Mathematical modeling of ultra wideband in vivo radio channel

This paper proposes a novel mathematical model for an in vivo radio channel at ultra-wideband frequencies (3.1–10.6 GHz), which can be used as a reference model for in vivo channel response without performing intensive experiments or simulations. The statistics of error prediction between experimental and proposed model is RMSE = 5.29, which show the high accuracy of the proposed model. Also, the proposed model was applied to the blind data, and the statistics of error prediction is RMSE = 7.76, which also shows a reasonable accuracy of the model. This model will save the time and cost on simulations and experiments, and will help in designing an accurate link budget calculation for a future enhanced system for ultra-wideband body-centric wireless systems

Performance Comparison of Dual Connectivity and Hard Handover for LTE-5G Tight Integration

Communications at frequencies above 10 GHz (the mmWave band) are expected to play a major role for the next generation of cellular networks (5G), because of the potential multi-gigabit, ultra-low latency performance of this technology. mmWave frequencies however suffer from very high isotropic pathloss, which may result in cells with a much smaller coverage area than current LTE macrocells. High directionality techniques will be used to improve signal quality and extend coverage area, along with a high density deployment of mmWave base stations (BS). However, when propagation conditions are hard and it is difficult to provide high quality coverage with mmWave BS, it is necessary to rely on previous generation LTE base stations, which make use of lower frequencies (900 MHz - 3.5 GHz), which are less sensitive to blockage and experience lower pathloss. In order to provide ultra-reliable services to mobile users there is a need for network architectures that tightly and seamlessly integrate the LTE and mmWave Radio Access Technologies. In this paper we will present two possible alternatives for this integration and show how simulation tools can be used to assess and compare their performance.Comment: This paper was accepted for presentation at the ninth EAI SIMUtools 2016 conference, August 22 - 23, 2016, Prague, Czech Republi