- author = "David Lynch and Michael Fenton and David Fagan and Stepan Kucera and Holger Claussen and Michael O'Neill",
- journal = "IEEE/ACM Transactions on Networking",
- title = "Automated Self-Optimization in Heterogeneous Wireless Communications Networks",
- year = "2019",
- volume = "27",
- number = "1",
- pages = "419--432",
- keywords = "genetic algorithms, genetic programming, Heterogeneous networks, software defined networking, self-organizing networks",
-
URL = "
http://human-competitive.org/sites/default/files/automated_self-optimization_in_heterogeneous_wireless_communications_networks.pdf",
-
DOI = "
doi:10.1109/TNET.2018.2890547",
- ISSN = "1063-6692",
- month = feb,
- abstract = "Traditional single-tiered wireless communications networks cannot scale to satisfy exponentially rising demand. Operators are increasing capacity by densifying their existing macro cell deployments with co-channel small cells. However, cross-tier interference and load balancing issues present new optimization challenges in channel sharing heterogeneous networks (HetNets). One-size-fits-all heuristics for allocating resources are highly suboptimal, but designing ad hoc controllers requires significant human expertise and manual fine-tuning. In this paper, a unified, flexible, and fully automated approach for end-to-end optimization in multi-layer HetNets is presented. A hill climbing algorithm is developed for reconfiguring cells in real time in order to track dynamic traffic patterns. Schedulers for allocating spectrum to user equipment are automatically synthesized using grammar-based genetic programming. The proposed methods for configuring the HetNet and scheduling in the time-frequency domain can address ad hoc objective functions. Thus, the operator can flexibly tune the tradeoff between peak rates and fairness. Far cell edge downlink rates are increased by up to 250percent compared with non-adaptive baselines. Alternatively, peak rates are increased by up to 340percent. The experiments illustrate the utility and future potential of natural computing techniques in software-defined wireless communications networks.",
-
notes = "Gold winner 2019 Humies. Slides:
http://www.human-competitive.org/sites/default/files/lynch_slides-3.pdf
Also known as \cite{8607896}",
