Sensing time and power allocation for cognitive radios using distributed Q-learning

Sensing time and power allocation for cognitive radios using distributed Q-learning

In cognitive radios systems, the sparse assigned frequency bands are opened to secondary users, provided that the aggregated interferences induced by the secondary transmitters on the primary receivers are negligible. Cognitive radios are established in two steps: the radios firstly sense the available frequency bands and secondly communicate using these bands. In this article, we propose two d...

Spectrum Sensing in Cognitive Radios using Distributed Sequential Detection

Cognitive Radios are emerging communication systems which efficiently utilise the unused licensed radio spectrum called spectral holes. They run Spectrum sensing algorithms to identify these spectral holes. These holes need to be identified at very low SNR (≤ −20 dB) under multipath fading, unknown channel gains and noise power. Cooperative spectrum sensing which exploits spatial diversity has ...

Machine Learning-aided, Robust Wideband Spectrum Sensing for Cognitive Radios

Channel Allocation in Cognitive Radios

In this project we investigate the problem of channel allocation to a set of users in a centralized Cognitive Radio System. We consider three possible formulations of the problem and explain the relationship of these constraints to physical limiting factors. In the first formulation, we aim to minimize total power used in the system while fulfilling user rate requirements. This problem can be s...

Adaptive Bandwidth Allocation Scheme for Cognitive Radios

In recent past, cognitive radio has come out to as a promising solution to the spectrum scarcity problem. It tends to increase the spectrum utilization by making use of underutilized frequencies with the help of dynamic spectrum allocation technique. In this paper, we present one such scheme for bandwidth allocation to cognitive radio. Our proposal helps the channel distributor to decide the qu...