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signaling overhead, we also evaluate the algorithm’s sensitivity to the number and bandwidth of resources as well as to outdated channel information.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.

Multi-connectivity can increase the reliability of wireless communications by orders of magnitude due to an increased diversity. However, simply copying packets and sending them on multiple links in parallel, i. e., as standardized as packet duplication, will result in a wasteful scheme. For example, there is no benefit in receiving the same information more often than once if multiple links succeed. This drawback can be resolved by channel coding. In a previous work, we proposed packet transmission schemes based on rateless codes, which could already increase resource efficiency compared to packet duplication. Here, we extend our previous studies in two different ways. First, we replace the previously used random linear fountain code by a more sophisticated raptor code, namely the R10 code. Second, we investigate a scenario, where the rateless coding scheme, which typically does not need any feedback, has acknowledgement information available. Both proposals show significant benefits of up to 15 % compared with our previous work in our mathematical analysis and empirical simulations.

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.

To realize the next generation of ultra-reliable low-latency communications (URLLC) with less radio resource consumption, methods relying solely on the addition of redundancy do not suffice. An alternative is to monitor the wireless channel and prevent outages due to small scale fading by allocating users to suitable radio resources based on the channel gain. To overcome monitoring delays, predicted channel information is utilized. In this paper we are analyzing the outage probability of a max-min radio resource allocation (RRA) approach when Gaussian errors are present in the channel state information (CSI). As a communications channel, a Rayleigh fast fading channel is assumed. The outage probability is lower and upper bounded to get analytical performance approximations. Furthermore, the performance is also empirically evaluated by means of extensive Monte-Carlo simulations. The analysis shows, that the achievable outage probability mostly depends on the size of the resource pool and the quality of the CSI.

By scheduling users to resources that are operational rather than on a best effort basis, the overall resource consumption of ultra-reliable low-latency communications (URLLC) can be reduced while maintaining a desired quality of service (QoS). To overcome the time delay between monitoring the channel state and the actual payload transmission, predictive methods which are tailored to the needs of URLLC become indispensable. In this paper we extend our Wiener filter based Rayleigh fading outage predictor to the Rician fading case. Compared to Rayleigh fading, additional estimators for the line of sight (LOS) parameters are presented. Our results show that the overall outage prediction performance increases significantly with increasing power of the LOS component compared to the Rayleigh fading case. The resource utilization for a particular user equipment (UE) rises to more than 99% in the investigated scenario for small prediction horizons and a Rician K-factor of K = 10 while achieving effective outage probabilities of 10−5. By comparing with the case of perfect parameter estimation, we show that the influence of the introduced estimators on the outage prediction performance is within acceptable limits.

Due to the great flexibility and innate simplicity of wireless networks, many applications are now realized with wireless connectivity at their core. Countless novel applications are enabled this way and legacy applications are transferred to mobile networks to reap the same benefits. As the networks evolve, applications are becoming ever more demanding, particularly with respect to high reliability and low latency. A common way to achieve high reliability in wireless communications is adding redundant communication channels by means of multi-connectivity. This comes at the cost of additional radio resources that could have been used by other connections. However, multiple links are not always required to achieve the desired reliability. Thus, we propose to combine multi-connectivity with rateless coding as a strategy for efficient resource usage in reliable wireless communications. The proposed schemes consider an erasure channel, and can therefore be implemented on the application layer, making them suitable for use with different physical layer wireless technologies simultaneously. We start out with a single-user analysis and then extend our discussion to multi-user scenarios. Our approach is compared against standardized packet duplication with our analytical framework and by means of simulation. The results with rateless coding show significant gains with respect to the required resources and feedback transmissions.

Ultra-reliable communications enable various advanced use cases, such as autonomous driving and safety critical applications. However, state-of-the-art vehicular communications technologies, such as IEEE 802.11p and LTE-V2X, cannot meet the reliability requirement of all time-critical use cases. Therefore, the next generation of these technologies are being developed to enhance vehicular support for ultra-reliable use cases. In this paper, the reliability of these upcoming vehicular communications technologies (i.e., IEEE 802.11bd and NR-V2X) is analyzed. Even though physical layer standardizations are not yet available, proposed candidate settings are used for investigations. We use Monte Carlo simulations to evaluate the physical layer performance of these technologies in various vehicle-to-vehicle (V2V) scenarios. High Doppler shifts in V2V scenarios is one of the main challenges to enable ultra-reliable communications. It is shown that NR-V2X can be expected to outperform IEEE 802.11bd in terms of reliability due to better handling of Doppler shifts. In case of IEEE 802.11bd, high Doppler shifts cause packet errors even at high signal-to-noise ratios (SNRs). Therefore, different measures to improve the performance of IEEE 802.11bd are discussed and evaluated.

Wireless system design on the physical layer is usually evaluated using comprehensive channel models. However, there is still a lack of publicly available stochastic channel models tailored to industrial use cases, which are recently considered more frequently. This paper presents the derivation of such a channel model for the 5 GHz ISM band and its parametrization. The frequency-selective behaviour is modeled by the Saleh-Valenzuela model. Based on a measurement campaign, the parameters of this model for a factory environment are determined and published the first time for the 5 GHz ISM band. Spatial correlation is modeled by the Kronecker model. The temporal variation of the channel is based on a theoretically derived Doppler spectrum assuming Laplacian distributed angle of arrivals. In addition to the description of the model components, key issues and common mistakes while constructing a channel model for industrial applications are discussed in order to advance the design and the deployment of future wireless industrial communications systems. The derived channel model is used in IEEE 802.11ax link layer simulations. It is shown that for industrial use cases specially tailored channel models are needed.