Computationally intelligent techniques for resource management in mmWave small cell networks

Muir, H., Pervaiz, H., Hassan, S. A., Musavian, L., Ni, Q., Imran, M. A. and Tafazolli, R. (2018) Computationally intelligent techniques for resource management in mmWave small cell networks. IEEE Wireless Communications, 25(4), pp. 32-39. (doi: 10.1109/MWC.2018.1700400)

Abstract

Ultra densification in HetNets and the advent of mmWave technology for 5G networks have led researchers to redesign the existing resource management techniques. A salient feature of this activity is to accentuate the importance of CI resource allocation schemes offering less complexity and overhead. This article overviews the existing literature on resource management in mmWave-based Het- Nets with a special emphasis on CI techniques and further proposes frameworks that ensure quality of service requirements for all network entities. More specifically, HetNets with mmWave-based small cells pose different challenges compared to an all-microwave- based system. Similarly, various modes of small cell access policies and operations of base stations in dual mode, that is, operating both mmWave and microwave links simultaneously, offer unique challenges to resource allocation. Furthermore, the use of multi-slope path loss models becomes inevitable for analysis due to irregular cell patterns and blocking characteristics of mmWave communications. This article amalgamates the unique challenges posed because of the aforementioned recent developments and proposes various CI-based techniques, including game theory and optimization routines, to perform efficient resource management.

• Item Type: Articles
• Additional Information: This work was supported in part through ESPRC UK Global Challenges Research Fund (GCRF) allocation under grant number EP/P028764/1.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad
• Authors: Muir, H., Pervaiz, H., Hassan, S. A., Musavian, L., Ni, Q., Imran, M. A., and Tafazolli, R.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Wireless Communications
• Publisher: Institute of Electrical and Electronics Engineers
• ISSN: 1536-1284
• ISSN (Online): 1558-0687
• Copyright Holders: Copyright © 2018 IEEE
• First Published: First published in IEEE Wireless Communications 25(4):32-39
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher