Analog Beamforming Research Articles

Performance Analysis of Optimal Analog Beamforming with Modified ESPRIT DOA Estimation Algorithm for MIMO NOMA System Over Rayleigh Fading Channel

In this paper, anefficient DOA estimation multi-input multi-output non-orthogonal Multiple Access (MIMO NOMA) system based on analog beamforming with modified ESPRIT (M-ESPRIT) algorithm is considered to minimize interference under the Rayleigh fading channel. Materials and Methods: An innovative Modified ESPRIT Direction of Arrival (M-ESPRIT DOA) estimation algorithm is used for user detection and to establish efficient communication. The proposed M-ESPRIT algorithm is compared with the existing MUSIC algorithm for a sample size of 20, taken for each group. Results: The performance of analog beamforming based MIMO NOMA system is measured in terms of capacity vs. Signal to Noise Ratio (SNR). The increased signal values due to the Singular Value Decomposition (SVD) method, while focusing on the desired user reduces the interference. From the simulation result, the mean capacity of the MIMO NOMA with MUSIC algorithm at 10dB SNR is 6 bps/Hz and at 20 dB SNR is 12 bps/Hz with 20 element antenna array and with 30 element array, capacity at 10 dB SNR is 11 bps/Hz while at 20 dB is 21 bps/Hz. With the M-ESPRIT algorithm, capacity at 10 dB SNR is 8 bps/Hz and at 20 dB SNR is 15 bps/Hz with 20 element antenna array and with 30 element array, capacity at 10 dB SNR is 12 bps/Hz and at 20 dB SNR is 24 bps/Hz.

A review on Precoding Techniques For mm-Wave Massive MIMO Wireless Systems

The growing demands for high data rate wireless connectivity shed lights on the fact that appropriate spectrum regions need to be investigated so that the expected future needs will be satisfied. With this in mind, the research community has shown considerable interest in millimeter-wave (mm-wave) communication. Generally, hybrid transceivers combining the analog phase shifter and the RF chains with digital signal processing (DSP) systems are used for MIMO communication in the fifth generation (5G) wireless networks. This paper presents a survey for different precoding or beamforming techniques that have been proposed in the literature. These beamforming techniques are mainly classified based on their hardware structure into analog and digital beamforming. To reduce the hardware complexity and power consumption, the hybrid precoding techniques that combine analog and digital beamforming can be implemented for mm-wave massive MIMO wireless systems. The performance of the most common hybrid precoding algorithms has been investigated in this paper.

Joint Design of Hybrid Beamforming and Reflection Coefficients in RIS-Aided mmWave MIMO Systems

This paper considers a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) downlink communication system where hybrid analog-digital beamforming is employed at the base station (BS). We formulate a power minimization problem by jointly optimizing hybrid beamforming at the BS and the response matrix at the RIS, under the signal-to-interference-plus-noise ratio (SINR) constraints at all users. The problem is highly challenging to solve due to the non-convex SINR constraints as well as the unit-modulus phase shift constraints for both the RIS reflection coefficients and the analog beamformer. A two-layer penalty-based algorithm is proposed to decouple variables in SINR constraints, and manifold optimization is adopted to handle the non-convex unit-modulus constraints. We also propose a low-complexity sequential optimization method, which optimizes the RIS reflection coefficients, the analog beamformer, and the digital beamformer sequentially without iteration. Furthermore, the relationship between the power minimization problem and the max-min fairness (MMF) problem is discussed. Simulation results show that the proposed penalty-based algorithm outperforms the state-of-the-art semidefinite relaxation (SDR)-based algorithm. Results also demonstrate that the RIS plays an important role in the power reduction.

