5G Signals Research Articles

Indoor Localization in Commercial 5G Environment with Single BS

Abstract. As commercial 5G systems rapidly expand, indoor positioning using 5G signals holds great potential for serving a large number of users. In this paper, an effective fingerprint solution is proposed for indoor positioning with 5G signal base station by exploring the multi-beam property. Multi-beam channel state information (CSI) and multi-beam reference signal received power (RSRP) are used as the observations for fingerprinting. To assess the effectiveness of the proposed scheme, field tests were conducted across various indoor environments. The results showed that the positioning accuracy is improved by more than 45% compared with the single beam by using the multi-beam characteristics of the 5G signal. Based on the multi-beam RSRP, the proposed scheme can achieve a positioning error of 67% below 1 meter. In the awareness of the two typical indoor deployments of 5G systems, i.e., the digital indoor distribution (DID) and the distributed antenna system (DAS), the paper also compared the 5G positioning performance in these two scenarios. The field tests showed that, the multi-beam in DID has more features than in DAS, which lead to a better positioning performance than that in DAS.

Location of 5G base station antenna in substation taking into account path loss and RF radiation

Aiming at the engineering problem that 5G base station antenna is difficult to locate efficiently in complex electromagnetic environment, a two-stage positioning method of 5G base station antenna substation is proposed, which considers signal path loss and antenna RF radiation. Firstly, the path loss solution model of the 5G base station antenna signal in the substation is established, and the RF radiation solution model generated by the coupling excitation of 5G high-frequency electromagnetic wave and the metal shell of the electrical equipment is constructed based on the big element physical optics method. Secondly, combining the advantages of particle swarm optimization (PSO) and interior point algorithm, the antenna positioning method considering path loss and RF radiation is constructed. Among them, in the first stage, the minimum loss of 5G signal path in the substation is taken as the goal, and the antenna stations in the substation are searched globally to get the optimal pre-selected position. In the second stage, the antenna position is calibrated according to the pre-selected position, so that the interference of RF radiation is minimized, and the final position is output. Finally, a 500 kV 5G substation in Henan Province was taken as the simulation object. Compared with the original scheme, the simulation results ensured the minimum 5G path loss in the substation and took into account the electromagnetic compatibility of the equipment in the substation. The effectiveness of the location strategy for maintaining the safe operation of the substation is verified, and it can provide a reference for the 5G base station antenna positioning project of the substation.

Guard Band Protection Scheme to Facilitate Coexistence of 5G Base Stations and Radar Altimeters

Reformation of the 3.7–4.0 GHz band to expand 5G communication deployment poses a risk of 5G signals disrupting radar altimeter operation, leading to data loss or inaccuracies. Thus, this paper proposes a guard band protection method to facilitate the coexistence of 5G base stations and radar altimeters operating in the 4.2–4.4 GHz band. To enhance the adjacent channel leakage ratio (ACLR), we implemented spectral regrowth on an oversampled waveform using a high-power amplifier model, filtering out-of-band spectral emissions. The results demonstrated that a 150 MHz guard band enables coexistence, except in the case of the 16-by-16 antenna array in rural environments. Notably, for the 4-by-4 antenna array in urban environments, coexistence can be achieved using a 50 MHz guard band. The proposed mitigation techniques may also be extended to promote coexistence between non-terrestrial networks and 5G communication systems, including satellites, unmanned aerial vehicles, and hot air balloons.

Preparation and research of high electromagnetic wave transmission type concrete in 5G frequency band

In urban areas with many buildings, the transmission of 5 G signals can be greatly absorbed or reflected, leading to decreased effectiveness of transmission. To address the issues mentioned above, the functional admixture formed by the mixture of nanocrystalline cellulose (NCC) and diammonium hydrogen phosphate (DAP) is added into concrete in this study, the electromagnetic transmission performance (ETP) and mechanical properties of concrete are enhanced simultaneously for the first time, and the electromagnetic transmission coefficient of concrete is doubled. When NCC and DAP are mixed, the electromagnetic transmission coefficient of concrete improved by 117.65 %-124.35 %, among which, when 0.5 wt% DAP and 4 wt% NCC are mixed, the electromagnetic transmission coefficient of concrete is the highest, and some frequency bands are as high as 70 %, meeting the requirements of electromagnetic wave transmitting materials. In addition, the compressive strength of concrete containing 4 wt% NCC and 0.5 wt% DAP increases by 24.3 % compared to concrete containing only 4 wt% NCC.

