Robert Falkenberg

Rushing Full Speed with LTE-Advanced Is Economical - A Power Consumption Analysis

Boosting data rates in LTE mobile networks is one of the key features of LTE-Advanced. This improved user experience is achieved by Carrier Aggregation (CA), in which the available spectrum of an operator is bundled out of several frequency bands. Accordingly, the user equipment has to supply multiple reception chains and therefore consumes considerably more power during a transmission. On the other hand, transmissions terminate faster, which enables a quick switchover into energy-saving mode. In order to examine these opposed facts, empirical analyses of existing devices are first carried out. Subsequently, we present a new CA enhancement of an existing context- aware power consumption model which incorporates the development density of the environment and the mobile device mobility. Based on the extended model we perform a detailed power consumption analysis and show that CA leads to power savings of 31% if the data rate doubled for large file transmissions. In addition, we show that CA can lead to power savings even from a data rate increase of 25%, regardless of mobility and urban development density. Besides, the measurement results show that CA operated in the same band leads to a lower power consumption than inter-band CA.

Empirical Analysis of the Impact of LTE Downlink Channel Indicators on the Uplink Connectivity

Many vehicular applications can be enabled of cellular communication networks like Long-Term Evolution (LTE). To guarantee a resource-efficient communication, the evaluation of the channel quality in the device is an important research topic in order to consider the channel quality for data transmission decisions. In this paper, the correlation between downlink channel quality indicators that are evaluated in the device and the uplink system performance is analyzed. For this purpose, theoretical analyses and field measurements in a dedicated LTE network as well as in a public LTE development are provided. The results show that the Reference Signal Received Power (RSRP) is suitable indicator for very good uplink connectivity situations and that the connectivity at the cell edge can be identified by the Reference Signal Received Quality (RSRQ).

A Simple Scheme for Distributed Passive Load Balancing in Mobile Ad-Hoc Networks

Efficient routing is one of the key challenges for next generation vehicular networks for providing fast and reliable communication in a smart city context. Various routing protocols have been proposed for determining optimal routing paths in highly dynamic topologies. However, it is the dilemma of those kinds of networks that good paths are used intensively, resulting in congestion and path quality degradation. In this paper, we adopt ideas from multipath routing and propose a simple decentral scheme for Mobile Ad-hoc Network (MANET) routing, which performs passive load balancing without requiring additional communication effort. It can easily be applied to existing routing protocols to achieve load balancing without changing the routing process itself. In comprehensive simulation studies, we apply the proposed load balancing technique to multiple example protocols and evaluate its effects on the network performance. The results show that all considered protocols can achieve significantly higher reliability and improved Packet Delivery Ratio (PDR) values by applying the proposed load balancing scheme.

PhyNetLab: An IoT-based warehouse testbed

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse.

Client-Based Control Channel Analysis for Connectivity Estimation in LTE Networks

Advanced Cyber-Physical Systems aim for the balancing of restricted local resources of deeply embedded systems with cloud-based resources depending on the availability of network connectivity: in case of excellent connectivity, the off-loading of large amounts of data can be more efficient than the local processing on a resource- constraint platform, while this latter solution is preferred in case of limited connectivity. This paper proposes a Client-Based Control Channel Analysis for Connectivity Estimation (C3ACE), a new passive probing mechanism to enable the client- side to estimate the connection quality of 4G networks in range. The results show that by observing and analyzing the control traffic in real-time, the number of active user equipment in a cell can be determined with surprising accuracy (with errors well below 10^-6). The specific challenge addressed in this paper lies in a dedicated filtering and validation of the DCI (Downlink Control Information). In a subsequent step the data rates to be expected can be estimated in order to enable decision about the choice of network and the timing of the data offloading to the cloud. The proposed methods have been implemented and validated leveraging the SDR OpenAirInterface, a real- life LTE network and a distributed load generator producing a scalable network traffic by a number of LTE User Equipment.