Jorge F. Schmidt

Underlay device-to-device communications in LTE-A: Uplink or downlink?

Device-to-device (D2D) communications is a promising candidate for increasing the throughput of cellular systems towards 5G. Its current consideration for inclusion in LTE-A is attracting a lot of research interest, including work on mode selection, bandwidth allocation, and power control. Some consider the uplink for D2D operation while others focus on operation over the downlink. It is still unclear, however, which link is preferable for D2D operation. This paper addresses this issue focusing on the outage performance of D2D receivers. We use stochastic geometry tools for our analysis, considering realistic system parameters and Nakagami fading. We find that the interference from the cellular system on the downlink, which is correlated over consecutive time slots, favors underlay D2D operation, resulting in a lower outage probability for the D2D transmissions.

DISTY: Dynamic Stochastic Time Synchronization for Wireless Sensor Networks

A time synchronization technique for networked devices with low-precision oscillators and low computational power is proposed and evaluated. We apply a dynamic stochastic model inserted into a Kalman filter formulation to track the clock evolution of oscillators and achieve synchrony to a central time reference. Indoor and outdoor experiments performed with commercially available wireless sensor platforms over several days serve as a proof of concept and show the synchronization accuracy under stable and varying temperature conditions.

Experiments with UWB aircraft sensor networks

We present an ultra-wideband (UWB) sensor network, deployed for aircraft applications. Off-the-shelf IEEE 802.15.4-2011 UWB compliant transceivers are, so far, only used for localization purposes. Thus, we modify transceiver configurations to enable data communication and realize a time division MAC scheme. Shadowing and the impact of passenger mobility are experimentally evaluated. Furthermore, channel attenuation and small-scale fading is analyzed, considering empty and occupied cabin cases and different node deployment positions.

Autoregressive Integrated Model for Time Synchronization in Wireless Sensor Networks

Time synchronization is challenging in wireless sensor networks due to the use of low-precision oscillators and the limited computational capacity of resources limited sensor nodes. While several schemes exist, the performance analysis of a majority of them is based on simulations and fail to capture key features of real world deployments. This paper explores the use of autoregressive integrated moving average models to provide a general clock model for sensor nodes with low precision oscillators and limited computational power. Based on measurements with off-the-shelf sensor devices Z1, an autoregressive integrated model for time synchronization is proposed. We derive a synchronization scheme (ARI-Sync) based on this model and compare it against the well known Flooding Time Synchronization Protocol (FTSP) observing significantly improved accuracy, roughly doubling the resynchronization period of Z1 nodes for a typical wireless sensor network application.

Demo: Exploring Autoregressive Integrated Models for Time Synchronization in Wireless Sensor Networks

Time synchronization provides the basis for several applications in wireless sensor networks but the limited memory and computational power, and the use of low precision oscillators make the task of time synchronization non-trivial. In this demonstration, we present a novel time synchronization scheme that is based on time series analysis. To provide a general model for the practical behavior of low precision oscillators, autoregressive integrated moving average models are explored. Based on the analysis of experimental data, an autoregressive integrated model (ARI (1,1)) is derived. Unlike the resource hungry Kalman filter based formulations, the proposed scheme is resource efficient as it results in simple linear regression processing. Experiments are performed on real sensor devices including Zolertia and TelosB, where an accuracy below 1 clock tick 1 is achieved.

Exploring Autoregressive Integrated Models for Time Synchronization in Wireless Sensor Networks

Time synchronization provides the basis for several applications in wireless sensor networks but the limited memory and computational power, and the use of low precision oscillators make the task of time synchronization non-trivial. In this demonstration, we present a novel time synchronization scheme that is based on time series analysis. To provide a general model for the practical behavior of low precision oscillators, autoregressive integrated moving average models are explored. Based on the analysis of experimental data, an autoregressive integrated model (ARI (1,1)) is derived. Unlike the resource hungry Kalman filter based formulations, the proposed scheme is resource efficient as it results in simple linear regression processing. Experiments are performed on real sensor devices including Zolertia and TelosB, where an accuracy below 1 clock tick1 is achieved.

Experimental Study of Packet Loss in a UWB Sensor Network for Aircraft

There is a strong demand in the aviation industry to replace cables in airplanes by wireless connectivity to gain flexibility and reduce weight. Such in-plane wireless communications must be reliable and robust against interference. As part of our activities in this domain, we present a proof-of-concept for an ultra-wideband (UWB) sensor network deployed in a mockup of a small passenger cabin of a commercial aircraft with a few passengers and report experimental results on the packet loss rate with off-the-shelf IEEE~802.15.4-2011 compliant UWB transceivers. It is shown that a combination of spatial and temporal diversity can significantly lower the packet loss rate of different link types without degrading throughput.