Smart Antenna Technology Research Articles

Designing Smart Antennas Using Machine Learning Algorithms

Smart antenna technologies improve spectral efficiency, security, energy efficiency, and overall service quality in cellular networks by utilizing signal processing algorithms that provide radiation beams to users while producing nulls for interferers. In this paper, the performance of such ML solutions as the support vector machine (SVM) algorithm, the artificial neural network (ANN), the ensemble algorithm (EA), and the decision tree (DT) algorithm used for forming the beam of smart antennas are compared. A smart antenna array made up of 10 half-wave dipoles is considered. The ANN method is better than the remaining approaches when it comes to achieving beam and null directions, whereas EA offers better performance in terms of reducing the side lobe level (SLL). The maximum SLL is achieved using EA for all the user directions. The performance of the ANN algorithm in terms of forming the beam of a smart antenna is also compared with that of the variable-step size adaptive algorithm.

Phased Array System Toolbox Pack Overview for New Course «5G Smart Antennas Technologies»

In the field of smart antenna technologies, approaches based on simulation modeling in special Matlab software, including the Phased Array System Toolbox extension package, deserve special attention. This package provides the implementation of algorithms and methods for modeling antenna arrays (AA) and beamforming (BF) systems in various applications, including radio communication, radar and radio navigation systems. Using the capabilities of this extension package, you can analyze the performance of active and passive AAs of various geometric configurations, including complex AAs formed from composite arrays of elements. The simulation models built with this expansion package allow the formation and processing of signals using models and methods of beamforming, when working on transmission and reception. For LTE and 5G NR mobile networks, satellite systems and WLANs, the PAST extension package allows modeling multipath AAs, including those operating in the adaptive BF mode. The extension package includes models of digital and hybrid BF algorithms that operate as part of massive MIMO spatial signal processing systems in the mmWave. Simulation capabilities in the extension package include, but are not limited to, reproducing fading conditions in a multipath radio channel and evaluating their impact on communication systems with an AP; algorithms and methods for determining signal direction of arrival (DOA). In this paper, we review the coordinate systems used in the PAST extension package. Subject of study. The article is devoted to an overview of the PAST extension package for use in the new 5G Smart Antenna Technologies training course. Method. The study of the possibilities of the PAST extension package is carried out by the simulation. Main results. The result of this work is an overview of the coordinate systems in basic software tools of the PAST extension package for use in the new course "5G Smart Antenna Technologies". Practical significance. This review introduces the capabilities of the PAST extension package and is the foundation of methodological support in the implementation of algorithms and methods for modeling antenna arrays and beamforming systems within the framework of the new training course “5G Smart Antenna Technologies”.

Problem Statement for the Developing a New Training Course «5G Smart Antennas Technologies»

Interest in smart antenna technologies is due to the development of ultra-dense networks of the fifth 5G and subsequent B5G (Beyond 5G) generations of the millimeter-wave band (MMW, millimeter-wave – mmWave), which is confirmed by the high publication activity of recent years both in the native, and in foreign scientific community. Together with scientific publications in foreign literature, textbooks in this area are published and republished. At the same time, in the native scientific and methodological literature, there is currently no textbook that reveals new approaches to studying the issues of adaptive beamforming using smart antennas in relation to ultra-dense 5G and B5G networks. In this paper, an analysis of the state of the problem in the field of intelligent antennas is carried out and a task is formulated for the development of an appropriate training course. Subject of study. The article is devoted to a contemporary review of the state of the problem in the field of smart antennas based on the analysis of Russian sources. Method. Analysis of the evolution of the development of methods and means of smart antenna technologies. Main results. The result of this work is the setting of the task for the development of a new training course "Technologies of smart antennas 5G". Practical significance. The analysis carried out serves as a rationale for the relevance and necessity of developing a new training course "Technologies of smart antennas 5G".

