Analyzing and optimizing performance of In Vivo network operating at THz band

Abstract

Tiny devices implanted inside a living body and communicating wirelessly with one another form an In Vivo network. Integration of In Vivo sensors with Internet of things (IoT) has opened a doorway for revolutionary healthcare possibilities. To make an In Vivo network more reliable and faster, a more sophisticated communication link is required. For these communication requirements, the Terahertz (THz) band owing to its large available bandwidth and non-ionizing effect looks promising for In Vivo applications. The challenge faced by terahertz band In Vivo network is that the signal transmitted in this band undergoes absorption and dispersion losses. These losses reduce the capacity of the channel. In this work, effect of pathloss on In Vivo channels for skin, water, whole blood, plasma, and red blood cells (RBCs) has been performed and its effect on channel capacity is computed. The results from the proposed model simulation show that channel capacity is minimum in RBCs as compared to water, whole blood and skin. Further using the optimization technique, the optimum value of channel capacity is being computed and contrasted for both Artificial neural network (ANN) & Genetic Algorithm (GA).