Future wireless communication systems are foreseen to provide powerful enhancements such as high-precision localization, allowing the radio environment to be characterized with high spatial resolution. On the other hand, future industrial ultra-reliable low-latency communications (URLLC) scenarios will place extreme reliability requirements on communication systems. In this work, we present the idea of using high-resolution radio environment maps (REMs) that contain received power levels per location as well as information about spatially occurring fading patterns for the trajectory optimization of mobile robotics to proactively increase communications reliability. To find the optimal trajectory, we show how to apply the Dijkstra path-finding algorithm to a two-dimensional REM. Simulations using a high-resolution REM from a previous measurement campaign indicate that small trajectory adaptations may increase the minimum received power (and hence the reliability) by orders of magnitude. By penalizing trajectory adaptations during optimization, we analyze the tradeoff between the number of lane adaptations and the communications reliability. Appropriate penalty parameters enable to drastically reduce the number of path adaptations without compromising reliability. Similar results are found for a ray-tracing-based REM of the same environment which suggests the use of synthetic REMs for effective investigation of other environments. This encourages follow-up investigations on reliability gains for radio propagation conditions in other environments.

Achieving high reliability in the presence of fading is particularly challenging under latency constraints, because the usual way of error mitigation by repetition becomes unfavorable. On the other hand, multi-connectivity does improve reliability without adding latency, but multiplies the required bandwidth per link and does not scale to a large number of users. There is hence a need for frequency diversity in a spectrum-efficient way. In this work, we investigate multi-user resource allocation schemes both without and with knowledge of each user’s channel state. We evaluate the allocation-dependent reliability in terms of outage rate and outage duration based on simulations of automated guided vehicles in an industrial environment. To increase validity and ensure real-world correlation between vehicles, we draw channel states from high-resolution channel measurements at a factory floor. For channel-aware allocation, we propose a near-optimal low-complexity algorithm using different quality functions based on channel state preference lists. Since accurate channel information per user and resource incurs signaling overhead, we also evaluate the algorithm’s sensitivity to the number and bandwidth of resources as well as to outdated channel information. In conclusion, channel-aware allocation offers significant reliability improvements over static allocation and emerges as a key enabler to realize ultra-reliable low-latency communications on a larger scale.

Knowledge about the current and future states of a radio channel takes the reliability of a communications system to a new level. A Radio Environment Map (REM) contains information about the channel state in the spatial domain for a given environment. Given a known user trajectory, this information can be used for channel prediction. In this work, we investigated the two primary limitations to this approach: the required spatio-temporal stationarity of the channel and the high localization accuracy of the user. The channel stationarity is quantified by repeated channel measurements. The high measurable consistency indicates the value of REMs in non-changing environments. Based on a high-resolution REM that we measured in an office environment, we quantify the impact of one- and two-dimensional localization errors on the resulting prediction error. With the results shown, localization accuracy requirements can be derived given the target channel prediction accuracy. Also, the results help to determine the required spatial resolution of REM measurements in practice.

Packet repetitions aim at increasing the communication reliability of vehicle-to-vehicle (V2V) communication by exploiting the wireless channel diversity. Congestion-awareness is essential to limit the channel load increase, leading to packet loss and rising access delays. Previously, channel busy ratio (CBR) thresholds have been derived under static load conditions, the investigation of time-varying load conditions remained open. This work provides the first investigation on threshold-based repetition allocation under time-varying load conditions, focusing on the accuracy and timeliness of the CBR observation. Therefore, we evaluate the impact on the achievable transmission range and end-to-end delay. The results show a trade-off between responsiveness to load changes achieved by short, and high accuracy achieved for long observation windows. While short observations allow to quickly adapt to load changes, which avoid performance degradation due to temporarily channel congestion, the observation underlies severe fluctuations leading misallocations causing performance loss. In contrast, long observations allow to avoid wrong allocations, instead they tend to oscillations. Based on the results, the dynamic adaptation of the observation time based on the load history is proposed. It shows that the adaptation using a simple threshold-based detection of load changes does not only quickly converges to the optimal allocation, but also reduces false and oscillating allocations.