Reconfigurable intelligent surface based hybrid precoding for THz communications

Benefiting from the growth of the bandwidth, Terahertz (THz) communication can support the new application with explosive requirements of the ultra-high-speed rates for future 6G wireless systems. In order to compensate for the path loss of high frequency, massive Multiple-Input Multiple-Output (MIMO) can be utilized for high array gains by beamforming. However, the existing THz communication with massive MIMO has remarkably high energy consumption because a large number of analog phase shifters should be used to realize the analog beamforming. To solve this problem, a Reconfigurable Intelligent Surface (RIS) based hybrid precoding architecture for THz communication is developed in this paper, where the energy-hungry phased array is replaced by the energy-efficient RIS to realize the analog beamforming of the hybrid precoding. Then, based on the proposed RIS-based architecture, a sum-rate maximization problem for hybrid precoding is investigated. Since the phase shifts implemented by RIS in practice are often discrete, this sum-rate maximization problem with a non-convex constraint is challenging. Next, the sum-rate maximization problem is reformulated as a parallel Deep Neural Network (DNN) based classification problem, which can be solved by the proposed low-complexity Deep Learning based Multiple Discrete Classification (DL-MDC) hybrid precoding scheme. Finally, we provide numerous simulation results to show that the proposed DL-MDC scheme works well both in the theoretical Saleh-Valenzuela channel model and practical 3GPP channel model. Compared with existing iterative search algorithms, the proposed DL-MDC scheme significantly reduces the runtime with a negligible performance loss.

Multiuser steered signed quadrature spatial modulation for millimeter‐wave massive multiple‐input multiple‐output with hybrid beamforming

AbstractIn this article, signed quadrature spatial modulation (SQSM) scheme is intrinsically amalgamated with both fully digital geometric mean decomposition (GMD)‐based precoding technique and analog beamforming (ABF) for transmission over millimeter‐wave (mmWave) channel. Explicitly, the proposed scheme combines SQSM and GMD‐based hybrid beamforming (HBF) in downlink multiuser scenario, where the Frobenius norm‐based user selection algorithm is considered. This proposed scheme is denoted as multiuser steered SQSM (MUS‐SQSM). The ABF is used to mitigate the severity of the propagation loss in mmWave band by using power amplifiers and phase shifters. The performance of the proposed scheme in terms of both the bit error rate and the average mutual information is assessed in comparison to the conventional SQSM scheme performance. Simulation results show that significant improvements are realized by both the user selection algorithm and the application of ABF technique as the number of antenna array elements increases. It is also demonstrated that MUS‐SQSM scheme is robust against the channel estimation errors. Furthermore, the proposed MUS‐SQSM scheme with HBF benefits from the multiplexing gain of SQSM, the diversity gain of serving multiple users, and from the beamforming gain. All these gains increase the energy efficiency of the proposed model; thus, the proposed scheme can be considered in 5G wireless systems deployment.

An Optimal Procedure for the Design of Discrete Constrained Lens Antennas with Minimized Optical Aberrations. Part II: Three-Dimensional Multifocal Architectures

Novel three-dimensional discrete lens antennas characterized by a number of focal points ranging from one to five and defined explicitly via analytical equations are presented in the paper. A procedure to derive rotationally symmetric afocal lenses starting from multifocal lenses that are not rotationally symmetric is proposed as well. In addition, an innovative method to identify the focal surface minimizing the optical aberrations is derived. The lenses are compared in terms of optical aberrations and accommodation constraints. The most suitable lens architectures depend mainly on the required angular field of view and magnification factor. It is shown that a reduction by a factor close to 3 in the optical aberrations can be obtained when selecting the most appropriate lens architecture and keeping comparable accommodation constraints. The results, derived exploiting a geometrical optics (GO) formulation, provide useful indications for the preliminary design of constrained lens antennas before adopting full wave rigorous techniques. Three-dimensional discrete lens antennas can offer significant advantages as compared to conventional analog beamforming networks (as those based on Butler matrixes) in terms of frequency bandwidth, number of beams and number of radiating elements.

