Learn More
Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in [1] a(More)
Compressed sensing is triggering a major evolution in signal acquisition. It consists in sampling a sparse signal at low rate and later using computational power for its exact reconstruction, so that only the necessary information is measured. Currently used reconstruction techniques are, however, limited to acquisition rates larger than the true density of(More)
—Unexpected disasters, both naturally occurring and those caused through human actions, result in severe damage to communication infrastructure. Additionally, such events are accompanied by sharp spikes in the usage of commercially licensed spectrum, when affected victims of the tragedy attempt to transmit information about themselves and capture high(More)
Decomposition techniques for linear programming are difficult to extend to conic optimization problems with general nonpolyhedral convex cones because the conic inequalities introduce an additional nonlinear coupling between the variables. However in many applications the convex cones have a partially separable structure that allows them to be characterized(More)
Recent underwater sensor network research has focused on developing physical, medium access control, and network layer protocols to enable high data rate, energy-efficient and reliable acoustic communications. However, it is now essential to design and standardize architectures that will enhance the usability and interoperability of underwater networks. (More)
We propose a novel optimal time slot allocation scheme for clustered underwater acoustic sensor networks that leverages physical (PHY) layer information to minimize the energy consumption due to unnecessary retransmissions thereby improving network lifetime and throughput. To reduce the overhead and the computational complexity, we employ a two-phase(More)
This study reports an experimental realization of non-local classical optical correlation from the Bell's measurement used in tests of quantum non-locality. Based on such a classical Einstein-Podolsky-Rosen optical correlation, a classical analogy has been implemented to the true meaning of quantum teleportation. In the experimental teleportation protocol,(More)