Research on reliable coverage planning of substation based on equipment service level

Abstract 5G network can meet the multi-type service access needs of substations and promote the intelligent upgrade and transformation of power grids. The layout of buildings and electrical equipment in substations, as well as electromagnetic interference, will have a greater impact on 5G signal coverage. In this paper, a three-dimensional simulation model of the substation is first established, and basic parameters of base station planning are determined. Then, a safety function considering equipment service level and an electromagnetic interference calculation method are defined. Finally, a coverage planning algorithm based on electrical equipment service level and received power quality is proposed to improve the reliability of service access and ensure the safe and stable operation of the system. Simulation results show that the algorithm is effective and reliable.

5G Radiation Source Location Based on Passive Virtual Aperture Technology by Single-Satellite

With the development of 5th-Generation Mobile Communication (5G) technology and the deployment of low-Earth orbit satellites, using satellites to locate 5G radiation sources is of great significance in commerce and the military as an important task of integrated sensing and communication. Recently, passive virtual aperture technology has been introduced into passive location to improve accuracy, but the existing method, using matched filters to search the Doppler information to realize the location, has the disadvantages of high complexity and poor range resolution. In this paper, an improved 5G radiation source location based on a virtual aperture is proposed, which uses the improved Golden Section search-fractional Fourier algorithm (GSS-FRFT) to improve the existing passive virtual aperture location methods. First, the received signals are coherently accumulated to convert the time gain into spatial gain, and the subcarrier phase information is extracted by Fast Fourier Transform based on the 5G signal characteristics to obtain the azimuth signal. Then, an improved high-order GSS-FRFT algorithm is proposed to analyze the Doppler information, and signal focusing and satellite ephemeris data are used to estimate the effective velocity and solve the radiation source location. The simulation results show that the proposed method can improve the location accuracy compared with other single-satellite location methods and has high resolution, high accuracy and low complexity compared with the existing passive virtual aperture location method.

Resonator-based near perfect metamaterial absorber with high EMI shielding for Wi-Fi and 5G applications

This paper introduces a perfect metamaterial absorber (MMA) achieving exceptional electromagnetic signal absorption at application-oriented frequencies of 2.40 and 3.50 GHz in addition to 6.09 GHz. The MMA exhibits absorption rates of 99.85, 98.6, and 96.7%, with high shielding effectiveness (SE) of 36.44, 32.58, and 31.13 dB against electromagnetic interference (EMI) at those frequencies. The structure of the copper resonator on the FR4 substrate allows the on-design frequency switching from 3.43 to 3.70 and 5.65 to 6.55 GHz, respectively. The structural symmetry enables polarization and incidence angle independence up to 60° for both transverse electric and magnetic modes. The perfect absorption of the MMA is shown by the near-zero polarization conversion ratio. There is an adjacent correlation between the measurement and simulation results. The proposed MMA emerges as an efficient EMI shield for Wi-Fi and 5G signals, offering perfect absorption and extensive polarization characteristics.

Fe3O4 Nanoparticles Embedded into Pyridinic-N-Rich Carbon Nanohoneycomb with Strong dx2-Pz Orbital Hybridization for High-Performance Electromagnetic Wave Absorption.

Carbon-based magnetic nanocomposites as promising lightweight electromagnetic wave (EMW) absorbents are expected to address critical issues caused by electromagnetic pollution. Herein, Fe3O4 nanoparticles embedded into a 3D N-rich porous carbon nanohoneycomb (Fe3O4@NC) were developed via the pyrolysis of an in-situ-polymerized compound of m-phenylenediamine initiated by FeCl2 in the presence of NaCl crystals as templates. Results demonstrate that Fe3O4@NC features highly dispersed Fe3O4 nanoparticles into an ultrahigh specific pyridinic-N doping carbon matrix, resulting in excellent impedance matching characteristics and electromagnetic wave absorbing capability with the biggest effective absorption bandwidth (EAB) of up to 7.1 GHz and the minimum reflective loss (RLmin) of up to -65.5 dB in the thin thickness of 2.5 and 2.3 mm, respectively, which also outperforms the majority of carbon-based absorbers reported. Meanwhile, its high absorption performance is further demonstrated by an ethylene propylene diene monomer wave absorbing patch filled with 8.0 wt % Fe3O4@NC, which can completely shield a 5G signal in a mobile phone. In addition, theory calculation reveals that there is a strongest dx2-Pz orbital hybridization interaction between Fe3O4 clusters and pyridinic-N dopants in the carbon network, compared with other kinds of N dopants, which can not only generate more dipoles of carbon networks but also increase net magnetic moments of Fe3O4, thereby leading to a coupling effect of efficient dielectric and magnetic losses. This work provides new insights into the precise design and synthesis of carbon-based magnetic composites with specific interface interactions and morphological effects for high-efficiency EMW absorption materials.

