A cooperative online learning scheme for resource allocation in 5G systems

Ismail Alqerm, Basem Shihada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.
Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Communications (ICC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)9781479966646
DOIs
StatePublished - Jul 26 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

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