Private cellular network deployments are increasingly adopted globally to connect machines on industrial campuses. Millimeter-wave (mmWave) cells need to be utilized when high wireless traffic volumes are expected, e.g., owing to high application requirements in conjunction with large number of devices. However, mmWave connectivity is highly sensible to non-line-of-sight (NLOS) conditions. For cost- and energy-efficiency reasons, 6G aims to illuminate under-connected shadow regions within the targeted service area using intelligent reflecting surfaces (IRSs). We present promising indoor measurement results for the attained performance boost using commercial equipment, where the introduction of a custom-designed passive IRS seamlessly restores throughput to 2 Gbit/s with the new propagation path increasing the link margin by more than 10 dB. Video Abstract-Demonstration video is available online at: https://tiny.cc/mmWaveHeliosMeasurements.

Future 6G private networks rely on millimeter-wave (mmWave) cells for ultra-high local connectivity, but non-line-of-sight (NLOS) scenarios demand costly dense deployments. Instead, a new approach gaining much attention in research introduces intelligent reflecting surfaces (IRSs) to increase coverage with fewer full-blown active antennas. In an earlier work, we introduced and validated a new passive IRS architecture leveraging additive manufacturing to provide reflections tailored exactly to the needs of a specific scenario. The design goal for so-called HELIOS reflectors is to procure a geometry realizing high power gains for mobile devices in a well-defined service area. This contribution introduces a design process coupling electromagnetic (EM) simulations with differential evolution-based optimization to custom-tailor the reflector shape. Our indoor measurements confirm the specified reflection characteristics and find that up to, on average, 41.2 % higher gain in receive power is attained over a broad angular range compared with a narrow-reflecting IRS. By increasing the IRS size, the peak gain of 20 dB can be matched. Moreover, it is found that the designed HELIOS reflectors support the entire mmWave spectrum. An additional benefit is given by the fact that the sub-6 GHz anchor link attains power gains of up to 12 dB from the same reflectors.

The ongoing development towards autonomous traffic requires detailed context information, including highly accurate position estimates. The 5G standard has therefore extended its feature support for positioning and defined six service levels (SLs) to cater to the various commercial use cases. User positioning at millimeter-waves (mmWaves) is considered particularly promising due to the inherent support for angle measurements and the contiguous broad bands. However, in the literature, a comprehensive classification of the achievable SLs with different positioning algorithms under different parameter measurement errors is missing. Based on ray-tracing data, we find that only the lower SLs can be achieved in an urban scenario, whereas SLs 4 to 6 are hard to meet due to the high availability requirements. For such use cases, hybrid positioning is needed to shorten the tail of the error distribution further: We show that positioning with a single base station (BS) is particularly well-suited because the identified network time synchronization problem is bypassed, thus attaining high accuracy at low overhead. Service availability can be improved further by integrating satellite-based estimates.

The use of high-gain directional communications is key to enable the capacity enhancement of millimeter-wave (mm-wave) for 5G-and-beyond networks. However, robust mm-wave coverage using directional beams entails significant beamsteering effort for maintaining precise beam alignment between the base station and the user. Numerous mm-wave beamsteering algorithms have been proposed in the literature, but verified largely using statistical channel models or limited measurements. Importantly this still leaves open the question of whether these studies can be directly translated to real outdoor mm-wave network deployments. In this paper, we present the results of the first extensive comparative evaluation of eight state-of-the-art mm-wave beamsteering algorithms based on outdoor mm-wave measurements using phased antenna arrays. We collect received signal strength data over fine-grained 3D angular orientations for 78 spatially-dense user positions in a European city, comprising an open-source dataset of over 421,000 individual measurements. We then perform an empirical evaluation of the beamsteering algorithms in the context of link establishment for static and link maintenance for mobile users. Overall, our results show that these state-of-the-art mm-wave beamsteering algorithms, when tested on real measurement data, perform far from optimal and worse than originally reported. A key takeaway from our evaluation is that the practical feasibility of beamsteering algorithms strongly depends on the trade-off between the incurred beam training delay and the antenna gains facilitated in the initial beam training stage which limit the established link budget. Our study of link maintenance for mobile users showed significant deviations from the maximum achievable performance for all algorithms, including those that leverage correlation of the mm-wave sparse link opportunities or historical link information for link recovery. This shows that, to enable seamless connectivity in future mm-wave networks, more sophisticated beamsteering algorithms must be designed that intelligently adapt to the site-specific mm-wave channel while taking into account the realistic antenna beams of commercially-viable phased antenna arrays.