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      • Department of Electrical and Electronics Engineering
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      Generalized global bandit and its application in cellular coverage optimization

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      Author
      Shen, C.
      Zhou, R.
      Tekin, C.
      Schaar, M. V. D.
      Date
      2018
      Source Title
      IEEE Journal on Selected Topics in Signal Processing
      Print ISSN
      1932-4553
      Publisher
      Institute of Electrical and Electronics Engineers
      Volume
      12
      Issue
      1
      Pages
      218 - 232
      Language
      English
      Type
      Article
      Item Usage Stats
      136
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      149
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      Abstract
      Motivated by the engineering problem of cellular coverage optimization, we propose a novel multiarmed bandit model called generalized global bandit. We develop a series of greedy algorithms that have the capability to handle nonmonotonic but decomposable reward functions, multidimensional global parameters, and switching costs. The proposed algorithms are rigorously analyzed under the multiarmed bandit framework, where we show that they achieve bounded regret, and hence, they are guaranteed to converge to the optimal arm in finite time. The algorithms are then applied to the cellular coverage optimization problem to achieve the optimal tradeoff between sufficient small cell coverage and limited macroleakage without prior knowledge of the deployment environment. The performance advantage of the new algorithms over existing bandits solutions is revealed analytically and further confirmed via numerical simulations. The key element behind the performance improvement is a more efficient 'trial and error' mechanism, in which any trial will help improve the knowledge of all candidate power levels.
      Keywords
      Coverage optimization
      Multi-armed bandit
      Online learning
      Regret analysis
      Permalink
      http://hdl.handle.net/11693/50198
      Published Version (Please cite this version)
      https://doi.org/10.1109/JSTSP.2018.2798164
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      • Department of Electrical and Electronics Engineering 3650
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