Control-Data Separation Architecture for Dual-Band mmWave Networks: A New Dimension to Spectrum Management

Ansari, Rafay, Pervaiz, Haris, Chrysostomou, Chrysostomos, Hassan, Syed Ali, Mahmood, Aamir and Gidlund, Mikael (2019) Control-Data Separation Architecture for Dual-Band mmWave Networks: A New Dimension to Spectrum Management. IEEE Access, 7. pp. 34925-34937. ISSN 2169-3536

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Official URL: https://doi.org/10.1109/access.2019.2903901

Abstract

The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this paper, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band, and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this paper includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.

Item Type: Article
Uncontrolled Keywords: Control-data separation architecture, resource allocation, dual-band millimeter wave, energy efficiency, spectral efficiency, multi-objective optimization.
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 05 Oct 2020 09:08
Last Modified: 05 Oct 2020 09:15
URI: http://nrl.northumbria.ac.uk/id/eprint/44393

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