Bjoern Dusza

AirShield: A system-of-systems MUAV remote sensing architecture for disaster response

For clarification, containment and combat of large danger areas, fast and flexible survey of potentially contaminated areas is an emerging challenge. In this paper we present a project that focuses on incidents, that are caused by uncontrolled emissions of liquid or gaseous contaminants (e.g. explosive or toxic gases or liquids, biological, chemical or nuclear weapons). Instead of sending specially equipped forces with expensive transport and measurement devices into the contaminated area, our proposed system makes use of an autonomous, wireless connected swarm of Micro Unmanned Aerial Vehicles (MUAV), often simply known as drones, that are featured with lightweight mobile sensor systems. In this paper we will be particularly focusing on the complex communication system, which on the one hand has to organize the on-board-communication between the control systems of the MUAV and the sensors and on the other hand has to establish wireless connections to the mission control center on the ground as well as to neighboring MUAVs in the air via a mesh network.

An accurate measurement-based power consumption model for LTE uplink transmissions

In this poster the results of an accurate, measurement-based power consumption profiling of Long Term Evolution (LTE) User Equipment (UE) are presented together with concrete model parameter sets for four different most recent LTE data sticks and one LTE smart phone. In contrast to existing power consumption models for cellular devices, the model presented in this poster allows for a precise quantification of energy supply requirements depending on the LTE uplink data transmission power, the device type and the carrier frequency. This knowledge can be for example applied for the suitable dimensioning of batteries and energy harvesting devices in the context of LTE-based wireless sensor networks.

Influence of M2M communication on the physical resource utilization of LTE

The number of Machine-to-Machine (M2M) applications is rapidly increasing in cellular communication systems. In order to ensure a maximum system capacity, the impact of this special kind of traffic on common Human-to-Human (H2H) communication needs to be analyzed. In this paper, a system model for performance evaluation of cellular networks like Long Term Evolution (LTE) in the presence of M2M communication and under different Quality of Service (QoS) constraints is presented. By means of a Markovian model, which is parameterized by laboratory measurements and ray tracing simulations, an estimation of the behavior of LTE for different traffic characteristics is shown. We present blocking probabilities for an LTE network with heterogeneous M2M and H2H traffic and compare different transmission strategies for M2M communication to minimize the impact on human users. The results show that particularly a large number of devices with a low data rate influences the utilization of an LTE cell very negatively.

Channel sensitive transmission scheme for V2I-based Floating Car Data collection via LTE

In this paper, we present a channel sensitive transmission scheme which reduces the negative impact of Vehicle-to-Infrastructure (V2I) traffic on the Quality of Services (QoS) of Human to Human (H2H) communication in cellular networks. The performance evaluation of Long Term Evolution (LTE) for different traffic characteristics is based on an introduced Markovian model. This describes the utilization of the shared LTE Resource Blocks (RBs). The model is parameterized by laboratory measurements and ray tracing simulations. We present blocking probabilities for an LTE network with heterogeneous V2I and H2H traffic and propose different transmission strategies for V2I data with the goal to minimize the impact on human users. The results show that the number of V2I devices can be doubled by using channel sensitive transmission schemes ensuring equal QoS for H2H communication compared to periodically data transmission.

CoPoMo: a context-aware power consumption model for LTE user equipment

Increasing the battery lifetime of power-hungry mobile devices has become a major research target for mobile operators. Based on extensive measurement campaigns with the most recent Long Term Evolution (LTE) devices, we introduce a new Markovian power consumption model, which takes into account the chosen system parameters (such as the number of physical resource blocks) as well as the context of a user in terms of radio channel conditions and service characteristics (non-real-time vs. real time). One key advancement of this generic model is its stochastic nature, which allows for determining the average power consumption of a device based on usage profiles including location information and service statistics. We have conducted comprehensive system simulations using realistic channel characteristics derived from ray-tracing analyses and validated the new model. Finally, we show that the proposed context-aware power consumption model enables quantitative analyses of the trade-off between network resource allocation and enhanced battery lifetime.

