34,183 research outputs found
Compressed Genotyping
Significant volumes of knowledge have been accumulated in recent years
linking subtle genetic variations to a wide variety of medical disorders from
Cystic Fibrosis to mental retardation. Nevertheless, there are still great
challenges in applying this knowledge routinely in the clinic, largely due to
the relatively tedious and expensive process of DNA sequencing. Since the
genetic polymorphisms that underlie these disorders are relatively rare in the
human population, the presence or absence of a disease-linked polymorphism can
be thought of as a sparse signal. Using methods and ideas from compressed
sensing and group testing, we have developed a cost-effective genotyping
protocol. In particular, we have adapted our scheme to a recently developed
class of high throughput DNA sequencing technologies, and assembled a
mathematical framework that has some important distinctions from 'traditional'
compressed sensing ideas in order to address different biological and technical
constraints.Comment: Submitted to IEEE Transaction on Information Theory - Special Issue
on Molecular Biology and Neuroscienc
Collaborative spectrum sensing optimisation algorithms for cognitive radio networks
The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance
Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks
In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones
Cognitive Radio for Emergency Networks
In the scope of the Adaptive Ad-hoc Freeband (AAF) project, an emergency network built on top of Cognitive Radio is proposed to alleviate the spectrum shortage problem which is the major limitation for emergency networks. Cognitive
Radio has been proposed as a promising technology to solve
todayâ?~B??~D?s spectrum scarcity problem by allowing a secondary user in the non-used parts of the spectrum that aactully are assigned to primary services. Cognitive Radio has to work in different frequency bands and various wireless channels and supports multimedia services. A heterogenous reconfigurable System-on-Chip (SoC) architecture is proposed to enable the evolution from the traditional software defined radio to Cognitive Radio
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