Submission Deadline: 31 January 2018
IEEE Access invites manuscript submissions in the area of Recent Advances in Cloud and Big Data-based Next-generation Cognitive Radio Networks.
In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to the complicated data processing, non-real-time information exchange and limited memory, SUs often suffer from the imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the resource allocation and interference management at the cloud center while relieving the stringent capacity demands in fronthaul links. Moreover, spectrum resources should be made available to more users, especially when the spectrum is underutilized but occupies a large band. Hence, cloud-based CRN can generate massive sensing samples that will benefit the applications of big data algorithms. The approaches to spectrum sensing and spectrum management can be greatly improved with decision making capabilities of spectral big data.
To integrate cloud and big data in CRN and to support high quality transmission, many challenges need to be addressed, such as cloud-based CRN, cloud-based spectrum management, big data-based spectrum sensing. This Special Section in IEEE Access will bring together leading researchers and developers from both industry and academia to discuss and present their views on all aspects of cloud and big data-based CRN.
The topics of interest include, but are not limited to:
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Associate Editor: Nan Zhao, Dalian University of Technology, China
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IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland
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