Smart, Fast, and Low Memory Beam-Steering Antenna Configurations for 5G and Future Wireless Systems

Smart Antennas are important to provide mobility support for many enhanced 5G and future wireless applications and services, such as energy harvesting, virtual reality, Voice over 5G (Vo5G), connected vehicles, Machine-to-Machine Communication (M2M), and Internet of Things (IoT). Smart antenna technology enables us to reduce interference and multipath problems and increase the quality in communication signals. This paper presents a number of nonlinear configurations of dipole arrays for forming a single beam in any desired direction. We propose three, four, six, and eight-element array structures to perform this single beam-steering functionality. The proposed array configurations with multiple axes of symmetry (in the azimuthal plane) decrease the computational repetitions in optimizing respective weight factors for beam-steering. The optimized weight factors are obtained through the Least Mean Square (LMS) method. MATLABTM is used to calculate optimized weight factors as well as to determine the resulting radiation patterns. Since antennas are bidirectional elements, beamforming in one direction means that the antenna will also have high receiving gain in that direction. Performances of differently configured models are compared in terms of their directivity, sidelobe reduction, and computational complexities for beam-steering.

A New Adaptive Beamforming of Multiband Fractal Antenna Array in Strong-Jamming Environment

This paper proposes, for the first time, a new radiation pattern synthesis for fractal antenna array that combines the unique multi-band characteristics of fractal arrays with the adaptive beamforming requirements in wireless environment with high-jamming power. In this work, a new adaptive beamforming method based on discrete cbKalman filter is proposed for linear Cantor fractal array with high performance and low computational requirements. The proposed Kalman filter-based beamformer is compared with the Least Mean Squares (LMS) and the Recursive Least Squares (RLS) techniques under various parameter regimes, and the results reveal the superior performance of the proposed approach in terms of beamforming stability, Half-Power Beam Width (HPBW), maximum Side-Lobe Level (SLL), null depth at the direction of interference signals, and convergence rate for different Signal to Interference (SIR) values. Also, the results demonstrate that the suggested approach not only achieves perfect adaptation of the radiation pattern synthesis at high jamming power, but also keep the same SLL at different operating frequencies. This shows the usefulness of the proposed approach in multi-band smart antenna technology for mobile communications and other wireless systems.

Data-driven Diversity Antenna Selection for MIMO Communication using Machine Learning

<p>With the popularity of wireless application environments, smart antenna technology has completely changed the communication system. In order to improve the quality of wireless transmission, smart antennas have been widely used in wireless devices. Wireless signal modeling and prediction machine learning gradually replaced the traditional smart antenna selection method in the antenna selection solution. This article utilizes mobile devices to adjust the diversity antenna pattern for test verification in a MIMO wireless communication environment. The proposed method manipulates signal parameters through error vector magnitude (EVM) and adds data-driven training data. The results show that the SVM and NN methods proposed in this paper are 10.5% and 14% higher than the traditional EVM calculation methods, respectively. Thereby, realize precise antenna adjustment of mobile devices and improving wireless transmission quality.</p> <p> </p>

Investigation of Adaptive Beam-forming Algorithms for Smart Antennas System

Smart antennas are examined as a promising technology in wireless communication systems. In the development of smart antenna technology, Adaptive beam-forming is the most important aspect. Adaptive beam-forming uses various algorithms to identify the signals in the desired direction and separate the interference from the undesired/unwanted direction. In this paper, Proposed Adaptive Beam-forming Algorithm offers the better solution for reducing interference and improves the system capacity. The main objective of this paper is to analyze the different approaches used for designing the smart antennas to track the desired signal and put perfect null towards the interferer signal.

Subspace leakage reduced nonuniform sparse Fibonacci‐like planar array to estimate azimuth and elevation angles of both Angle of Arrival and Angle of Departure

Estimation of azimuth and elevation angles of both Angle of Arrival and Angle of Departure is a challenging research topic in 5G smart antenna technology. The key contributions of this work involve two novel algorithms implemented in a uniform planar array for the estimation of the arrival and departure angles using the received signal from the coherent users. One of the two algorithms reduces search complexity without any reduction in the angular resolution of the estimated angles. This is done through selection of active antennas in the uniform planar array to make it sparse without creating angle ambiguity. The second method improves the angular resolution in estimating the angles through reduction in the subspace leakage that occurs between the signal and noise subspace. Numerical simulations prove the proposed two algorithms producing a high angular resolution with reduced complexity.

