Base Station Antennas Research Articles

Design of Shared-Aperture Base Station Antenna with a Conformal Radiation Pattern

Aiming at solving the problem of radiation pattern distortion caused by coupling between antennas in different frequency bands in traditional shared-aperture base station array antennas, a new shared-aperture array antenna integrating high-frequency filtering units and medium-frequency electromagnetic transparent antenna units is proposed. Without adding additional decoupling structures, it is possible to effectively reduce the coupling of different frequencies, while weakening common-mode and scattering interferences, making the radiation pattern conformal. The array consists of an electromagnetic transparent antenna unit in the medium-frequency (1.71–2.70 GHz) band and four filtering antenna units in the high-frequency (3.30–3.70 GHz) band. The four high-frequency antenna units form two 2 × 1 linear arrays arranged on both sides of the medium-frequency antenna unit and share a reflector. The simulation and measurement results show that the voltage standing wave ratio (VSWR) in the working frequency band is less than 1.50, the average gain in the medium-frequency band is 8.80 dBi, the average gain in the high-frequency band is 12.20 dBi, and the radiation pattern is normal. It is suitable for the field of shared-aperture base station antennas.

Innovative Approaches to Beam Forming Antenna Array Systems with Adaptive Partial Update NLMS Algorithms

Improvements in interference cancellation, energy economy, spectrum efficiency, and system security are among the most pressing needs for today's wireless networks. One effective technique for this is the use of a Beamforming Array Antennas (BAA). However, the complexity of the Beamforming (BF) network, the long convergence time, and the large number of adjustable weight coefficients, all work against full band BAA. The key innovation and contribution of this research was to use Partial Update (PU) instead of full band adaptive algorithms, as no previous attempt had been made to do so. A subset of the array's elements, rather than all of them, will be connected to by PU methods. This allows the system to reduce the number of active antennas across all cells while maintaining high efficiency, and low cost. In this research, a new architectural model was proposed that makes use of PU adaptive algorithms, to reduce the required number of phase shifters (PSs), and hence base station antennas. For the most part, we will be discussing PU Normalized Least Mean Square (PU NLMS) algorithms like M-max NLMS, Periodic-NLMS, and Stochastic-NLMS. Using a Uniform Linear Array (ULA) Antennas in a simulation environment, we find that the, in terms of Mean Square Error (MSE), convergence rate, and steady-state error, it is evident that all PU NLMS algorithms (with the exception of Periodic-NLMS) had performed close, and approximately equivalent performance to the full band NLMS algorithms. In other hands, these PU algorithms maintain the radiation pattern with as little change from the original (distortion-free) as possible and symmetrical of the array, while. fewer elements are needed to produce the same amount of radiation. Reducing the number of required coefficients N to M (M = 5; M: Number of coefficients to be update per iteration) compared to the full update method (N = 8), to obtain the Reduction ratio 38%.

Beam downtilt reconfigurable linear antenna array for 5G/6G macro base stations

AbstractIn this letter, a beam downtilt reconfigurable linear antenna array is presented for the demand of the electrical downtilt of 5G/6G macro base station antennas. The antenna is capable of fine‐angle beam direction reconfiguration, allowing for improved adaptability in various environmental conditions. A hierarchical network design is employed, which incorporates essential elements such as phase shifter modules, power dividers, and couplers. These fundamental components are used to construct a five‐element reconfigurable feeding network for the antenna array. The designed network ensures stable phase shifts and excellent impedance matching performance. By integrating the feeding network with the antenna elements, the system achieves electronic beam tilt adjustment across four states, enabling the linear array to tilt downward within a range of 6–12° around 3.5 GHz. This design provides enhanced beam control, making it suitable for next‐generation macro base station applications in 5G and 6G networks.

