Abstract
Nanotechnology enables the creation of novel devices which can produce, process content transmission for multimedia on a nanoscale basis. The link of broadly distributed multimedia nano-systems through current communication networks and eventually the Internet describes a novel communication model that is often the Internet of Multimedia Nano-Things (IoMNT). The IoMNT is a completely cyber-physical device having a large variety of applications in biomedical, security and safety areas of the environment and business, among others. In this project a modulation technique targeting body-centric network is explored. An analogy of real THz antenna is developed within a terahertz multi-layer modeling channel for a human skin tissue. As a result, the investigation of how signals at THz frequency band interact and transmit within the skin biomaterial. The project model is based on theoretical equations that describe electromagnetic propagation in a dielectric medium, and the electromagnetic characteristics of human tissue were gathered from various sources. The model has been carried out in an easy to work around package MATLAB that can be used in simulation on number of layers from a library either with fixed or randomly set depths. The human skin model used to collect data was selected to have four layers: epidermis, dermis, blood, and hypodermis, with the depth of the layers varying between normal human body values. This multi-layer channel model based on MATLAB is validated. The MATLAB program's results revealed that frequency and content have a substantial impact on path failure. The estimated path loss could thus differ considerably, but for a human skin model with depths of 0.21 mm, 1.23 mm, 1.38 mm, and 3.76 mm, the frequencies of 0.5-1.5 THz at the end distance resulted in a path loss estimated about 250-350 dB. Lastly, the numerical analysis is performed within ten data sets produced from the multi-layer channel model to establish a basic interpolation equation capable of describing path loss via varying tissue layer depths of a human skin. Against 90 individual random data sets, the average mean error of 4.08 % and a cumulative mean error of 6.61% were attained as a result of equation used.