@conference {365,
	title = {Rate adaptation in cognitive radio links with time-varying channels},
	booktitle = {21st European Signal Processing Conference (EUSIPCO)},
	year = {2013},
	month = {September},
	publisher = { European Signal Processing (EURASIP) Society},
	organization = { European Signal Processing (EURASIP) Society},
	address = {Marrakech, Morocco},
	abstract = {In this work we address the optimal rate adaptation problem of a cognitive radio (CR) link in time-variant channels. A secondary user (SU) link detects an idle channel and starts the transmission with the goal of transmitting a given amount of data packets. During the transmission the transmitter dynamically adapts the frames rate, from a finite number of available rates, according to the channel state. If a frame is decoded with error, the corresponding data must be retransmitted in further frames. If a primary user (PU) access the channel during  the process, the CR link immediately stops the transmission.The rate adaptation problem is formulated as an infinite horizon Markov decision process (MDP). We split the problem
in a finite number of much simpler MDP problems that can be efficiently solved by conventional MDP solving algorithms. So, the optimal policy and the corresponding maximum probability of successful transmission can be easily obtained.},
	keywords = {Cognitive radio (CR), Markov decision processes (MDP), rate control},
	isbn = { ISSN 2219-5491},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
@conference {368,
	title = {Model-free Adaptive Rate Selection in Cognitive Radio Links},
	booktitle = {5th International Conference on Mobile Networks and Management (MONAMI)},
	year = {2013},
	month = {September},
	publisher = {Springer-Verlag. LNICST series},
	organization = {Springer-Verlag. LNICST series},
	address = {Cork, Ireland},
	abstract = {In this work we address the rate adaptation problem of a cognitive radio (CR) link in time-variant fading channels. Every time the primary users (PU) liberate the channel the secondary user (SU) selects a transmission rate (from a finite number of available rates) and begins the transmission of fixed sized packets until a licensed user reclaims the channel back. After each transmission episode the number of successfully transmitted packets is used by the SU to update its optimal rate selection ahead of the next episode. The problem is formulated as an n-armed bandit problem and it is solved by means of a Monte Carlo control algorithm.},
	keywords = {Cognitive radio (CR), n-armed bandit problem, rate control, re- inforcement learning (RL)},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
@conference {360,
	title = {Dynamic rate adaptation in cognitive radio considering time-dependent channel access models},
	booktitle = {8th International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM)},
	year = {2013},
	month = {July},
	address = {Washington DC, USA},
	abstract = {Recent studies showed that, in practical situations,
the primary user (PU) access to the channel is better modeled
as a time dependent random process. Taking this into account,
we address the optimal rate adaptation problem of a cognitive
radio (CR) link. A secondary user (SU) link detects an idle
channel and starts the transmission with the goal of transmitting
a given amount of data packets within a given time. During the
transmission, and taking into account frame retransmission, the
transmitter dynamically adapts the frames rate, from a finite
number of available rates. If the PU accesses the channel, the SU
immediately stops the transmission. The problem is formulated
as an episodic Markov decision process (MDP). We show that
selecting the best stationary policy (using the same rate for the
whole transmission) can perform close to optimal.},
	isbn = {978-1-936968-83-1},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
