Raja Sattiraju

Availability indication as key enabler for ultra-reliable communication in 5G

Due to its flexibility, cost-efficiency, and the ability to support mobility, wireless connectivity is seen today as a key enabler for a wide range of applications beyond classical mobile communications. A significant part of these applications depends on the capability of the wireless communication system to provide reliable connectivity. However, due to the randomness of the wireless propagation channel, reliability is still a critical issue in these systems. Some applications, such as vehicular and industrial applications, demand a level of reliability that wireless communication systems typically are not able to guarantee. This paper provides a framework that enables these applications to make use of wireless connectivity only if the transmission conditions are favorable enough. The concept is based on the idea that - despite the fact that it is practically impossible to ensure error-free wireless communication - it is feasible to derive boundary conditions for the transmission success. To this end, the paper introduces a novel metric for Ultra-Reliable Communication (URC) referred to as “Availability”, that determines the expected presence or absence of link reliability at the time of transmission. The availability is signaled by means of an Availability Indicator (AI) to the applications. Moreover, we develop the system model for computing the AI and illustrate the potential benefits of the new reliability metric by means of a possible implementation for automotive scenarios.

Robustness of Location Based D2D Resource Allocation against Positioning Errors

Device-to-Device (D2D) communications underlaying cellular network exploits physical proximity of the devices and aims at enhancing resource utilization, coverage, data rates and Quality of Service (QOS). Further, it enables the network operators to offload conventional network routed traffic to direct peer- to-peer links and could also support new application fields, such as Machine-to-Machine (M2M) and Vehicle-to-Vehicle (V2V), communication. In order to enable D2D communication, allocating resources (Physical resource blocks: PRBs) to D2D links by reusing cellular resources is a vital procedure. There are several resource allocation (RA) schemes that facilitate resource reuse of cellular PRBs for D2D communication. In most of these schemes, the crucial information for deciding upon PRB reuse is positions of D2D pairs and cellular users, so that mutual interference can be reduced. Further, there are certain schemes that rely on angular information of users to carry out resource allocation for D2D users. Thus, accuracy of position information plays an important role for employing these RA schemes in real world. This paper discusses RA schemes that are based on position/angular information and evaluates the robustness of location based RA schemes against positioning errors in real world deployment.

Reliability Modeling, Analysis and Prediction of Wireless Mobile Communications

The future Fifth Generation (5G) mobile cellular networks that are currently in research phase today enable broad range of services/applications beyond classical mobile communications. One key enabler for Ultra-Reliable services to be integrated into mobile networks is the Reliability of transmission success of a given data packet. This is harder mainly owing to the time-dependent effective link qualities of the communicating devices. However, successful indication of the availability of the instantaneous link quality (e.g., by the device) would allow opportunistic access of ultra reliable services/applications when the link conditions are fair enough. This paper introduces a framework for modeling, predicting and analyzing the theoretical reliability of the wireless link based on factors such as fading, mobility, interference etc. The analysis and prediction is based on the part stress method [1] by assuming time dependent factors as elements/components and their respective Transmission Times To Failure (TTTF). The proposed framework also supports other reliability analysis techniques such as Fault Tree Analysis [2] and Accelerated testing [3] of wireless systems and to improve the components.

Dynamic Context-Aware Optimization of D2D Communications

As one of the key technologies for next generation wireless communication systems, Device-to-Device (D2D) communication is able to offer several benefits, e.g. low end-to-end latency and traffic offload. In particular network controlled D2D operation underlaying the primary cellular system, e.g. LTE, and reusing its radio resources, is seen as an appealing option for increasing system capacity. However, a D2D link that reuses radio resources of another link introduces mutual interference in between these two links. In this paper, we firstly propose a network controlled radio resource management (RRM) algorithm that maximizes overall user satisfaction with the assistance of context information. The task of the algorithm is to decide on appropriate operation mode and allocate radio resources to both cellular and D2D links with respect to their channel state information (CSI) and service requirements. Furthermore, the RRM algorithm is extended to account for link priority information. Simulation results demonstrate the substantial performance improvement of our smart algorithm compared with a partial smart algorithm in terms of links satisfaction ratio.

Virtual Cell Sectoring for Enhancing Resource Allocation and Reuse in Network Controlled D2D Communication

Device-to-Device (D2D) communication underlaying cellular communications takes advantage of physical proximity of devices to improve coverage, resource utilization, data rates, QoS,and offers network operators the possibility to offload normally network-routed traffic to direct P2P links. This paper presents a novel Resource Allocation (RA) concept for D2D User Equipment(D-UEs) reusing the Physical Resource Blocks (PRBs) of the Cellular UEs (C-UEs). The RA algorithm is based on a virtual sectoring concept that relies on network assisted positioning technologies. By means of system level simulations, we show that this novel RA scheme yields significant performance and efficiency gains. To this end, we show the gains when such a RA scheme is employed along with some potential future directions.

Machine learning based obstacle detection for Automatic Train Pairing

Short Range wireless devices are becoming more and more popular for ubiquitous sensor and actuator connectivity in industrial communication scenarios. Apart from communication-only scenarios, there are also mission-critical use cases where the distance between the two communicating nodes needs to be determined precisely. Applications such as Automatic Guided Vehicles (AGVs), Automatic Train Pairing additionally require the devices to scan the environment and detect any potential humans/obstacles. Ultra-Wide Band (UWB) has emerged as a promising candidate for Real-Time Ranging and Localization (RTRL) due to advantages such as large channel capacity, better co-existence with legacy systems due to low transmit power, better performance in multipath environments etc. In this paper, we evaluate the performance of a UWB COTS device — TimeDomain P440 which can operate as a ranging radio and a monostatic radar simultaneously. To this end, we evaluate the possibility of using Supervised Learning based estimators for predicting the presence of obstacles by constructing a multiclass hypothesis. Simulation results show that the Ensemble tree based methods are able to calculate the likelihood of obstacle collision with accuracies close to 95%.

Design of a highly reliable wireless module for ultra-low-latency short range applications

Current radio systems are currently optimized for capacity and range. However, certain applications of wireless systems require fast and reliable communication over short distances. The challenge of these systems is to communicate with a minimum time delay (latency) while at the same time being very reliable and resilient to interference. This paper describes the concept and the proposed abstract architecture of a wireless technology that allows highly reliable and ultra low latency transmission of data between moving units over a few meters, the applications of which can be found in multitude of domains such as Train Communicaion Networks (TCNs), Truck/Tractor — Trailer Communication, Platooning, and in smart industry in the form of co-ordinating machines. The paper also describes the set of novelties that were planned to be realized as part of the final demo hardware.

Achievable Performance Gains Using Movement Prediction and Advanced 3D System Modeling

In contrast to synthetic user mobility models, user movements in real-world scenarios are restricted and typically conform to location-specific street layouts. Further in urban areas, user movements depend on traffic laws and behavior of other users. For example, vehicular users are said to stop at red traffic lights or should brake, if a vehicle ahead suddenly stops. Moreover, cellular users moving in these urban environments may face severe and abrupt changes in receive signal levels, which in the worst case result in connection drops. In order to pro-actively prevent these situations, where link rate decreases, handover execution is triggered too late, or even the connection dropped, a context-enhanced user movement prediction scheme is presented in this paper. Further, achievable performance gains using user movement prediction and modeling network deployment, user mobility, and radio propagation in a more realistic manner as envisioned for the next generation of wireless networks 5G are presented.