Beamforming design with fully connected analog beamformer using deep learning

SummaryBeamforming (BF) architecture, an emerging approach for large‐scale antenna arrays, is a key task for the next decade's communication systems. The proposed approach in millimeter wave transmission is a fully connected analog phase‐shifter‐based BF architecture with limited radio frequency chains and imperfect channel state information (CSI). Deep learning (DL) is a powerful method for channel estimation and signal identification in wireless communications. Hence, this research proposes a DL‐enabled beamforming neural network (BFNN) which can be programmed to optimize the beamformer to attain better spectral efficiency. Simulation findings reveal that the proposed BFNN achieves significant performance gain and high robustness to imperfect CSI. The proposed BFNN greatly decreases the computational complexity by 0.16 million floating point operations (FLOPs) over 0.26 million FLOPs by conventional BF algorithms.

An FPGA-Accelerated Parallel Digital Beamforming Core for Medical Ultrasound Sector Imaging.

Plane-wave transmission followed by parallel receive beamforming is popular among high frame rate (HFR) ultrasound (US) imaging methods. However, due to technological limitations, HFR imaging is not widely successful in clinical US. The proposed work aims to design a field-programmable gate array (FPGA)-accelerated parallel beamforming core for medical US sector imaging systems. This architecture supports up to 128 channels and forms 28 beams per plane wave transmission in parallel. A block random access memories (BRAMs)-based, 28-read one-write (28R1W) multi-ported delay line architecture is actualized to realize the delay line. In addition, to optimize the FPGA memory, the required beam focusing delays are stored in an external static random access memory (SRAM) and are loaded into the internal delay line registers by a cycle stealing direct memory access (DMA). The FPGA prototype validation and verification are performed on the custom-designed Xilinx-Kintex-7 XC7C410T FPGA-based US imaging platform. The results showed that for a field of view (FOV) of 90° with 0.5° resolution, 640×480 imaging size, a ft/s of 714 is achieved. The performance of the proposed parallel beamformer architecture is compared with existing development works and concluded that the architecture is superior due to its occupancy of FPGA hardware resources and the processing speed.

Near-Field Orthogonal Beam Scan by Phased Arrays of Antennas With Active Analog Beamformer for Maximum NF-RCS in Target Detection

Near-field radar cross section (NF-RCS) of a target depends on antennas’ radiation and can be maximized by adjusting the radiation patterns. It is justified by the power return ratio and can be computed by a comparison method. A theoretical foundation of operational mechanism for phased arrays of antennas is presented to produce conformal radiations for NF-RCS enhancement. The target’s scattering coefficients are extracted from operating the antenna array’s digital phase shifters (DPSs) to steer the resulting beams in this work. The scattering matrix is then analyzed by the singular value decomposition (SVD) to determine the antennas’ excitations for maximum NF-RCS with estimation stability. It results in orthogonal beams for the two-way radiations of antenna arrays to interpret the scattering mechanisms. The feasibility is validated by HFSS full-wave simulations and experimental measurement data.

On the beamforming design of millimeter wave UAV networks: Power vs. capacity trade-offs

The millimeter wave (mmWave) technology enables unmanned aerial vehicles (UAVs) to offer broadband high-speed wireless connectivity in 5G/6G networks. However, the limited footprint of a single UAV implementing analog beamforming (ABF) requires multiple aerial stations to operate in swarms to provide ubiquitous network coverage, thereby posing serious constraints in terms of battery power consumption. A possible remedy is to investigate the concept of hybrid beamforming (HBF) transceivers, which use a combination of analog beamformers to achieve higher flexibility in the beamforming design. This approach permits multiple ground users to be served simultaneously by the same UAV, despite involving higher energy consumption than its ABF counterpart. This paper presents a tractable stochastic analysis to characterize the ergodic capacity and power consumption of UAV mmWave networks, focusing on the trade-off between ABF and HBF architectures. A multi-beam coverage model is derived as a function of several UAV-specific parameters, including the number of UAVs, the deployment altitude, the antenna configuration, and the beamforming design. Our results show that, while ABF achieves better ergodic capacity at high altitudes, an HBF configuration with multiple beams, despite the use of more individually power-hungry RF blocks, always consumes less total power with limited capacity degradation.

