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Reliability, interoperability and efficiency are fundamental in Wireless Sensor Network deployment. Herein we look at how transmission power control may be used to reduce interference, which is particularly problematic in high-density conditions. We adopt a distributed approach where every node has the ability to learn which transmission power is most appropriate, given the network conditions and...
This paper investigates enhanced Inter-Cell Interference Coordination (eICIC) techniques for Heterogeneous Networks (HetNets), and models this strategic coexistence as a multi-player system in which interference management strategies inspired from a form of reinforcement learning known as distributed Q-learning are devised. Specifically, this paper focuses on time domain eICIC techniques in which...
In cellular networks, balancing the throughput among users is important to achieve a uniform Quality-of-Service (QoS). This can be accomplished using a variety of cross-layer techniques. In this paper, the authors investigate how the down-tilt of basestation (BS) antennas can be adjusted to maximize the user throughput fairness in a heterogeneous network, considering the impact of both a dynamic user...
As the scarce spectrum resource is becoming overcrowded, cognitive wireless mesh networks express great flexibility to improve the spectrum utilization by opportunistically accessing the authorized frequency bands. One of the critical challenges for realizing such networks is how to adaptively match transmit powers and allocate frequency resources among secondary users (SUs) of the licensed frequency...
Dynamic channel selection is an important component of multi-channel wireless systems. It allows a transmitter to identify the channel offering the best radio conditions and to avoid interference created by other transmitters. In absence of interference, the channel selection problem can be simply interpreted as a Multi-Armed Bandit problem for which low-regret learning algorithms such as Exp3 have...
This paper proposes a self-organized spectrum assignment strategy in the context of next generation multicell orthogonal frequency division multiple access networks. The proposed strategy is able to dynamically find spectrum assignments per cell depending on the spatial distribution of the users over the scenario, opening new spectrum access opportunities for secondary spectrum usage. Reinforcement...
This paper proposes a dynamic spectrum assignment strategy in the context of next generation multicell orthogonal frequency division multiple access networks. The proposed strategy is able to dynamically find spectrum assignments per cell depending on the spatial and temporal distribution of the users over the scenario. Reinforcement learning methodology has been employed to implement the strategy,...
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