Energy Detection Based Spectrum Sensing Over k-μ and k-μ Extreme Fading Channels

Energy detection (ED) is a simple and popular method of spectrum sensing in cognitive radio systems. It is also widely known that the performance of sensing techniques is largely affected when users experience fading effects. This paper investigates the performance of an energy detector over generalized κ-μ and κ- μ extreme fading channels, which have been shown to provide remarkably accurate fading characterization. Novel analytic expressions are firstly derived for the corresponding average probability of detection for the case of single-user detection. These results are subsequently extended to the case of square-law selection (SLS) diversity and for collaborative detection scenarios. As expected, the performance of the detector is highly dependent upon the severity of fading since even small variations of the fading conditions affect significantly the value of the average probability of detection. Furthermore, the performance of the detector improves substantially as the number of branches or collaborating users increase in both severe and moderate fading conditions, whereas it is shown that the κ- μ extreme model is capable of accounting for fading variations even at low signal-to-noise values. The offered results are particularly useful in assessing the effect of fading in ED-based cognitive radio communication systems; therefore, they can be used in quantifying the associated tradeoffs between sensing performance and energy efficiency in cognitive radio networks.

Selective reporting: a half signalling load algorithm for distributed sensing

Spectrum sensing is a powerful tool of the cognitive cycle to help circumvent the apparent spectrum scarcity faced by wireless transmission systems. To overcome the challenging issues faced by the localized sensing, multiple cognitive radios can cooperate to explore the multiuser diversity and generate a more reliable decision on the presence of a signal in the frequencies of interest. In such a cooperative sensing scenario, a common reporting channel is needed for the transmission of the information of each element. As the number of elements that participate in the sensing operation increases, so does the bandwidth demanded for the reporting channel, quickly becoming the limiting factor in this scenario. To tackle the issue of reducing the sensing report overhead, this paper introduces a new cooperative sensing scheme that introduces silence periods in the reporting and, relying on information theory principles, explores the information present in these periods to reduce by 50% the sensing reporting overhead while maintaining the same performance of standard reporting schemes. Numerical and experimental results confirm the theoretical analysis and show the predicted reduction in reporting overhead and performance preservation

The Use of Biomaterials in Islet Transplantation

Pancreatic islet transplantation is a therapeutic option to replace destroyed β cells in autoimmune diabetes. Islets are transplanted into the liver via the portal vein; however, inflammation, the required immunosuppression, and lack of vasculature decrease early islet viability and function. Therefore, the use of accessory therapy and biomaterials to protect islets and improve islet function has definite therapeutic potential. Here we review the application of niche accessory cells and factors, as well as the use of biomaterials as carriers or capsules, for pancreatic islet transplantation

Neural adaptations to electrical stimulation strength training

This review provides evidence for the hypothesis that electrostimulation strength training (EST) increases the force of a maximal voluntary contraction (MVC) through neural adaptations in healthy skeletal muscle. Although electrical stimulation and voluntary effort activate muscle differently, there is substantial evidence to suggest that EST modifies the excitability of specific neural paths and such adaptations contribute to the increases in MVC force. Similar to strength training with voluntary contractions, EST increases MVC force after only a few sessions with some changes in muscle biochemistry but without overt muscle hypertrophy. There is some mixed evidence for spinal neural adaptations in the form of an increase in the amplitude of the interpolated twitch and in the amplitude of the volitional wave, with less evidence for changes in spinal excitability. Cross-sectional and exercise studies also suggest that the barrage of sensory and nociceptive inputs acts at the cortical level and can modify the motor cortical output and interhemispheric paths. The data suggest that neural adaptations mediate initial increases in MVC force after short-term EST