An Intelligent cognitive sensing and detection strategy for medical telemetry networks

Abstract

In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in development of smart hospitals and smart cities. In medical telemetry networks frequency spectrum concept is used for providing treatment to patients who are far away from hospitals. In cognitive radios, spectrum sensing concept is used in which energy detection method is mostly used because it is simple to implement. While measuring health care environments using cognitive radios probability detection, false alarm probability and threshold parameters are calculated. In this paper for identifying spectrum holes in spectrum sensing using energy detection, distributed diffusion non-negative least mean square algorithm is proposed. It gives better results compared to energy detection concept alone in terms of probability detection converged earlier. If number of nodes are increasing probability detection is decreased from one and move towards left and its SNR is around 1.5-2 dB with proposed method. Hence simulation results give better results in terms of sensing ability while measuring patient condition.