Industrial automation has created a high demand for private 5G networks, the deployment of which calls for an efficient and reliable solution to ensure strict compliance with regulatory emission limits. While traditional methods for measuring outdoor interference include collecting real-world data by walking or driving, the use of unmanned aerial vehicles (UAVs) offers an attractive alternative due to their flexible mobility and adaptive altitude. As UAVs perform measurements quickly and semiautomatically, they can potentially assist in near-real-time adjustments of the network configuration and fine-tuning its parameters, such as antenna settings and transmit power, as well as help improve indoor connectivity while respecting outdoor emission constraints. This article offers a firsthand tutorial on using aerial 5G emission assessment for interference management in nonpublic networks by reviewing the key challenges of UAV-mounted radio scanner measurements. In particular, we outline the challenges of practical assessment of the outdoor interference originating from a local indoor 5G network while discussing regulatory and other related constraints, and address practical methods and tools while summarizing the recent results of our measurement campaign. The reported proof of concept confirms that UAV-based systems represent a promising tool for capturing outdoor interference from private 5G systems.

UAV-Aided Interference Assessment for Private 5G NR Deployments: Challenges and Solutions

Crowdsourcing is a promising approach to collect the received signal strength (RSS) measurements required to construct Wi-Fi radio environment maps (REMs) via spatial interpolation methods. However, crowdsourced RSS measurements are often unreliable and especially in indoor propagation environments they are strongly affected by shadowing and fading. It is thus important to understand which spatial interpolation method is better suited for such REMs. In this paper we present an extensive empirical performance evaluation of four major spatial interpolation methods for crowdsourced indoor Wi-Fi REMs: Inverse Distance Weighting (IDW), Gradient Plus Inverse Distance Squared (GIDS), Ordinary Kriging (OrK), and Universal Kriging (UnK). We evaluate them both quantitatively by the estimation error, and qualitatively by visually observing the resulting REMs from measured Wi-Fi beacon RSSs. In our experiments we used sixteen Raspberry Pi boards and we considered different measurement location densities and spatial distributions in an office environment with four rooms. Both the quantitative and qualitative analysis of our experimental results show that there is only a negligible difference in the accuracy of the REMs constructed using the four considered spatial interpolation methods, relative to the inherent variability in the RSS reported by different devices. This suggests that, in practice, for crowdsourced indoor Wi-Fi REMs, simpler methods like IDW may be preferred over more computationally complex methods like Kriging. Importantly, our analysis also shows that, for moderate measurement location densities, the global RSS estimation error over a large indoor area with multiple rooms does not comprehensively characterize the performance of spatial interpolation methods. In addition to considering this metric, a quantitative analysis of the local error specific to each room, and a qualitative evaluation of the observed topology of the resulting REM need to be performed. This is a novel observation and suggests that more sophisticated metrics should be investigated for different engineering applications of REMs.

Crowdsourced Indoor Wi-Fi REMs: Does the Spatial Interpolation Method Matter?

This paper explores the data cleaning challenges that arise in using WiFi connectivity data to locate users to semantic indoor locations such as buildings, regions, rooms. WiFi connectivity data consists of sporadic connections between devices and nearby WiFi access points (APs), each of which may cover a relatively large area within a building. Our system, entitled semantic LOCATion cleanER (LOCATER), postulates semantic localization as a series of data cleaning tasks - first, it treats the problem of determining the AP to which a device is connected between any two of its connection events as a missing value detection and repair problem. It then associates the device with the semantic subregion (e.g., a conference room in the region) by postulating it as a location disambiguation problem. LOCATER uses a bootstrapping semi-supervised learning method for coarse localization and a probabilistic method to achieve finer localization. The paper shows that LOCATER can achieve significantly high accuracy at both the coarse and fine levels.

LOCATER: Cleaning WiFi Connectivity Datasets for Semantic Localization

A design method is proposed in this article for on-line (online measurement: measurement when producing devices) and on-site (on-site measurement: measurement when using devices) passive intermodulation (PIM) measurement with a small-size anechoic chamber. In a PIM measurement, the role of an anechoic chamber is to shield extraneous electromagnetic signal and reduce reflection, so that an accurate measurement result can be obtained. However, the chamber itself may introduce new PIM sources due to the nonlinearity in absorbing material and shielding enclosure. The traditional method to lower the influence of chamber to PIM measurement is to design a large-size PIM test chamber in order to reduce the PIM level by path loss. In this article, an innovative design concept of the PIM test chamber is presented by controlling the PIM source level of the anechoic chamber instead of increasing the size of the chamber. It can significantly reduce the chamber size using this method, particularly suitable for on-line and on-site PIM measurement. To implement the concept, absorbing material and shielding enclosure structure with extremely low PIM are developed. The design concept includes defining the worst-case reflection level, estimating the PIM level due to reflected signals, and determining the smallest size of the chamber that meets the design specifications. Finally, two PIM test chambers are built to demonstrate the design concept. PIM measurement results are given to verify the theoretical analysis.