Dual-Polarized Crossed-Dipole Base Station Antenna Array With High-Isolation and Wide-Angle Scanning

Dual-Polarized Crossed-Dipole Base Station Antenna Array With High-Isolation and Wide-Angle Scanning

A hybrid equivalent circuit model and plane wave spectrum method for decoupling surface designs in multi‐band shared‐aperture antenna arrays

AbstractShared‐aperture antenna arrays are attractive for 5G base stations, owing to their compact size and multi‐band frequency coverage. Decoupling surfaces are effective for suppressing crossband mutual coupling. However, their designs typically rely on full‐wave simulations of scattering parameters, which may not ensure a good radiation performance and is time‐consuming. A systematic methodology based on the hybrid equivalent circuit model and plane wave spectrum method is proposed for decoupling surface designs. The decoupling surface is represented by its equivalent circuit and the spectral expression converts the electromagnetic field into a circuit problem. Both the scattering parameter and radiation pattern can be solved with the circuit, offering an efficient design method that ensures consistent radiation patterns between the model and full‐wave simulations. A double‐layer decoupling surface with wide stopbands, high transmission property, and sharp roll‐off transition was realised. Furthermore, to reduce the overall profile height, the reflection phase of the decoupling surface was tuned. A triple‐band shared‐aperture base station antenna array was developed. Simulated and measured results demonstrate the array works properly in the 0.69–0.96 GHz, 1.7–2.7 GHz, and 3.3–3.8 GHz frequency bands with stable radiation patterns, and crossband mutual coupling is well suppressed, validating the effectiveness of the proposed methodology.

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.

Energy‐efficient power allocation and antenna selection in full‐duplex multi‐cell distributed antenna systems

AbstractEnergy efficiency problem is investigated in distributed antenna systems (DAS), in which both users and base station (BS) antennas are full‐duplex (FD) capable. Multi‐cell and multi‐user scenario is considered. Users transmit power, BS antennas transmit power, and BS antenna selection are jointly optimized under single‐antenna power constraints, per‐user power constraints, and antenna selection constraints. Using the fractional programming, we convert the objective function equivalently from the fractional form to subtractive form. Then, the reformulated problem is decomposed into two subproblems for iterative optimization, the local optimal solution is obtained. Simulation results show the energy efficiency is significantly better than other reference algorithms and close to the optimal algorithm.

Impact of hardware impairments and BS antenna tilt on 3D drone localization and tracking

Today, GPS-free drone localization is increasingly gaining attention in various applications, but it faces significant accuracy challenges in three-dimensional (3D) space due to various impairments. This study investigates the effects of carrier frequency offset (CFO), phase noise (PN), and down-tilted base station (BS) antennas on drone positioning and tracking. Additionally, we explore the impact of inter-site distance (ISD) and BS density on drone position estimation accuracy. In our methodology, we consider a flying drone equipped with a single transmission antenna and BSs configured with 4 × 4 antennas under specific impairments. We first analyze the effects of these impairments on the signal’s covariance matrix. Then, using the MUSIC algorithm, we estimate the azimuth and elevation angles, which serve as the basis for drone localization using the Least Squares (LS) method across all BSs. Finally, the estimated positions feed into an Extended Kalman Filter (EKF) for tracking. Our results present a sequential analysis of the impact of all impairments on the off-diagonal covariance matrix, on the Angle of Arrival (AOA) estimation and 3D drone localization. We use simulations to demonstrate how hardware impairments affect 3D drone localization accuracy under varying ISD and BS densities.

Design of higher gain 1×4 cylindrical dielectric resonator antenna for mm-wave base stations

Design of higher gain 1×4 cylindrical dielectric resonator antenna for mm-wave base stations

An efficient multi‐probe enabled midfield over‐the‐air test method for 5G base station antenna pattern reconstruction

AbstractWith the accelerated deployment of 5G massive multi‐input multi‐output (MIMO)‐structured base stations (BSs), accurate and efficient testing of massive MIMO arrays is essential to ensure that the 5G massive MIMO antenna array can perform as expected. The increasing trend of both antenna element and array physical size makes massive MIMO antenna pattern measurement in the direct‐far‐field OTA environment unrealistic due to the signal attenuation, long measurement time, and ultra‐high test system construction cost. Therefore, the necessity of a compact, efficient, low‐complex, yet accurate OTA test method is evident, especially for 5G massive MIMO BS arrays. This paper proposes a novel multi‐probe‐enabled midfield (MF) OTA test method for 5G massive MIMO devices in compact measurement settings where antenna pattern measurement can be efficiently performed. The detailed theoretical analysis for the 5G massive MIMO array MF antenna pattern reconstruction method is presented, and the simulated validation results based on the typical 5G BS antenna arrays are provided and analysed, which demonstrate the effectiveness of the proposed MF OTA test method and can provide insights into the radio frequency parametric measurement for 5G massive MIMO devices.

