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Imperfect CSI based intelligent dynamic spectrum management using cooperative reinforcement learning framework in cognitive radio networks
The rapid development of wireless traffic pushed the wireless community to research
different solutions towards the efficient utilization of the available radio spectrum. However, a …
different solutions towards the efficient utilization of the available radio spectrum. However, a …
AutoODC: Automated generation of orthogonal defect classifications
Orthogonal defect classification (ODC), the most influential framework for software defect
classification and analysis, provides valuable in-process feedback to system development …
classification and analysis, provides valuable in-process feedback to system development …
A reinforcement learning-based green resource allocation for heterogeneous services in cooperative cognitive radio networks
The explosive growth of heterogeneous mobile data traffic with stringent Quality of Service
(QoS) requirements put significant pressure on the existing network infrastructure and also …
(QoS) requirements put significant pressure on the existing network infrastructure and also …
Cooperative radar and communications coexistence using reinforcement learning
The growing population of radar and communications systems poses a challenge to spectral
coexistence. In this preliminary study, we investigate the utility of reinforcement learning in …
coexistence. In this preliminary study, we investigate the utility of reinforcement learning in …
Distributed Q-learning based dynamic spectrum management in cognitive cellular systems: Choosing the right learning rate
This paper presents the concept of the Win-or-Learn-Fast (WoLF) variable learning rate for
distributed Q-learning based dynamic spectrum management algorithms. It demonstrates …
distributed Q-learning based dynamic spectrum management algorithms. It demonstrates …
An aggregation approach for solving the non-linear fractional equality knapsack problem
In this paper, we present an optimal, efficient and yet simple solution to a class of the
deterministic non-linear fractional equality knapsack (NEFK) problem—a substantial …
deterministic non-linear fractional equality knapsack (NEFK) problem—a substantial …
Accelerating reinforcement learning for dynamic spectrum access in cognitive wireless networks
N Morozs - 2015 - etheses.whiterose.ac.uk
This thesis studies the applications of distributed reinforcement learning (RL) based
machine intelligence to dynamic spectrum access (DSA) in future cognitive wireless …
machine intelligence to dynamic spectrum access (DSA) in future cognitive wireless …
Mobility-prediction based proactive edge caching in vehicular networks
Q Wang - 2022 - etheses.whiterose.ac.uk
This thesis studies and designs machine intelligence based mobility-prediction algorithms to
address the proactive edge caching problem in vehicular networks. In particular, the thesis …
address the proactive edge caching problem in vehicular networks. In particular, the thesis …
A hybrid proactive caching system in vehicular networks based on contextual multi-armed bandit learning
Proactive edge caching has been regarded as an effective approach to satisfy user
experience in mobile networks by providing seamless content transmission and reducing …
experience in mobile networks by providing seamless content transmission and reducing …
Interval fuzzy sliding-mode formation controller design
This paper focuses on the design of a formation controller for multi-robot dynamic systems
using interval fuzzy sliding-mode algorithm. The objective of formation control is to have all …
using interval fuzzy sliding-mode algorithm. The objective of formation control is to have all …