A cooperative online learning scheme for resource allocation in 5G systems
Type
Conference PaperAuthors
Alqerm, Ismail
Shihada, Basem

KAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2016-07-26Online Publication Date
2016-07-26Print Publication Date
2016-05Permanent link to this record
http://hdl.handle.net/10754/621298
Metadata
Show full item recordAbstract
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.Citation
AlQerm I, Shihada B (2016) A cooperative online learning scheme for resource allocation in 5G systems. 2016 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2016.7511617.Conference/Event name
2016 IEEE International Conference on Communications, ICC 2016Additional Links
http://www.shihada.com/node/publications/5GlearningICC.pdfhttp://ieeexplore.ieee.org/document/7511617/
ae974a485f413a2113503eed53cd6c53
10.1109/ICC.2016.7511617