Optimize Cellular Network Performance Using Phased Arrays

In conventional telecommunication systems, the base station does not know the user equipment location; it broadcast in all directions to fully cover the entire cell area. This represents power waste in addition to transmitting the signal in directions where users do not exist, which seen as interference for co-channel cells. This reduces SNR that limits the capacity and impedes the use of the spectrum effectively. This consideration led to the use of smart antenna (SA) technology that uses the Space-division multiple access (SDMA technique, Based on extracting spatial data for users within the network. In this work, Phased Arrays are used to improve the performance of the GSM network in terms of (decrease power, raise coverage, increase capacity, reduce co-channel interference) with the comparison to conventional antennas. Simulation has studied and realized using Matlab, simulation results, and performances have presented. Introduction.

Research on Smart Antenna System Based on Beamforming Algorithm

As the most important element of mobile communication, antenna is the component that radiates and receives electromagnetic waves.The performance of the antenna plays a very important role in the overall performance of mobile communications.Due to the increase in user demand, mobile communication systems are increasingly demanding antennas.In this paper, the composition and principle of the smart antenna system are analyzed. The smart antenna system is composed of an antenna array, a group of beam forming networks and algorithms. Compared with the antenna of the traditional antenna, it has no interference between signals and reduces. The characteristics of external interference and noise, and improved signal coverage, the research results show that smart antenna technology will provide the best service for future mobile communications.

Intelligent Traffic-Lights Management by Exploiting Smart Antenna Technology (ITSAT)

Existing traffic lights’ timings and switching patterns do not operate with real-time traffic conditions. This results in wastage of time, fuel, and higher emission of CO2. This paper proposes an intelligent traffic-lights management system by exploiting Smart Antenna Technology (already installed on cellular Base Stations). With the proposed approach, the traffic lights’ duration adapts to the real-time traffic flow. Our proposed approach does not delve into improvements of Smart Antenna Technology but suggests to extract cell-phones’ location information, which translates it into traffic density and use the information to control traffic lights’ timings. The work is based on the assumption that the cell-phones density corresponds to the vehicles’ density on the roadways. We also propose a Notifier integrated into the TDC. It alerts the driver about the signal transition from red to green, and thus helps drivers use their cell phones serenely for the transitory duration the light stays the red. The analysis shows that the proposed approach not only improves the Average Waiting Time (AWT) by 59.3% but also saves 3.42 gallons of fuel, and reduces CO2 emission by 67 pounds per year for each commuter.

Green-Initiative for Realizing Adaptive Traffic-Signals by Exploiting Smart-Antenna Technology (GREATEST)

Traffic signals control and coordination is a critical function on today's busy roadways. Typical traffic signals have been shifting from fixed cycle timing to the adaptive cycling regime using variety of sensors. However, several shortcomings such as; a vehicle approaching the signal needs to be at certain fix positon from sensor, sensitivity of sensors, and requirement of direct communication between vehicle and traffic light etc., are identified in the existing sensors based approaches. We propose a technique for realizing adaptive traffic signal timing by exploiting Direction of Arrival (DOA) and Timing Advance (TADV) information transmitted from cell-phones, carried by the car drivers and passengers, to Smart Antenna installed on cellular base stations. The simulation results based on a simplified traffic scenario show that the proposed method offers an overall eleven-percent improvement in travel time and thirty-four-percent reduction in vehicle Red-light wait time.

