Applications of model-free learning in wireless networks
| dc.contributor.author | Cao, Huijin | |
| dc.contributor.examiningcommittee | Alfa, Attahiru (Electrical and Computer Engineering) Peng, Qingjin (Mechanical Engineering) Wong, Vincent (Electrical and Computer Engineering, The University of British Columbia) | en_US |
| dc.contributor.supervisor | Cai, Jun (Electrical and Computer Engineering) | en_US |
| dc.date.accessioned | 2018-09-12T20:10:23Z | |
| dc.date.available | 2018-09-12T20:10:23Z | |
| dc.date.issued | 2018-08-20 | en_US |
| dc.date.submitted | 2018-08-20T23:39:04Z | en |
| dc.degree.discipline | Electrical and Computer Engineering | en_US |
| dc.degree.level | Doctor of Philosophy (Ph.D.) | en_US |
| dc.description.abstract | When wireless decision-making entities have complete information, the network control problems are frequently addressed in the model-based paradigm. However, due to the practical limitation of information incompleteness/locality, directly applying the model-based solutions will face difficulties. As a result, the method of controlling-by-learning without the need for the a priori network model, namely, the model-free learning, has been considered as one promising implementation approach to wireless networks. In this thesis, the applications of the model-free learning in three networks with different characteristics and objectives are investigated, they are an opportunistic spectrum access (OSA) network, a cloudlet-based mobile cloud computing (MCC) network, and an energy harvesting based network. Effective and efficient model-free learning mechanisms in these networks are aimed to be designed. Both analytical and numerical results validate the efficacy of the proposed algorithms. | en_US |
| dc.description.note | October 2018 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/33335 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Cognitive radio networks | en_US |
| dc.subject | Opportunistic spectrum access | en_US |
| dc.subject | Nash equilibrium | en_US |
| dc.subject | Stochastic learning automata | en_US |
| dc.subject | Cloudlet-based mobile cloud computing | en_US |
| dc.subject | Energy harvesting | en_US |
| dc.subject | Proactive caching | en_US |
| dc.subject | Post-decision state | en_US |
| dc.subject | Approximate reinforcement learning | en_US |
| dc.subject | Markov decision process | en_US |
| dc.title | Applications of model-free learning in wireless networks | en_US |
| dc.type | doctoral thesis | en_US |