Chaotic Orthogonal Composite Sequence for 5G NR Time Service Signal Capture Algorithm

Establishing a national comprehensive PNT (Positioning, Navigation, and Timing) system has become a consensus among major countries worldwide. As a crucial component in completing the entire PNT system, the 5G NR (new radio) time service signal plays a vital role. This paper proposes a 5G NR time service signal that uses a spread spectrum system, shares the 5G signal frequency band, but does not occupy the bandwidth of the 5G communication signal. This timing service signal has relatively low power, making it appear “submerged” within the power of the 5G communication signal. The spread spectrum code for this timing signal employs the chaotic orthogonal composite sequence proposed in this paper. Compared to traditional spread spectrum sequences, this sequence offers better security than m-sequences, improved autocorrelation than Walsh sequences, and an effective suppression of the short-period characteristics exhibited when the Skew Tent-Map chaotic sequence takes special values. This paper simulates the capture of the 5G NR time service signal in an environment with a signal-to-noise ratio of 10 dB using an FFT-based parallel code phase search algorithm, successfully capturing the 5G NR time service signal and verifying the feasibility of the proposed chaotic orthogonal composite sequence as a spread spectrum code.

Dynamic LSTM for 5G Signal Power Amplifier Behavioral Model

Dynamic LSTM for 5G Signal Power Amplifier Behavioral Model

Power Amplifier Predistortion Using Reduced Sampling Rates in the Forward and Feedback Paths.

The feasibility of implementing digital predistortion for next-generation wireless communication is faced with a dilemma due to the ever-increasing demand for faster data rates. This causes the utilized bandwidth to increase significantly, as seen in the 5G NR standard in which bandwidths as high as 400 MHz are utilized. Hence, the development of new predistortion techniques in which the forward and feedback paths operate at lower sampling rates is of utmost importance to realize efficient and practical predistortion solutions. In this work, a novel predistortion technique is presented by which the predistortion is divided between the digital and analog domains. The predistorter is composed of a memoryless AM/AM gain function that is implementable in the analog domain, and a nonlinear model with memory effects in the digital domain to relax the sampling rate requirements on both the forward and feedback paths. Experimental validation was carried out with a 20 MHz and a 40 MHz 5G signal, and the results indicate minimal linearization degradation with a sampling rate reduction of 50% and 30%, respectively. This sampling rate reduction is concurrently applied in the digital-to-analog converter of the forward path and the analog-to-digital converter of the feedback path.

Rotating Target Detection Using Commercial 5G Signal

Passive radar detection emerges as a pivotal method for environmental perception and target detection within radar applications. Through leveraging its advantages, including minimal electromagnetic pollution and efficient spectrum utilization, passive radar methodologies have garnered increasing interest. In recent years, there has been an increasing selection of passive radar signal sources, and the emerging 5G has the characteristics of a high-frequency band, high bandwidth, and a large number of base stations, which give it significant advantages for use in passive radar. Therefore, in this paper, we introduce a passive radar target detection method based on 5G signals and design a rotating target speed measurement experiment. In the experiment, this paper validated the method of detecting rotating targets using 5G signals and evaluated the measurement accuracy, providing a research foundation for passive radar target detection using 5G signals and detecting rotating targets such as drone rotors.

Measurement and Analysis of 4G/5G Mobile Signal Coverage in a Heavy Industry Environment.

In the evolving landscape of Industry 4.0, the integration of advanced wireless technologies into manufacturing processes holds the promise of unprecedented connectivity and efficiency. In particular, the data transmission in a heavy industry environment needs stable connectivity with mobile operators. This paper deals with the performance study of 4G and 5G mobile signal coverage within a complex factory environment. For this purpose, a cost-effective and portable measurement setup was realized and used to provide long-term measurement campaigns monitoring and recording several key parameter indicators (KPIs) in 4G/5G downlink and upload. To support the reproducibility of the provided study and other research activities, the measured dataset is publicly available for download. Among others findings, the obtained results show how the performance of 4G/5G is influenced by a heavy industry environment and of the time of day on the network load.