Defected waveguide structure designs and characteristics

AbstractThis article presented defected waveguide structure (DWS) designs and characteristics with microstrip‐fed circular monopole antenna for ultrawideband applications. Typically, waveguide is often designed and employed as antenna and filter application in its rigid dimension. The reconfigurable design toward the waveguide in terms of structural alteration with DWS was found less concerned among researchers although defected ground structure and defected microstrip structure have been applied widely. The motivation of this article was to propose the different DWS designs and characteristics in terms of the S‐parameters result. DWS in basic square geometry with different configurations of straight lines were introduced and compared with FR4 substrate waveguide. Simulated S‐parameters results were modeled in terms of equivalent circuit and measured for validation. For practical measurement, waveguide ports at both open‐ended surface of waveguide were replaced by the monopole antenna. For the modeled S‐parameters results, the square DWS design and square DWS with horizontal straight lines showed quite similar characteristics with higher S11 and lower S21 above frequency 9 GHz. Whereas square DWS with vertical straight lines and square DWS with both horizontal vertical straight lines showed higher S11 and lower S21 below frequency 3.5 GHz. Square DWS with vertical straight lines achieved the lowest S21 around −70 dB below 3.5 GHz and lower S21 around −50 dB at frequency 10.3 GHz. Thus, DWS is proposed for the future smart antenna technology as it can be further modified to meet the different requirements without changing the antenna configuration.

Implementation of 4x4 Mimo with Zigbee

MIMO (multiple inputs, multiple outputs) is an antenna technology for wireless communications in which multiple antennas are used at both the source (transmitter) and the destination (receiver). The antennas at each end of the communications circuit are combined to minimize errors and optimize data speed. MIMO is one of several forms of smart antenna technology, the others being MISO (multiple inputs, single output) and SIMO (single input, multiple outputs). In conventional wireless communications, a single antenna is used at the source, and another single antenna is used at the destination. In some cases, this gives rise to problems with multipath effects. In digital communications systems such as wireless Internet, it can cause a reduction in data speed and an increase in the number of errors. The use of two or more antennas, along with the transmission of multiple signals (one for each antenna) at the source and the destination, eliminates the trouble caused by multipath wave propagation, and can even take advantage of this effect.This was only the first step as system then started to utilize the multipath propagation to advantage, turning the additional signal paths effectively be considered as additional channels to carry additional data.

Angle of Arrival Estimation in Smart Antenna for Wireless Communication

Smart antenna technology has emerged as one of the most efficient techniques in supporting maximum communication link throughput. A smart antenna system with innovative signal processing can enhance the resolution of a signal’s direction of arrival estimation. Successful design of Smart antenna is dependent on the efficient performance of DOA estimation algorithm as well as beamforming algorithm. This paper presents a comparative performance study between Classical Beam forming method, MUSIC (Multiple Signal Classification), MVDR (Minimum Variance Distortion less Response) which are different direction of arrival algorithms used in linear antenna array. The objective is to analyse and compare these algorithms and determine which provides maximum efficiency.

Application of Smart Antenna in TD - SCDMA

With the rapid development of global communications business, future personal communication wireless mobile communicationtechnology has aroused great concern. Way to eliminate the impact of co-channel interference (CCI), multiple access interference (MAI)and multipath fading becomes a major factor in improving the performance of wireless mobile communication systems. The smart antennauses the digital signal processing technology to generate the spatial directional beam so that the antenna main beam is aligned with thedirection of arrival of the user signal. The side lobe or the zero point is aligned to the direction of the interfering signal to reach the fullefficient use of the mobile subscriber signal, thus remove or suppress the interference signal purpose. Compared with other increasinglydeep and mature interference removal technology, the application of smart antenna technology in mobile communication is even more in theascendant and showing great potential. One of the key technologies of the third generation mobile communication standard TD-SCDMAsystem submitted by our country is the intelligent antenna technology. The paper introduces the history and development of the smartantenna in detail, and deeply analyzes the application of the smart antenna in TD-SCDMA. The application of smart antenna has beendeveloped.

Design of thinned fractal antenna arrays for adaptive beam forming and sidelobe reduction

This study introduces, for the first time, a new design methodology that combines the unique multi-band features of thinned fractal antenna arrays with the adaptive beamforming requirements. The major challenges of fractal array design are the high sidelobe level (SLL), the huge number of elements at higher-growth stages, and the radiation pattern synthesis. In this study, the ant colony optimisation algorithm is utilised for thinning fractal arrays by estimating the optimum combination of ‘on’ and ‘off’ elements corresponding to lowest possible SLL, while the least mean square algorithm is investigated as an adaptive beamforming method in the proposed design. The capability of the proposed design is demonstrated by investigating hexagonal and pentagonal fractal antenna arrays under various parameter regimes. The results show that the proposed design is much superior in terms of multi-band frequency operation, array element reduction, and beamforming accuracy. This reveals the effectiveness of the proposed technique as a promising design in smart antenna technology.