True-Time-Delay Receiver IC With Reconfigurable Analog and Digital Beamforming

Spatial diversity advantages such as improved signal-to-noise ratio and in-band blocker filtering can be achieved through beamforming in the digital and/or analog domain. Digital beamforming benefits from the precision and efficient parallelization of digital signal processing. On the other hand, analog beamforming allows the filtering of in-band but out-of-beam blockers before the ADC which can improve the dynamic range performance of the receiver. A delay method based on resampling has recently emerged as a viable solution for enabling true-time-delay analog beamforming receivers, which overcome the fractional bandwidth limitation of phase-shift beamforming due to beam squint. This paper presents a 22-nm CMOS receiver prototype that enables reconfiguration between true-time-delay analog and digital beamforming to allow choosing the more suitable operation mode in different signal environments. The reconfigurability is achieved by exploiting the time-interleaved nature of both the resampling delay setup and high speed ADCs. In addition to the beamforming mode reconfigurability, the receiver achieves state-of-the-art 2 GHz instantaneous beamformed bandwidth in the analog mode. The receiver reaches a 100% fractional bandwidth at the low end of the 1–6 GHz frequency range.

An Efficient Beamforming Architecture to Handle the Trade-Off Between Performance and Hardware Complexity in Multiuser Massive MISO Systems

Beamforming is the fundamental concept of wireless communications to serve several users through multiple-antenna transceivers. The advent of massive multiple-input multiple-output (MIMO) systems leads to an investigation into beamforming to reach optimal performance. However, fully-digital beamforming implementation has to face important challenges in terms of consumed power and cost of the RF chains and converters. To solve the problem, some studies focus on reducing hardware complexity by dividing the beamforming into digital and analog parts, known as hybrid beamforming (HBF). In HBF systems, the dominant part of the hardware complexity depends on the architecture of the analog network, which determines the required RF components. In this paper, we categorize the analog beamforming parts based on the connectivity between RF-chains and antennas. Moreover, we show the impacts of the connection on the analog beamforming matrix. To this aim, we propose an efficient connectivity architecture in which the antennas are divided into fully-connected and singly-connected groups so that we can deal with the hardware complexity-performance trade-off. In addition, to achieve further performance improvements, we propose a dynamic architecture that adjusts the connection of the RF-chain antenna to the channel state information (CSI) through a switch network. Analytically, we propose an efficient approach to calculate the zero-forcing precoder, which is proper for both fixed and dynamic architectures. A two-part algorithm based on the greedy search method has also been developed to obtain switch states in dynamic architecture and then implemented by a deep neural network (DNN). The simulation results confirm the theoretical analysis and the suitability of the proposed architecture.

Efficient Algorithms for Constant-Modulus Analog Beamforming

The use of a large-scale antenna array (LSAA) has become an important characteristic of multi-antenna communication systems to achieve beamforming gains such as in designing millimeter-wave (mmWave) systems to combat severe propagation losses. In such applications, each antenna element has to be driven by a radio frequency (RF) chain for the implementation of fully-digital beamformers, significantly increasing the hardware cost, complexity, and power consumption. Therefore, constant-modulus analog beamforming (CMAB) becomes a viable solution. In this paper, we consider the scaled analog beamforming (SAB) or constant-modulus analog beamforming (CMAB) architecture and design the system parameters by solving two variants of beampattern matching problem. In the first case, both the magnitude and phase of the beampattern are matched to the given desired beampattern whereas in the second case, only the magnitude of the beampattern is matched. Both the beampattern matching problems are cast as a variant of the constant-modulus least-squares (CLS) problem. We provide efficient algorithms based on the alternating majorization-minimization (AMM) framework that combines the alternating minimization and the MM frameworks and the conventional-cyclic coordinate descent (C-CCD) algorithms to solve the problem in each case. We also propose algorithms based on a new modified-CCD (M-CCD) based approach. For all the developed algorithms we prove convergence to a Karush-Kuhn-Tucker (KKT) point (or a stationary point). Numerical results demonstrate that the proposed algorithms converge faster than the state-of-the-art solutions. Among all the algorithms, the M-CCD-based algorithms have faster convergence when evaluated in terms of the number of iterations and the AMM-based algorithms offer lower complexity.

