Characterization of Spatial-Temporal Channel Statistics from Indoor Measurement Data at D Band

Millimeter-wave (mmWave) and D Band (110--170~GHz) frequencies are poised to play a pivotal role in the advancement of sixth-generation (6G) systems and beyond, owing to their ability to enhance performance metrics such as capacity, ultra-low latency, and spectral efficiency. This paper concentrates on deriving statistical insights into power, delay, and the number of paths based on measurements conducted across four distinct locations at a center frequency of 143.1 GHz. The findings underscore the suitability of various distributions in characterizing power behavior in line-of-sight (LOS) scenarios, including lognormal, Nakagami, gamma, and beta distributions, whereas the loglogistic distribution gives the optimal fit for power distribution in non-line-of-sight (NLOS) scenarios. Moreover, the exponential distribution shows to be the most appropriate model for the delay distribution in both LOS and NLOS scenarios. In terms of the number of paths, observations indicate a tendency for the highest concentration within the 10 m to 30 m distance range between the transmitter (Tx) and receiver (Rx). These insights shed light on the statistical nature of D band propagation characteristics, which are vital for informing the design and optimization of future 6G communication systems

Ray-Optics Simulations of Outdoor-to-Indoor Multipath Channels at 4 and 14 GHz

Radio wave propagation simulations based on the ray-optical approximation have been widely adopted in coverage analysis for a range of situations, including the outdoor-to-indoor (O2I) scenario. In this work we present O2I ray-tracer simulations utilizing a complete building floor plan in the form of a point cloud. The ray-tracing simulation results are compared to measured channels at 4 and 14 GHz in terms of large scale parameters, namely path loss, delay spread and angular spread. In this work we address the importance of 1) interior walls and propagation paths originating therein, and 2) site-specific knowledge of window structure in accurately reproducing the O2I channel, particularly the presence of a thin insulating metal film on the windows. The best agreement between measurements and simulations was observed for the most detailed simulation. For both frequencies a mean error of less than 1.5 dB is reached for path loss, and a relative error of less than 10% for delay and angular spreads. Not including the metal film in simulations increases error of estimated building entry loss considerably, whereas absence of interior walls is detrimental to reproduction of large scale parameters.

On the Feasibility of Out-of-Band Spatial Channel Information for Millimeter-Wave Beam Search

The rollout of millimeter-wave (mmWave) cellular network enables us to realize the full potential of 5G/6G with vastly improved throughput and ultra-low latency. MmWave communication relies on highly directional transmission, which significantly increase the training overhead for fine beam alignment. The concept of using out-of-band spatial information to aid mmWave beam search is developed when multi-band systems operating in parallel. The feasibility of leveraging low-band channel information for coarse estimation of high-band beam directions strongly depends on the spatial congruence between two frequency bands. In this paper, we try to provide insights into the answers of two important questions. First, how similar is the power angular spectra (PAS) of radio channels between two well-separated frequency bands? Then, what is the impact of practical system configurations on spatial channel similarity? Specifically, the beam direction-based metric is proposed to measure the power loss and number of false directions if out-of-band spatial information is used instead of in-band information. This metric is more practical and useful than comparing normalized PAS directly. Point cloud ray-tracing and measurement results across multiple frequency bands and environments show that the degree of spatial similarity of beamformed channels is related to antenna beamwidth, frequency gap, and radio link conditions.

Impacts of Real Hands on 5G Millimeter-Wave Cellphone Antennas: Measurements and Electromagnetic Models

Penetration of cellphones into markets requires their robust operation in time-varying radio environments, especially for millimeter-wave communications. Hands and fingers of a human cause significant changes in the physical environments of cellphones, which influence the communication qualities to a large extent. In this paper, electromagnetic models of real hands and cellphone antennas are developed, and their efficacy is verified through measurements for the first time in the literature. Referential cellphone antenna arrays at $28$ and $39$~GHz are designed. Their radiation properties are evaluated through near-field scanning of the two prototypes, first in free space for calibration of the antenna measurement system and for building simplified models of the cellphone arrays. Next, radiation measurements are set up with real hands so that they are compared with electromagnetic simulations of the interaction between hands and simplified models of the arrays. The comparison showed a close agreement in terms of spherical coverage, indicating the efficacy of the hand and antenna array models along with the measurement approach. The repeatability of the measurements is $0.5$~dB difference in terms of cumulative distributions of the spherical coverage at the median level.

Ultrawideband Antenna Systems Embedded into a Load Bearing Wall for Connected Buildings

The importance of indoor mobile connectivity has increased during the last years, especially during the Covid-19 pandemic. In contrast, new energy-efficient buildings contain structures like low-emissive widows and multi-layered thermal insulations which all block radio signals effectively. To solve this problem with indoor connectivity, we study passive antenna systems embedded in walls of low-energy buildings. We provide analytical models of a load bearing wall along with numerical and empirical evaluations of ultrawideband back-to-back antenna spiral antenna system in terms of electromagnetic- and thermal insulation. The antenna systems are optimized to operate well when embedded into load bearing walls. Unit cell models of the antenna embedded load bearing wall, which are called {\it signal-transmissive walls} in this paper, are developed to analyze their electromagnetic and thermal insulation properties. We show that our signal-transmissive wall improves the electromagnetic transmission compared to a raw load bearing wall over a wide bandwidth of 3-8 GHz, covering most of the new radio frequency range 1 (NR FR1), without compromising the thermal insulation capability of the wall demanded by the building regulation.

6G Radio Requirements to Support Integrated Communication, Localization, and Sensing

6G will be characterized by extreme use cases, not only for communication, but also for localization, and sensing. The use cases can be directly mapped to requirements in terms of standard key performance indicators (KPIs), such as data rate, latency, or localization accuracy. The goal of this paper is to go one step further and map these standard KPIs to requirements on signals, on hardware architectures, and on deployments. Based on this, system solutions can be identified that can support several use cases simultaneously. Since there are several ways to meet the KPIs, there is no unique solution and preferable configurations will be discussed.

Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well.

Artificial intelligence enabled radio propagation for communications-Part I: Channel characterization and antenna-channel optimization

To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we investigate the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. It firstly provides a comprehensive overview of ML for channel characterization and ML-based antenna-channel optimization in this first part, and then it gives a state-of-the-art literature review of channel scenario identification and channel modeling in Part II. Fundamental results and key concepts of ML for communication networks are presented, and widely used ML methods for channel data processing, propagation channel estimation, and characterization are analyzed and compared. A discussion of challenges and future research directions for ML-enabled next generation networks of the topics covered in this part rounds off the paper.

Integration of Communication and Sensing in 6G: a Joint Industrial and Academic Perspective

6G will likely be the first generation of mobile communication that will feature tight integration of localization and sensing with communication functionalities. Among several worldwide initiatives, the Hexa-X flagship project stands out as it brings together 25 key players from adjacent industries and academia, and has among its explicit goals to research fundamentally new radio access technologies and high-resolution localization and sensing. Such features will not only enable novel use cases requiring extreme localization performance, but also provide a means to support and improve communication functionalities. This paper provides an overview of the Hexa-X vision alongside the envisioned use cases. To close the required performance gap of these use cases with respect to 5G, several technical enablers will be discussed, together with the associated research challenges for the coming years.