Affective evaluation and exposure perception of everyday mobile phone usage situations.

To understand citizens' reactions to the 5G rollout, their affective reaction and perception of radiofrequency electromagnetic fields (RF-EMF) exposure are of interest. Although precursor studies on 2G-4G have investigated exposure perception mostly quantitatively, the present study applied a qualitative exploratory approach. A number of 35 individual interviews and 6 focus groups with the same participants were conducted in December 2022. Participants were recruited from several locations in Germany, where 5G rollout was at different stages. Interactive tasks, particularly an affective evaluation task and a ranking task, encouraged participants to consider their affect regarding mobile communications and their exposure perception. This approach allowed the participants to first engage with the topic of mobile communications/5G in an intuitive way, before talking about their specific beliefs on RF-EMF exposure. Several pictures showing a person (1) interacting with a mobile phone, (2) surrounded by other peoples' mobile phones, or (3) in the vicinity of mobile phone base stations (antennas) were used as stimulus materials. Data were analyzed using an exploratory content analysis. In the affective evaluation task participants revealed more negative associations with base stations than with mobile phones. The analysis showed that the reasons for their evaluation were very diverse, whereby exposure to RF-EMF only played a subordinate role. Further, the ranking task indicated that most participants (n=20) felt more exposed from base stations than from mobile devices. Results are mostly in-line with the literature on 2G-4G and do not indicate a substantially different exposure perception for 5G.

Broadband Suppression of Mutual Coupling in Compact Base Station Antenna Array by Adjusting Hybrid Coupling in Spatial Filtering Baffles

Broadband Suppression of Mutual Coupling in Compact Base Station Antenna Array by Adjusting Hybrid Coupling in Spatial Filtering Baffles

Performance evaluation of symbol detection algorithms in massive MIMO communication systems

Abstract Massive MIMO (mMIMO) is the essential technique for attaining the exponential increase in the data rate needed for future communication systems. These advancements have been significantly supported by progress in VLSI technology, which enables the integration of an enormous number of antennas and the complex signal processing essential for massive MIMO systems on a single chip. This work conducts a comprehensive analysis of the intricacy of seven matrix decomposition techniques for symbol detection in future mMIMO communication systems: ADMM-based infinity norm (ADMIN), Neumann series (NS), Newton iteration (NI), Jacobi iteration (Ja), improved Gauss-Seidel (IGS), conjugate gradient (CG), and QR decomposition (QR), against linear and near-optimal minimum mean square error (MMSE). QR, GS, Ja, and CG belong to linear algebraic methods based on matrix decomposition. MMSE and ADMIN are nonlinear optimization methods; NS and NI are iterative methods. The analysis examines into the complexity of these detection algorithms, considering the symbol error rate, the convergence rate, the initial solution vector, and the correlation factor. Performance evaluations are conducted on 8 and 16-user mMIMO systems with 64 and 128 base station antennas, modulation schemes (32-QAM and 64-QAM), iteration counts (p = 1, 2, 3, 4), correlation factors (α = 0.2, 0.4, and 0.6), and initial solution vectors (zero vector, D −1 and W 2 −1 yMF ). The result clearly shows that if the initial solution and number of iterations are chosen properly, the IGS-based linear detector achieves near-optimal performance with a lower computational complexity of O(K 2) compared to the nonlinear MMSE-based detector with a computational complexity of O(K 3).

Study on the preparation and magnetodielectric properties of ferrite composite Co2Z/LFO-LZT for broadband antenna application

Magnetic materials are anticipated to address the bandwidth and size limitations of dielectric resonant antennas (DRAs) to fulfill the application demands of 5G base station antennas. The present study focuses on the development of a novel Co2Z/LFO-LZT magnetic composite with exceptional microwave dielectric-magnetic properties through a hybrid ceramic process. The proposed ceramic achieves uniform dispersion of spinel magnetic nanocrystals at the grain boundary of Co2Z, resulting in the formation of a particular micro-concrete structure that significantly enhances ceramic densification and reduces magnetic-dielectric loss. The electromagnetic parameters of the ceramic optimized and used for antenna design are εr = 11; μr = 2; tanδε = 0.001; tanδμ = 0.08 at 5 GHz. A high-performance Magnetodielectric Resonant Antenna (MDRA) was designed, which exhibits a low profile of 11.4% λ0 at 5 GHz, and broadband performance covering 19.0% and 11.8% bandwidth at 5 and 8 GHz.