Measuring the Impact of the Mobile Radio Channel on the Energy Efficiency of LTE User Equipment

The energy that has to be spent for the successful submission of one Bit is an important figure of merit for the performance analysis and optimization of modern wireless communication systems. The many factors which are influencing this performance parameter range from the efficiency of the User Equipments (UE) power amplifier to the average path loss, the Transmit Power Control (TPC) parametrization and the fading characteristics of the radio channel. Although many of the relationships can be analytically modeled, the aim of this paper is to present reliable measurements based on commercially available Long Term Evolution (LTE) hardware. Therefore, extensive User Datagram Protocol (UDP) data rate measurements have been performed in a mobile communications laboratory for different radio channel conditions. The impact of the mobile fading channel was emulated by a sophisticated radio channel emulator. Beside this, the on average consumed power of the LTE UE was measured during data transmission. From the results of these measurements, quantitative figures on the energy efficiency are presented for different LTE frequency bands and different radio channels. The results show that major energy savings are possible if the 800 MHz frequency band, which becomes available as part of the digital dividend, can be used for user with bad channel conditions. Considering energy efficiency as a Quality of Service (QoS) parameter of increasing importance the results presented in this paper allow for a context sensitive optimization in a way that the Modulation and Coding Scheme (MCS) switching points as well as the frequency band are chosen with respect to the UEs condition.

Three dimensional channel characterization for low altitude aerial vehicles

Based on the recent developments in the area of lithium polymer batteries and carbon fiber-reinforced plastic materials Micro Unmanned Aerial Vehicles (MUAV) have significantly gained in importance. Therefore, the use of MUAV based swarms is a feasible approach for remote sensing, surveillance and in particular for emergency and rescue missions [1][2]. Developing MUAVs which operate at low altitudes opens a new and challenging use case for both aerial mesh networks and existing cellular networks. The channel characteristics are crucial for the design of the required communication system. Since channel models for cellular networks typically assume that the users are at ground level, the use of these models for aerial deployment is a questionable attempt. For this reason, we are focusing in this paper on the channel characterization and analysis of an aerial mesh network based on a MUAV swarms. A choice of well known analytical and empirical channel models are adapted to the boundary conditions of low altitude platforms and subsequently validated by raytracing measurements in order to state their applicability.

Performance of Channel-Aware M2M communications based on LTE network measurements

The interaction between Machine-to-Machine (M2M) Communications, also known as Machine-Type Communications (MTC), and Human-to-Human (H2H) Communications is a recent topic in the context of cellular networks like Long Term Evolution (LTE). In this paper, we evaluate the performance of Channel-Aware MTC (CAT) based on LTE resource allocation measurements of a real LTE deployment. By means of a novel measurement setup, which uses a real-time spectrum analyzer, the LTE resource utilization in terms of occupied Resource Blocks (RBs) of the uplink is quantified for different channel conditions. Furthermore, the resource distribution in time and frequency domain, which is determined by the scheduler, is analyzed in this paper allowing for the calculation of average data rates and the spectral efficiency. The measurement results are used to quantize the potential gain of CAT. It is shown that by means of the scheme, the influence of MTC on other LTE users can be significantly reduced. In addition, the fraction of available RBs can be increased by 47%.

Optimized cross-layer protocol choices for LTE in high-speed vehicular environments

One important advantage of the Orthogonal Frequency Division Multiple Access (OFDMA) based cellular communication system Long Term Evolution (LTE) is its robustness against different kinds of impairments as they may occur on the mobile radio communication channel. This includes an increased toughness not only in harsh multi path scenarios, but also for the case of extremely high user velocities. In this paper, the applicability of the LTE system for two example applications (LTE based backhaul for high speed trains and live transmission of flight recorder data) is investigated by means of extensive throughput measurements (TCP and UDP) incorporating a radio channel emulator. The measurement results show that LTE in general is capable to provide reliable communication links for both considered scenarios. However, extreme velocities as they occur in a “flight data transmission at cruising speed” scenario rely on a specialized cross-layer parameterization.

Client-Based Control of the Interdependence Between LTE MTC and Human Data Traffic in Vehicular Environments

The interdependence between machine-type communication (MTC) and human-to-human (H2H) communication has become a major topic for the development of cellular communication systems. One example of MTC application is dynamic traffic forecast, which uses sensors that are mounted on cars as an information source (so-called extended floating car data). To reduce the impact of MTC traffic on the quality of service (QoS) of human users, this paper presents a client-controlled channel-aware transmission (CAT) strategy. A new Markovian model of the Long Term Evolution (LTE) radio resources assuming heterogeneous MTC and H2H traffic is used to evaluate the performance of this approach. The close-to-reality parameterization of the model is achieved by laboratory LTE data rate measurement campaigns and ray-tracing analyses. The model demonstrates that the CAT scheme decreases the LTE cell utilization and improves the QoS in terms of blocking probability of H2H communication. The results regarding CAT are validated in an independent simulation and by LTE field measurements. Beyond this, the influence of different MTC traffic models, including best- and worst-case investigations, is provided.