Downlink Massive MIMO Systems: Achievable Sum Rates and Energy Efficiency Perspective for Future 5G Systems

To meet up with the ever increasing subscribers' demand for higher data rates and mobile data traffic growth in the telecommunication industry, the fifth generation (5G) systems is being considered for the next future cellular communication standards. The two principal design requirements being aimed at in 5G are robust data transmission rates in Gigabits and low power consumption systems. Massive multiple input multiple output (M-MIMO) technology is an evolving smart antenna technology which has some key promising potentials to boost 5G networks in meeting the aforementioned requirements. However, there is an emergent concern that increased number of antenna arrays in M-MIMO system could induce high power consumption and poor energy efficiency when deployed at the base stations (BSs). Also, inter-cellular interference which occurs as a result of pilot contamination, fast fading and uncorrelated noise effects in the radio channels are other open issues in M-MIMO system. This work investigates and compare the achievable sum rates and energy efficiency of a downlink single cell M-MIMO systems utilizing linear and nonlinear precoding schemes. First, we have shown how the increasing signal-to-noise ratio and M-antennas impact the achievable sum rates. Furthermore, the energy saving potentials of M-MIMO systems in macro, micro and pico cellular environments when linear and nonlinear precoding schemes are utilized at the BS have been demonstrated. Particularly, by means of power fairness index, the tradeoff among the energy efficiency, sum rate and the system users have also been presented and discussed. Results show that substantial energy efficiency improvements can be achieved in micro and pico cellular environments of downlink M-MIMO systems when non-linear successive interference cancellation precoding is applied compared to linear precoding schemes.

Link Estimation in Robot Networks for Multi-Radio Control and Range Extension

Several existing and emerging robotic applications such as ordnance disposal, disaster assessment, and search-and-rescue require high-speed communication links to span large distances. Path loss, combined with other wireless propagation effects, makes this a challenging problem. Directing radio frequency (RF) transmissions toward the intended receiver can mitigate this issue; however, operating smart antenna technology is costly for resource-constrained robots, and its performance degrades in light-of-sight (LOS) conditions, which is common in outdoor scenarios. In order to overcome this challenge, we propose adding a secondary radio, combined with a passive reflector, which is only employed when the primary omnidirectional radio is deemed unreliable. The dynamic switching of the directional radio between sleep and idle states provides communication diversity, while striving to conserve energy for battery-powered systems. An efficient link quality (LQ) estimator based on fuzzy logic provides the intelligence necessary to perform the radio switching action. Our method of passively assessing LQ at the transmitter is shown to be more efficient and agile than other presented LQ estimators, while still remaining effective in dynamic environments.

UNIFORM AND CONCENTRIC CIRCULAR ANTENNA ARRAYS SYNTHESIS FOR SMART ANTENNA SYSTEMS USING ARTIFICIAL NEURAL NETWORK ALGORITHM

Recently, researchers were interested in neural algorithms for optimization problems for several communication systems. This paper shows a novel algorithm based on neural technique presented to enhance the performance analysis of beam-forming in smart antenna technology using N elements for Uniform Circular Array (UCA) and Concentric Circular Array (CCA) geometries. To demonstrate the effectiveness and reliability of the proposed approach, simulation results are carried out in MATLAB. The radiators are considered isotropic, and hence mutual coupling effects are ignored. The proposed array shows a considerable improvement against the existing structures in terms of 3-D scanning, size, directivity, HPBW and SLL reduction. The results show that multilayer feed-forward neural networks are robust and can solve complex antenna problems. However, artificial neural network (ANN) is able to generate very fast the results of synthesis by using generalization with early stopping method. Important gain in the running time and memory used is obtained using this latter method for improving generalization (called early stopping). To validate this work, several examples are shown.