Enhancing spectral efficiency in uplink/downlink channels of multi-cell massive MIMO for 5G networks

Massive multiple-input multiple-output (MIMO) systems are at the forefront of 5G technology, significantly improving energy efficiency compared to earlier wireless communication systems. This study develops an optimal model for energy-efficient massive MIMO systems, aiming to increase spectral efficiency (SE) within a multi-cell framework. Base stations (BSs) use various techniques for channel estimations during uplink (UL) transmission, including minimum mean-squared error (MMSE), Least Squares, and Element-wise MMSE (EW-MMSE) estimators. The research evaluates the SE achievable through MMSE channel estimation by applying different receive combining schemes. Additionally, it explores downlink (DL) transmission using various precoding schemes, utilizing vectors similar to those in combining schemes. Simulations show a significant improvement in SE by advancing UL and DL transmission models. The study highlights that optimized MMSE channel estimation, along with an increased number of BS antennas and the ability to serve multiple user equipment (UEs) per cell, can enhance the average SE per cell. The findings indicate that optimizing channel estimation is crucial for the development of massive MIMO systems, especially for improving SE in both UL and DL transmissions.

Enhanced Energy Transfer Efficiency for IoT-Enabled Cyber-Physical Systems in 6G Edge Networks with WPT-MIMO-NOMA

The integration of wireless power transfer (WPT) with massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks can provide operational capabilities to energy-constrained Internet of Things (IoT) devices in cyber-physical systems such as smart autonomous vehicles. However, during downlink WPT, co-channel interference (CCI) can limit the energy efficiency (EE) gains in such systems. This paper proposes a user equipment (UE)–base station (BS) connection model to assign each UE to a single BS for WPT to mitigate CCI. An energy-efficient resource allocation scheme is developed that integrates the UE–BS connection approach with joint optimization of power control, time allocation, antenna selection, and subcarrier assignment. The proposed scheme improves EE by 24.72% and 33.76% under perfect and imperfect CSI conditions, respectively, compared to a benchmark scheme without UE–BS connections. The scheme requires fewer BS antennas to maximize EE and the distributed algorithm exhibits fast convergence. Furthermore, UE–BS connections’ impact on EE provided significant gains. Dedicated links improve EE by 24.72% (perfect CSI) and 33.76% (imperfect CSI) over standard connections. Imperfect CSI reduces EE, with the proposed scheme outperforming by 6.97% to 12.75% across error rates. More antennas enhance EE, with improvements of up to 123.12% (conventional MIMO) and 38.14% (massive MIMO) over standard setups. Larger convergence parameters improve convergence, achieving EE gains of 7.09% to 11.31% over the baseline with different convergence rates. The findings validate the effectiveness of the proposed techniques in improving WPT efficiency and EE in wireless-powered MIMO–NOMA networks.

Measurement of the electric field of mobile telephone base station antennas in Riobamba (Ecuador), to determine the specific absorption rate (SAR) in the human body

Exposure to electromagnetic and radio frequency fields generated by communication technologies such as mobile phones has raised concerns about electromagnetic pollution and its possible health effects. The objective of the study was to measure the electric field coming from cell phone base station antennas and determine through simulation in virtual anatomical models the maximum and average SAR in the whole body and in 10 g in different parts of the human body. The measurements were carried out with a selective non-ionizing electromagnetic radiation meter at 10 sites in the city of Riobamba, Ecuador. The highest maximum and average SAR for whole body was 3.045x10−7 and 3.923 x10−8 W/kg, respectively. While, at 10 g, the maximum SAR reached up to 8.52x10−9 W/kg in arms and the average SAR 2.13x10−9 W/kg in legs. All results are well below the limits established by the ICNIRP, suggesting a low risk of exposure. This work provides valuable information on the levels of exposure to electric fields from mobile telephone base stations and the results collected in this research could serve as a reference for future research, since the sampling method used could be reproduced to study the temporal variation of electric field levels in the city and conduct more comprehensive studies of SAR distribution in the human body.