User Association and Hybrid Beamforming Designs for Cooperative mmWave MIMO Systems

Hybrid analog and digital beamforming has emerged as a key enabling technology for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) communication systems since it can balance the trade-off between system performance and hardware efficiency. Owing to the strong ability of central control, cooperative networks show great potential to enhance the spectral efficiency of mmWave communications. In this paper, we consider cooperative mmWave MIMO systems and propose user association and hybrid beamforming design algorithms for three typical hybrid beamforming architectures. The central processing unit (CPU) of the cooperative networks first matches the service pairs of base stations (BSs) and users. Then, an iterative hybrid beamforming design algorithm is proposed to maximize the weighted achievable sum-rate performance of the mmWave MIMO system with fully connected hybrid beamforming architecture. Moreover, a heuristic analog beamforming design algorithm is introduced for the fixed subarray hybrid beamforming architecture. In an effort to further exploit multiple-antenna diversities, we also consider the dynamic subarray architecture and propose a novel antenna design algorithm for the analog beamforming design. Simulation results illustrate that the proposed hybrid beamforming algorithms achieve a significant performance improvement than other existing approaches and the dynamic subarray architecture has great advantages of improving the energy efficiency (EE) performance.

Hybrid Beamformer Exploiting Multistream per User Transmission for Millimeter-Wave NOMA Communications

This treatise investigates multistream hybrid beamforming (HBF) for a millimeter-wave non-orthogonal multiple access (NOMA) system deployed in a downlink of an urban microcell environment. Maximization problem is developed to optimize sum-rate. For the sake of ensuring high correlation of users’ channels, user’s clustering and ordering are based on the angle of arrivals and users’ channel-weights, respectively. An optimized analog combiner of each user is obtained from the first <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{s}$ </tex-math></inline-formula> column vectors of the left unitary matrix derived from the singular value decomposition of the channel of each user. Analog beamformer is matched to the phase of the strong users ’ composite intermediate analog channel to maximize the beamforming gain. Both the analog combiner and precoder for sub-connected structure (SCS) are formulated via a novel dominant sub-array matrix elements’ extractor. Conventional zero-forcing processing is contemplated for digital precoding. Memory space complexity is evaluated to corroborate the simplicity of the proposed schemes’ computational complexity. Results obtained from the simulation exhibit that HBF-NOMA attain superior sum-rate than HBF-orthogonal multiple access and conventional multiuser schemes in line of sight link. Lastly, the proposed SCS-HBF-NOMA precoding scheme performs higher than fully connected counterpart in terms of energy efficiency.

QCQP With Extra Constant Modulus Constraints: Theory and Application to SINR Constrained Mmwave Hybrid Beamforming

The constant modulus constraint is widely used in analog beamforming, hybrid beamforming, intelligent reflecting surface design, and radar waveform design. The quadratically constrained quadratic programming (QCQP) problem is also widely used in signal processing. However, the QCQP with extra constant modulus constraints was not systematically studied in mathematic programming and signal processing. For example, the multiple quality of service (QoS) constrained analog beamforming is rare, while the QoS constrained digital beamforming methods are abundant. We propose to tackle the QCQP with extra constant modulus constraints problem by solving a series of subproblems with linear programming (LP) under extra constant modulus constraints. Under mild condition, the strong duality between the LP with extra constant modulus constraints and its dual problem is established. Then, by using the optimal solutions from the subproblems, the QCQP with extra constant modulus constraints problem is solved with a monotonically converged algorithm, and all converged solutions are Karush-Kuhn-Tucker (KKT) points. As an application of the proposed method, the signal-to-interference-plus-noise-ratio (SINR) constrained hybrid beamforming is solved. Simulation results show that the transmit power of the proposed method is similar to that of the semidefinite relaxation (SDR) method, while the computational time of proposed method is much smaller than that of the SDR method. The proposed method always provides feasible solution, while the SDR method does not always provide feasible solution.