Empirical modelling of dust storm path attenuation for 5G mmWave

The rapid evolution of communication technologies, particularly the emergence of 5G mm-wave networks, presents unprecedented challenges, particularly in regions prone to dust and sandstorms. These environmental factors can significantly impact 5G signals by attenuating radio waves, leading to signal degradation. This paper investigates the complex interplay between dust storms and 5G mm-wave wireless communication, offering a novel and comprehensive analysis that extends beyond existing models. Our study investigates into the impact of dust storms on 5G mm-wave wireless communication, specifically focusing on signal attenuations under both non-line of sight (NLOS) and line of sight (LOS) conditions. Through the utilize of the NYUSIM channel simulator and exploration of parameters such as dust particle size, storm duration, and environmental factors, we present a detailed numerical results. In the NLOS scenario, path loss measurements record substantial values, highlighting the significant impact of dust storms across different mm-wave frequencies. Conversely, in the LOS scenario, our findings reveal distinct patterns of path loss and shadow fading, shedding light on the complex interaction between dust storms and signal propagation. This research marks a significant advancement in the field, providing a quantitative foundation for addressing dust-induced attenuation in 5G mm-wave communication. By emphasizing novel research methodologies and innovative ideas, our study contributes to a deeper understanding of the challenges posed by dust storms in 5G mm-wave wireless communication systems, paving the way for more effective mitigation strategies and network optimization techniques.

How and why we built our Smart Farm

The Smart Farm of Bioeconomy Campus project (2021–2023) developed a unique hub of Smart Farming technology. The resulting Smart Farm aims to accelerate the adoption of smart technologies in farms according to the United Nations Sustainable Development Goals (SDGs). Therefore, at the Smart Farm, near-market technologies and services are tested, developed, and demonstrated. The aim is to remove barriers to their adoption and accelerate innovation in the sector, significantly increasing the benefits for farmers and the related agricultural industry. The foundation of the Smart Farm is based on processing various types of data. In the project, data was intensively collected from 16 hectares of test plots where barley was cultivated. Regular measurements were taken from the soil, crops, and from machinery and tractors equipped with ISOBUS technology. Measurements included the use of wireless soil sensors (20 units), drone imaging (RGB, multispectral, and thermal cameras), satellite images, and tractor telematics data. Additionally, the usability of the 5G signal in machine guidance was measured. Based on the collected data, precision farming was planned and implemented. Automated field navigation with headland automation was compared to traditional manual driving methods. Using GIS, maps such as profitability and energy consumption maps were generated from the data. The project developed a Farmer's Data Repository, through which a farmer can license their data to the desired destination via a data delivery service. The project also demonstrated the operation of such a system, compliant with EU data regulations, in collaboration with partner companies. A comprehensive project, the Finnish Future Farm (2023–2026), has begun based on the foundation of the Smart Farm, involving companies, educational and research organizations, farmers, and stakeholders. The project will build a digital twin of the physical Smart Farm, both of which will be utilized in R&D, experimentation, and education.

A Robust Evolutionary Particle Filter Technique for Integrated Navigation in Urban Environments via GNSS and 5G Signals

A Robust Evolutionary Particle Filter Technique for Integrated Navigation in Urban Environments via GNSS and 5G Signals

Pencil Beams and High-Precision Aiming of Wireless Power

Wireless Power Transfer (WPT) is the technique of delivering energy to specific targets with high-gain antennas. An important global application is SpaceBased Solar Power (SBSP) in which powersats in Earth orbit gather sunlight and beam this power to terrestrial groundstations (rectennae). At the distances involved, and the power levels needed to be economical, any stray (off-axis or off-target) energy can disrupt communications, giving cause for regulatory restriction or public objection of SBSP. Until recently, sidelobe levels (SLL) were limited to no lower than -60 dB, meaning that a gigawatt beam would give off kilowatt-range SLL, leading to desensitization of communications devices for a very wide radius surrounding a rectenna. The author discovered, published, and validated a specific design for a phased array antenna (PAA) that allows SLL to be reduced to -240 dB, creating what is called a "pencil beam" with negligible off-axis energy. Studies have found that this method can be applied to PAA as small as 6 m diameter at 5.8 GHz. This breakthrough discovery was first published in 2016 but appears to have largely escaped notice by the WPT community. The second issue is aiming accuracy, with the de facto solution being phase conjugation at the transmit PAA using a pilot beam issued from the receiver. While elegant, the accuracy of angle of arrival (AOA) using phase conjugtion is limited to about 1 degree (17 milliradians). This is sufficient for 5G signals over 100s of meters, but grossly inadequate for SBSP that requires microradian pointing accuracy. A novel method to detect AOA at the microrad scale that is separated from the transmitter emission electronics allows independent optimization of both. This work presents simulation studies showing microradian capability and laboratory results in the single millirad range, a factor of 10 improvement over the current state of the art. With this new approach, an orbiting powersat can aim its beam to a terrestrial target with stability under 100 m with off-axis energy at -127 dBm (typical surface environments are -100 to -80 dBm). The combination of a pencil beam and highly-accurate AOA detection bode well for realizing the benefits of SBSP.