Dynamic SNR, Spectral Efficiency, and Rate Characterization in 5G/6G mmWave/sub-THz Systems with Macro- and Micro-Mobilities

The performance of 5G/6G cellular systems operating in millimeter wave (mmWave, 30–100 GHz) and sub-terahertz (sub-THz, 100–300 GHz) bands is conventionally assessed by utilizing the static distributions of user locations. The rationale is that the use of the beam tracking procedure allows for keeping the beams of a base station (BS) and user equipment (UE) aligned at all times. However, by introducing 3GPP Reduced Capability (RedCap) UEs utilizing the Radio Resource Management (RRM) Relaxation procedure, this may no longer be the case, as UEs are allowed to skip synchronization signal blocks (SSB) to improve energy efficiency. Thus, to characterize the performance of such UEs, methods explicitly accounting for UE mobility are needed. In this paper, we will utilize the tools of the stochastic geometry and random walk theory to derive signal-to-noise ratio (SNR), spectral efficiency, and rate as an explicit function of time by accounting for mmWave/sub-THZ specifics, including realistic directional antenna radiation patterns and micro- and macro-mobilities causing dynamic antenna misalignment. Different from other studies in the field that consider time-averaged performance measures, these metrics are obtained as an explicit function of time. Our numerical results illustrate that the macro-mobility specifies the overall trend of the time-dependent spectral efficiency, while local dynamics at 1–3 s scales are mainly governed by micro-mobility. The difference between spectral efficiency corresponding to perfectly synchronized UE and BS antennas and time-dependent spectral efficiency in a completely desynchronized system is rather negligible for realistic cell coverages and stays within approximately 5–10% for a wide range of system parameters. These conclusions are not affected by the utilized antenna array at the BS side. However, accounting for realistic radiation patterns is critical for a time-dependent performance analysis of 5G/6G mmWave/sub-THz systems.

Combined scheme for mitigating coupling interference in dual‐band shared‐aperture base station antenna

AbstractA dual‐band shared‐aperture antenna array is presented, involving a combined scheme to suppress mutual coupling interference. The proposed array is comprised of a low‐band (LB) antenna, a frequency selective surface (FSS), sixteen high‐band (HB) antennas, and a reflector. The LB antenna utilises electromagnetic transparent (ET) characteristics to minimise scattering interference, while the FSS isolates resonance interference and port signal interference. The combined scheme integrates the benefits of both the ET antenna and FSS to suppress mutual coupling interference effectively. A prototype of the proposed antenna was fabricated and measured, operating at 1.7–2.7 GHz and 3.3–3.9 GHz. The simulated and measured results demonstrate stable patterns for both the LB antenna and the HB antennas. The cross‐band isolation is higher than 28 dB in the low‐band. With these advantages, the antenna array is suitable for base station applications.

Beamforming optimization of meta-learning algorithm based on gradient descent in RIS-assisted ISAC system

In this paper, we study an integrated sensing and communication (ISAC) system assisted by reconfigurable intelligent surface (RIS). Our goal is to minimize the transmit power of the BS by jointly optimizing the active beamforming and the passive beamforming under the constraints of the signal-to-interference-plus-noise ratio (SINR) of users, the Cramer–Rao bound (CRB) of sensing and the unit-modulus of RIS reflection elements. The optimization problem is difficult to solve because the objective function is non-convex and the variables are coupled. In addition, a large number of base station (BS) antennas lead to high-dimensional transmit beamforming vectors. We first prove that the optimization variables in the optimization problem are low-dimensional coefficient matrices and passive beamforming, rather than active and passive beamforming, which reduces the complexity compared with the original problem. In addition, when the sensing channel space belongs to the communication channel space, the dedicated sensing signal is not needed. Inspired by the meta-learning technology that can solve non-convex problems, we propose a meta-learning algorithm based on gradient descent (MLAGD) to design beamforming, which tends to learn dynamic optimization strategies and iteratively update optimization variables. Specifically, we first introduce Lagrangian multipliers to transform the constrained optimization problem into the Lagrangian dual domain, and the manifold-based optimization is employed to handle the unit-modulus constraint. The meta-learning neural networks are constructed to update optimization variables through local loss function, and then network parameters are updated through global loss function. The numerical results show the effectiveness of the algorithm.