Reliable V2V communications is key to enable energy-efficient and accident-free road mobility. Packet repetitions as proposed for IEEE 802.11bd allow to increase the transmission reliability by combining redundant messages at the cost of increased channel load, leading to packet loss and rising access delays. As so far no investigations on this reliability trade-off are available, we present the first comprehensive analysis on repetitions for the new technology. Therefore, we quantify the combining gain in link-level simulations, which show a benefit of frequency diversity. Next, we model the repetition reliability trade-off in dependency of the vehicle density on system-level. The results show a severe performance degradation with increasing density caused by the added transmissions. Based on the results, we elaborate on how to design an optimal distributed repetition algorithm. It shows that defining static channel load thresholds is not sufficient to maximize the transmission reliability, as it does not correctly considers the impact of the allocation. Finally, we propose to employ multi-channel repetitions to mitigate potential channel congestion, meanwhile maximizing the combining gain.

Ultra-Reliable Low-Latency Communications (URLLC) is a prerequisite for advancing industrial automation. To verify whether communications systems meet these stringent requirements, physical layer simulations are a powerful tool. Such simulations rely on a large number of channel realizations to obtain statistically significant results. Using exclusively real-world measured channels is challenging, e.g., due to the measurement time needed. In this work, we propose how to derive a channel model that mimics not only the mean but equally the temporal behavior of data from an industrial channel measurement campaign. The approach considers time variation on a large scale, modeled through a Markov process, as well as fading of individual channel components, achieved through Doppler-filtered random processes based on empirical distributions. The model is validated in link-level simulations by comparing the synthesized channels to the original measured data by means of performance metrics relevant to URLLC, including mean and maximum outage durations. Our validations show that the model performs well and especially the outage durations, caused by consecutive packet losses, match the real channel characteristics very well. In the future, we can use the model to investigate how extensive measurements need to be in order to make statements about the performance of communications systems.

With the advent of the fourth industrial revolution i.e. Industry 4.0, plants and factories are becoming smarter and interconnected. The transitions demand vertical integration and seamless connectivity. For this purpose, there is a need for semantic communication between various devices including the heavily resource-constrained field devices. To address this, a real-time capable hardware-based implementation of a well-established semantic communication protocol, i.e. OPC Unified Architecture was designed and developed. This chip-based implementation is power-efficient and compact, making it suitable for the field level. The chip was analyzed and incorporated in a demonstrator as a proof of concept of its integration at field level in a plant module of the process industry. Various opportunities are also examined where the chip could be utilized to deliver benefits to existing and future technologies.

Various radio technologies address the diverse performance requirements of today's ITS applications and compete for deployment. Instead of choosing a specific technology, a heterogeneous mix of currently available as well as emerging V2X technologies is considered. Benefits are: the support of mixed deployments, flexible technology choice based on application requirements and reliability enhancements achieved by redundancy concepts. Besides presenting the highly heterogeneous architecture, we show the implementation design of its main components. Further we present a proof-of-concept implementation, which is validated in the Dresden test-bed for different use cases.

Cooperative automated driving applications require reliable and low- latency exchange of periodic control information among vehicles in proximity. Performing well at low channel loads, vehicular ad-hoc technologies suffer from performance degradation caused by channel congestion. We propose to apply Multi-RAT diversity to improve the reliability of transmissions by increasing robustness against channel congestion. Multi-RAT diversity is achieved by the redundant use of multiple access technologies in parallel. In this paper, we investigate on the potential reliability improvement by combing IEEE 802.11p and LTE-D2D mode 2. Besides explaining the basic effects and main design aspects, we quantify the potential gain in an example highway platooning scenario based on simulations and concrete requirements. The results show a high potential in the redundant use of IEEE 802.11p and PC5-based ad-hoc technologies. Significant increases in transmission range of up to four times, especially at high vehicle densities and under strict reliability requirements, are achieved.

Exploiting the full potential of automated driving systems requires reliable wireless communication enabling network connectivity and cooperation among vehicles. Multiple V2X technologies are addressing the requirements of connected autonomous driving applications. Recent investigations have shown that none of the technologies is flexible and reliable enough to serve the diverse requirements in terms of delay, reliability and throughput under the various circumstances observed by vehicles. Hybrid V2X communications enables the coordination of multiple communication technologies to efficiently adapt to the time-varying channel and road traffic conditions. Further it allows to increase reliability and throughput of transmissions by combining multiple RATs in parallel. This work gives an overview of the potential, challenges and main design aspects of hybrid V2X communications considering the latest technological developments.