sanqing Hu
Dr. Lian Zhao
Dr. Nazanin Rahnavard
Guest Editors

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Keywords

  • spectrum sensing and measurements
  • medium access control design for cognitive radio networks
  • physical layer design of cognitive radio networks
  • artificial intelligence and machine learning for cognitive radio networks
  • MIMO, OFDM in cognitive radio
  • resource allocation, game theory in cognitive radio
  • dynamic spectrum access
  • cognitive radio in cellular networks
  • spectrum sharing, mobility management, QoS
  • cross-layer design for cognitive radio networks
  • cognitive radio network security
  • DSP for cognitive radio
  • standards and testbed
  • compressive sensing for cognitive radio networks

Published Papers

No papers have been published in this special issue yet, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Type of Paper: Article
Title: Dynamic Optimal Radio Resource Allocation for MIMO MAC in Cognitive Radio Networks
Authors: Peter He and Lian Zhao
Affiliation: Dept. of Electrical and Computer Engineering, Ryerson University, Ontario, Canada, M5B 2K3
Abstract: This paper considers a cognitive radio (CR) network, in which the unlicensed (secondary) users (SUs) are allowed to concurrently access the spectrum allocated to the licensed (primary) users provided that their interference to the primary users (PUs) satisfies certain constraints. The SUs are equipped with multiple antennas, thus referred as multiple input multiple output multiple access channels (MIMO-MAC) in the CR Networks.  With the requirement to satisfy the quality of service (QoS) of the PUs, the precious spectrum resource can be utilized by the SUs with objectives to maximizing the sum-rate and optimizing power allocation. To effectively and efficiently optimize the power allocation of the SUs, a tight pair of upper and lower bounds, as an interval, of the optimal Lagrange multiplier is proposed. Furthermore, a novel water-filling is proposed for the inner loop computation of the proposed problem. It is shown that the new water-filling can obtain the exact solution with finite iterations. Convergence proof of the proposed algorithm is also presented.

Type of Paper: Article
Title: Efficient Optimal Power Allocation using H-infinity Method for OFDM Cognitive Radio Networks
Authors: Peter He and Lian Zhao
Affiliation: Dept. of Electrical and Computer Engineering, Ryerson University, Ontario, Canada, M5B 2K3
Abstract: This paper considers an OFDM cognitive radio (CR) network, in which the unlicensed (secondary) users (SUs) are allowed to concurrently access the spectrum allocated to the licensed (primary) users provided that their interference to the primary users (PUs) satisfies certain constraints. To achieve fair radio resource allocation, the advanced H-infinity optimization method is used. The objective of the target problem is to minimize the H-infinity norm of the rate vector through the optimization of power allocation of the SUs. Novel algorithm with water-filling and its convergence proof are presented to obtain optimal solutions. Numerical results are presented to verify the efficiency of the proposed algorithm.

Type of Paper: Article
Title: Performance Analysis of Multiple-Primary User Cognitive Radio Networks over Nakagami-m Fading Channels
Authors: Sattar Hussain and Xavier Fernando
Affiliation:
Ryerson Communications Lab, Dept. of Electrical and Computer Eng., Ryerson University, 350 Victoria Street, Toronto, ON M5B 2KC, Canada
Abstract: Improving spectrum efficiency through cognitive radio technology has been investigated thoroughly in the last few years. However, the majority of the works consider a single-primary user model which may not be realistic. In this paper, we investigate a performance analysis of multiple-primary user cognitive radio (MPUCR) networks over the most general Nakagami-m fading channels. An advanced statistical approach is used to derive exact closed-form expressions for average false alarm probability and detection probability and a detailed performance analysis is done  in terms of network size, number of samples, number of primary users, and the SNR.

Last update: 23 January 2014

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