MIMO In Vivo

We present the performance of MIMO for in vivo environments, using ANSYS HFSS and their complete human body model, to determine the maximum data rates that can be achieved using an IEEE 802.11n system. Due to the lossy nature of the in vivo medium, achieving high data rates with reliable performance will be a challenge, especially since the in vivo antenna performance is strongly affected by near field coupling to the lossy medium and the signals levels will be limited by specified specific absorption rate (SAR) levels. We analyzed the bit error rate (BER) of a MIMO system with one pair of antennas placed in vivo and the second pair placed inside and outside the body at various distances from the in vivo antennas. The results were compared to SISO simulations and showed that by using MIMO in vivo, significant performance gain can be achieved, and at least two times the data rate can be supported with SAR limited transmit power levels, making it possible to achieve target data rates in the 100 Mbps.Comment: WAMICON 201

Ultrawideband Technology for Medical In-Body Sensor Networks: An Overview of the Human Body as a Propagation Medium, Phantoms, and Approaches for Propagation Analysis

[EN] An in-body sensor network is that in which at least one of the sensors is located inside the human body. Such wireless in-body sensors are used mainly in medical applications, collecting and monitoring important parameters for health and disease treatment. IEEE Standard 802.15.6-2012 for wireless body area networks (WBANs) considers in-body communications in the Medical Implant Communications Service (MICS) band. Nevertheless, high-data-rate communications are not feasible at the MICS band because of its narrow occupied bandwidth. In this framework, ultrawideband (UWB) systems have emerged as a potential solution for in-body highdata-rate communications because of their miniaturization capabilities and low power consumption.This work was supported by the Programa de Ayudas de Investigación y Desarrollo (PAID-01-16) at the Universitat Politècnica de València, Spain; by the Ministerio de Economía y Competitividad, Spain (TEC2014-60258-C2-1-R); and by the European FEDER funds. It was also funded by the European Union’s H2020:MSCA:ITN program for the Wireless In-Body Environ-ment Communication–WiBEC project under grant 675353.Garcia-Pardo, C.; Andreu-Estellés, C.; Fornés Leal, A.; Castelló-Palacios, S.; Pérez-Simbor, S.; Barbi, M.; Vallés Lluch, A.... (2018). Ultrawideband Technology for Medical In-Body Sensor Networks: An Overview of the Human Body as a Propagation Medium, Phantoms, and Approaches for Propagation Analysis. IEEE Antennas and Propagation Magazine. 60(3):19-33. https://doi.org/10.1109/MAP.2018.2818458S193360

Intelligent Reflecting Surfaces Positioning in 6G Networks

The work analyzed the positioning of IRS over the coverage region of micro cell to derive optimal placement location to support cell-edge Internet of Things (IoT) devices with a favorable signal-to-interference plus noise ratio (SINR). Moreover, the work derived that the implementation of IRS significantly enhances energy efficiency notably reducing the transmit power of the micro cell base station

ANÁLISIS Y COMPRESIÓN DE SEÑALES NEURONALES PARA SU TRANSMISIÓN INALÁMBRICA

Esta tesina ofrece un estudio sobre un sistema para la captación, compresión y transmisión inalámbrica de las señales neuronales, en el que destaca la movilidad que ofrece la transmisión inalámbrica ya que permitirá tanto la realización de experimentos "in-vivo", como el desarrollo de dispositivos implantables sin los inconvenientes del cableado.Traver Sebastiá, L. (2007). ANÁLISIS Y COMPRESIÓN DE SEÑALES NEURONALES PARA SU TRANSMISIÓN INALÁMBRICA. http://hdl.handle.net/10251/12540Archivo delegad