Small Anechoic Chamber Design Method for On-Line and On-Site Passive Intermodulation Measurement

A horizontal planar scanner with an approximate size of 40 m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times40$ </tex-math></inline-formula> m has been implemented using the Unmanned Aerial Vehicle (UAV) technology. The UAV is not wired to the ground to maintain the flexibility and short setup time of a non-tethered flight. In this configuration, the UAV-mounted continuous-wave source is not phase-locked to the on-the-ground receiver. A dual-polarized reference antenna placed on the ground is hence used to retrieve the relevant phase information. The presented approach has been applied on the Pre - Aperture Array Verification System (Pre -AAVS1) of the Square Kilometre Array, which is a digital beamformed array with 16 active elements. An inverse source technique has been applied on measured Near-Field (NF) data acquired on two different sets of points (one for each electric field component) from all the receiver channels. In this way, Embedded Element Patterns (EEPs), array calibration coefficients and pattern have been determined from NF data only. The achieved results have been validated using a complementary set of Far-Field (FF) measurements and simulations. 

https://ieeexplore.ieee.org/ielx7/8566058/9669085/09771232.pdf

Large Horizontal Near-Field Scanner Based on a Non-Tethered Unmanned Aerial Vehicle

Radio coverage is a crucial component in any radio network design and deployment. In order to develop a design and deployment tool, we studied and utilized two different measurement approaches suitable for estimating indoor WiFi coverage. One of the tested approaches uses a handheld spectrum analyzer, while the other is a protocol-dependent method using standard Windows API calls. The applicability of these approaches is shown and the pros and cons of both measurement approaches are discussed based on visualization of the examples and comparison of the results. An analysis of the degree of dynamic radio channel effects for the observed differences between the two methods is also presented.

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Applying and Comparing Two Measurement Approaches for the Estimation of Indoor WiFi Coverage

This study presents the usage of unmanned aircraft for site survey and antenna pattern measurements in-situ in mobile networks. The site survey is one part of the verification and optimization process of the network operator. Mobile network operators' responsibility is to ensure the broadly available, reliable network series that are essential for customer experience. Technically that means mobile network coverage of the desired area without holes and with good capacity. The operator performs network planning in order to optimize coverage and capacity. It is essential to know the antenna pattern to plan and design an effective and efficient mobile network. Antenna manufacturers provide antenna radiation patterns measured in the standard anechoic chamber. Understanding how real site implementation differs from the laboratory measurements is also crucial. This study focuses on developing in-situ antenna measurements for the antenna patterns recorded in the laboratory. The evaluation of antenna radiation patterns in a real environment will provide additional information about what kind of effect the antenna site mast, installation, and antenna performance parameters will have on the theoretical radiation pattern.

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Using Unmanned Aircraft Systems for Mobile Network Verifications

The aim of this paper is to introduce the measurement method for challenging Non-Line of Sight (NLOS) conditions in mobile networks. The need to develop the measurement method appeared LTE (Long Term Evolution) uplink (UL) performance with different antenna technologies when receiving NLOS signal in field tests. Many challenges appeared during the study. This paper introduces the challenges and presents solution.

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Development of the measurement method for challenging NLOS conditions in mobile networks

The unmanned aircraft systems (UAS) are commonly used for aerial photography, express delivery for packets or video monitoring. The UAS technology can help responding to the growing demands of the frequency monitoring by national radiocommunication authorities (NRAs). This article presents a practical usage trial of an unmanned aircraft for monitoring the spectrum usage and finding the interference location. The monitoring of spectrum usage is one part of the NRAs’ process for guarantee user compliance with radio license conditions. Finding illegal or malfunctioning transmitters is a challenging task especially in urban environment, due to multi-path propagation conditions. This study focuses on practical assessment of the method for determining accurate location of radio frequency interference sources from the buildings using the UAS technology. The practicability of the UAS technology usage in spectrum monitoring activities was under the evaluation. This study showed promising results that UAS with the measurement equipment setup suits NRAs’ as a tool for mobile monitoring on the air.

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The Use of Unmanned Aircraft System for the Radio Frequency Interference Measurements

The objective of this paper is to compare uplink (UL) performance with different antenna technologies when receiving Non-Line of Sight (NLOS) signal in field tests. The antenna configurations in use were a passive antenna system and an active antenna system (AAS). The radiation pattern can be controlled horizontally by changing its azimuth angle and vertically by changing the tilt angle of the antenna. AAS includes a flexible configuration that consists of diversity beams and other features for beam controlling. The field trial benefitted 2-way and 4-way receive (RX) diversity in both antenna systems. The field trial environment consists of three macro-cellular Long Term Evolution (LTE) evolved Node B (eNB) operating in 2.1 GHz band. This trial environment has two AAS and one passive system in use for the measurements. The environment can encompass one macro cell and with vertical controlling, it is possible to add an additional beam and with horizontal controlling it is possible to steer the main beam towards the user equipment (UE). Field trial used drive test software to evaluate the test network performance. Mobile network user had UE in drive testing to evaluate cellular network quality from the mobile device's point of view. The field trial results indicate that AAS beam controlling can achieve remarkable capacity gain in uplink direction when UE does not have a line of sight to the eNB.

Marjut Koskela

Papers

Applying and Comparing Two Measurement Approaches for the Estimation of Indoor WiFi Coverage

Using Unmanned Aircraft Systems for Mobile Network Verifications

Development of the measurement method for challenging NLOS conditions in mobile networks

The Use of Unmanned Aircraft System for the Radio Frequency Interference Measurements

Antenna configuration comparison in challenging NLOS locations