Embedding and decoding hidden data channels on computer displays

In a given setup, a LCD screen is mounted horizontally so that objects, e.g. game tokens, can be placed on the surface of the display. A PC displays information on the screen, e.g. a floor plan of a board game. The object placed on the screen is equipped with one or more optical sensors that ¿look¿ at the display area under the object. The information captured by the sensor is transmitted back to the PC that displays the information (after optional pre-processing the object). In order to determine de position of the objects in the screen, the screen is partitioned into a large number of separate areas. A separate hidden data channel has to be implemented in each of these areas. The data transmitted through these data channels can be used to transmit position identifying the given area. The task of this work is to research and design a system for implementing such a multitude of hidden data channels on a video display with the following constraints: - The displayed hidden data channel shall be invisible or at least unobtrusive to the human eye in the chosen setup. - The capacity of the channel should be as large as possible. - The system should be able to function if the sensor is placed between two, or three of the hidden data channel areas. - The system needs to be robust against typical error signals like ¿strobing back light of the display¿. - The system should be able to adapt to special conditions found on different types of display families.Querol Giner, AJ. (2009). Embedding and decoding hidden data channels on computer displays. http://hdl.handle.net/10251/21015.Archivo delegad

Cognitive MAC protocols for mobile Ad-Hoc networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased