Browsing School of Engineering by Author "MACALUSO, IRENE"
Now showing items 1-6 of 6
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Carrier Aggregation as a Repeated Game: Learning Algorithms for Efficient Convergence to a Nash Equilibrium
DA SILVA, LUIZ; MACALUSO, IRENE (2013)Carrier aggregation is a key feature of next generation wireless networks to deliver high-bandwidth links. This paper studies carrier aggregation for au- tonomous networks operating in shared spectrum. In our model, ... -
Complexity of Spectrum Activity and Benefits of Learning for Dynamic Channel Selection
DA SILVA, LUIZ; MACALUSO, IRENE (2013)We explore the question of when learning improves the performance of opportunistic dynamic channel selection by characterizing the primary user (PU) activity using the concept of Lempel-Ziv complexity. We evaluate the ... -
The effect of the spectrum opportunities diversity on opportunistic access
DA SILVA, LUIZ; AHMADI, HAMED; MACALUSO, IRENE (IEEE, 2013)To improve their ability to find spectrum oppor- tunities, intelligent secondary radios (SR) can learn from their past observations and predict possible spectrum opportunities. However, because of the diverse behavior ... -
Exclusive Sharing & Virtualization of the Cellular Network
FORDE, TIM; DOYLE, LINDA; MACALUSO, IRENE (IEEE, 2011)The focus of this paper is to progress a discussion about the redefinition of what it means to be a cellular network operator. Alternative modes of ownership may allow for the creation of more flexible cellular networking ... -
Learning and Reasoning in Cognitive Radio Networks
DA SILVA, LUIZ; MACALUSO, IRENE (2013)Cognitive radio networks challenge the traditional wireless networking paradigm by introducing concepts firmly stemmed into the Artificial Intelligence (AI) field, i.e., learning and reasoning. This fosters optimal resource ... -
Learning Nash Equilibria in Distributed Channel Selection for Frequency-Agile Radios
DA SILVA, LUIZ; DOYLE, LINDA; MACALUSO, IRENE (2012)Wireless communication networks are evolving towards self- configuring, autonomous and distributed multiagent systems in which nodes are deployed randomly and have to adapt to the en- vironment in which they operate. A ...