Enhancing 5G propagation into vehicles and buildings using optically transparent and polarisation insensitive metasurfaces over wide-incidence angles

This article introduces two transmissive metasurfaces applied to normal windows, aiming to improve the 5G outdoor-to-indoor (O2I) coverage. These windows can be utilized in various settings, such as vehicles or buildings. The proposed unit cells, designed to be wide-incident angle and polarization insensitive, are implemented in both single-glazing and double-glazing glasses, arranged in a periodic structure to form the transmission surfaces. Both metasurfaces maintain optical transparency by incorporating Indium Tin Oxide (ITO) as the conductive element in each unit cell. These engineered transmission surfaces enhance the 5G signal indoor coverage at the 3.5 GHz band across a broad range of incident angles. While multi-layer structures typically exhibit heightened sensitivity to the angle of incidence, the proposed two-layered transmissive surfaces demonstrate substantial angular stability, reaching up to 65 and 75 degrees for double- and single-glazed glass, respectively. To achieve this wide and stable angular response, evolutionary optimization techniques were employed to fine-tune the proposed unit cells. Both designs exhibit a high transmission coefficient across the operating frequency for a variety of incident angles, surpassing those reported in the existing literature. Experimental evaluations of the fabricated prototypes indicate that both metasurfaces hold significant potential for enhancing signal propagation into buildings and vehicles.

5G Indoor Positioning Error Correction Based on 5G-PECNN.

With the development of the mobile network communication industry, 5G has been widely used in the consumer market, and the application of 5G technology for indoor positioning has emerged. Like most indoor positioning techniques, the propagation of 5G signals in indoor spaces is affected by noise, multipath propagation interference, installation errors, and other factors, leading to errors in 5G indoor positioning. This paper aims to address these issues by first constructing a 5G indoor positioning dataset and analyzing the characteristics of 5G positioning errors. Subsequently, we propose a 5G Positioning Error Correction Neural Network (5G-PECNN) based on neural networks. This network employs a multi-level fusion network structure designed to adapt to the error characteristics of 5G through adaptive gradient descent. Experimental validation demonstrates that the algorithm proposed in this paper achieves superior error correction within the error region, significantly outperforming traditional neural networks.

GNSS/5G Joint Position Based on Weighted Robust Iterative Kalman Filter

The Global Navigation Satellite System (GNSS) is widely used for its high accuracy, wide coverage, and strong real-time performance. However, limited by the navigation signal mechanism, satellite signals in urban canyons, bridges, tunnels, and other environments are seriously affected by non-line-of-sight and multipath effects, which greatly reduce positioning accuracy and positioning continuity. In order to meet the positioning requirements of human and vehicle navigation in complex environments, it was necessary to carry out this research on the integration of multiple signal sources. The Fifth Generation (5G) signal possesses key attributes, such as low latency, high bandwidth, and substantial capacity. Simultaneously, 5G Base Stations (BSs), serving as a fundamental mobile communication infrastructure, extend their coverage into areas traditionally challenging for GNSS technology, including indoor environments, tunnels, and urban canyons. Based on the actual needs, this paper proposes a system algorithm based on 5G and GNSS joint positioning, aiming at the situation that the User Equipment (UE) only establishes the connection with the 5G base station with the strongest signal. Considering the inherent nonlinear problem of user position and angle measurements in 5G observation, an angle cosine solution is proposed. Furthermore, enhancements to the Sage–Husa Adaptive Kalman Filter (SHAKF) algorithm are introduced to tackle issues related to observation weight distribution and adaptive updates of observation noise in multi-system joint positioning, particularly when there is a lack of prior information. This paper also introduces dual gross error detection adaptive correction of the forgetting factor based on innovation in the iterative Kalman filter to enhance accuracy and robustness. Finally, a series of simulation experiments and semi-physical experiments were conducted. The numerical results show that compared with the traditional method, the angle cosine method reduces the average number of iterations from 9.17 to 3 with higher accuracy, which greatly improves the efficiency of the algorithm. Meanwhile, compared with the standard Extended Kalman Filter (EKF), the proposed algorithm improved 48.66%, 35.17%, and 38.23% at 1σ/2σ/3σ, respectively.