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms,mmWave-massive MIMO,” which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better all-over performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.

Robust Energy-Efficient Hybrid Beamforming Design for Massive MIMO LEO Satellite Communication Systems

In low earth orbit (LEO) satellite communication systems, the limited energy supply capacity and the difficulty in obtaining channel state information (CSI) are the practical challenges. Motivated by this, we focus on the design of robust hybrid beamforming to maximize the energy efficiency of LEO satellite communication systems. Assuming that the LEO satellite transmitter adopts the massive multi-input multi-output (MIMO) technology, considering the CSI errors caused by propagation delay and Doppler shift, under the constraints of transmit power and quality of service (QoS), a robust energy-efficient hybrid beamforming scheme is proposed. Since that there are no explicit expressions for the ergodic user rate and the ergodic signal-to-interference-plus-noise ratio, the approximate values with closed-form expressions are adopted. Then, we invoke the semidefinite programming (SDP) algorithm to transform the nonconvex quadratic constrained quadratic programming (QCQP) problem equivalently, and an inner and outer nested iterative algorithm combining quadratic transformation fractional programming (QTFP) and concave convex process (CCCP) is utilized to transfer a nonconvex problem into a convex problem. Meanwhile, we adopt a penalty function algorithm to solve the rank-one constraint in semidefinite programming algorithm. Finally, we invoke the normal form distance minimization (NFDM) algorithm and the alternating optimization (AltOpt) algorithm to jointly solve the digital beamforming matrix and analog beamforming matrix in hybrid beamformer. Numerical results validate that our proposed robust approach significantly outperforms the conventional one.

Joint Phase-Time Arrays: A Paradigm for Frequency-Dependent Analog Beamforming in 6G

Hybrid beamforming is an attractive solution to build cost-effective and energy-efficient transceivers for millimeter-wave and terahertz systems. However, conventional hybrid beamforming techniques rely on analog components that generate a frequency flat response such as phase-shifters and switches, which limits the flexibility of the achievable beam patterns. As a novel alternative, this paper proposes a new class of hybrid beamforming called Joint phase-time arrays (JPTA), that additionally use true-time delay elements in the analog beamforming to create frequency-dependent analog beams. Using as an example two important frequency-dependent beam behaviors, the numerous benefits of such flexibility are exemplified. Subsequently, the JPTA beamformer design problem to generate any desired beam behavior is formulated and near-optimal algorithms to the problem are proposed. Simulations show that the proposed algorithms can outperform heuristics solutions for JPTA beamformer update. Furthermore, it is shown that JPTA can achieve the two exemplified beam behaviors with one radio-frequency chain, while conventional hybrid beamforming requires the radio-frequency chains to scale with the number of antennas to achieve similar performance. Finally, a wide range of problems to further tap into the potential of JPTA are also listed as future directions.

Calculating Beamforming Vectors for 5G System Applications

The growing demand for broadband Internet services is forcing scientists around the world to seek and develop new telecommunication technologies. With the transition from the fourth generation to the fifth generation wireless communication systems, one of these technologies is beamforming. The need for this technology was caused by the use of millimeter waves in data transmission. This frequency range is characterized by heavy path loss. The beamforming technology could compensate for this significant drawback. This paper discusses basic beamforming schemes and proposes a model implemented on the basis of QuaDRiGa. The model implements a MIMO channel using symmetrical antenna arrays. In addition, the methods for calculating the antenna weight coefficients based on the channel matrix are compared. The first well-known method is based on the addition of cluster responses to calculate the coefficients. The proposed one uses the singular value decomposition of the channel matrix into clusters to take into account the most correlated information between all clusters when calculating the antenna coefficients. According to the research results, the proposed method for calculating the antenna coefficients allows an increase in the SNR/SINR level by 8–10 dB on the receiving side in the case of analog beamforming with a known channel matrix.