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In contemporary radar technology, the observation and detection of objects with low radar cross-sections remains a significant challenge. A multi-functional radar model employing a digital phased array antenna system offers notable advantages over traditional radar in addressing this issue. Nonetheless, to fully capitalize on these benefits, improving the structure of the receiving path in digital transceiver modules is crucial. A method for improving the digital receiving path model by implementing a matched filter approach is introduced. Given that the return signals from objects are often lower than the internal noise, the analog part of the digital transceiver modules must ensure that its dynamic range aligns with the level of this noise and the weak signal. The output signal level of the analog part must correspond to the allowable input range of the analog-to-digital converter. Improvements in the receiving path to achieve a fully matched model can reduce errors in the phase parameters and amplitudes of the useful signal at the output. The simulation results presented in this paper demonstrate a reduction in amplitude error by approximately 1 dB and a phase error exceeding 1.5 degrees for the desired signal at the output of each receiving path. Consequently, these improvements are expected to enhance the overall quality and efficiency of the spatial and temporal accumulation processes in the digital phased array antenna system. Furthermore, to maintain the matched filter model, we also propose incorporating an adaptive "pseudo-expansion" of the linear gain range. This involves adding a feedback stage with an automatic and adaptive bias voltage adjustment for the intermediate-frequency preamplifier in the analog part of the receiving path. Simulations to qualitatively verify the validity of this proposal are conducted using data from practical operational radar system models. [ABSTRACT FROM AUTHOR]

The rapid development of wireless technology has heightened the requirement for antenna performance. Traditional antennas, characterized by their static performance, are no longer sufficient to accommodate the dynamic requirements of modern wireless systems. The advent of reconfigurable antennas has opened new horizons for unleashing the full potential of wireless communication systems. These antennas are versatile and can switch various performance modes in a simple yet ingenious structure. Based on the cutting‐edge research, this paper deeply explores their core design principles, the latest breakthroughs, and the ingenious methods. Through an in‐depth analysis of a multitude of reconfigurable antenna design cases, existing design methods are categorized into four categories: electronic and optical switches, structural physical change, smart materials, and bistable composites. Each category is subjected to a meticulous dissection, revealing the underlying design mechanisms, highlighting innovativeness, and discussing both the strengths and limitations. Furthermore, by conducting a comprehensive comparative analysis, this paper concludes the forthcoming challenges and prospective trajectories for this research domain. Therefore, this paper can serve as a valuable reference for researchers seeking to deepen their understanding and application of various reconfiguration methods in the design of reconfigurable antennas, guiding them toward the forefront of antenna technology innovation. [ABSTRACT FROM AUTHOR]

The efficacy of meta-heuristic algorithms has been demonstrated in solving unconstrained optimization problems. Inspired by the food foraging behavior of beetles, we propose herein a model-free meta-heuristic optimization algorithm, referred to as the Beetle Antennae Search-Bellwether Swarm, which incorporates the schemes of adaptive antenna fiber length and direction vector. A joint annealing-heating scheme along with the re-initialization mechanism is proposed such that each antenna fiber length could simultaneously gradually decrease or increase in different circumstances. We also propose to adapt each individual antenna fiber length based on the best smell perception direction (bellwether). The proposed schemes of adaptive antenna fiber length yield the algorithm almost insusceptible to different initial antenna fiber lengths for a relatively large range of initial antenna fiber lengths. The softmax combiner is leveraged to obtain the direction vector such that the beetle would be steered to step toward the new randomly combined direction and arrive at a candidate position. The beetle position is further updated by evaluating whether the candidate position is conducive to minimizing the objective function. The illustrative simulations demonstrate the fast initial convergence, cost-effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

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This review offers an extensive examination of the evolving landscape of Long Range (LoRa) Microstrip Patch Antennas (MPAs), highlighting their crucial role in optimizing LoRa systems within the Internet of Things (IoT). As the demand for energy-efficient standards like LoRa grows with the expanding IoT market, this research becomes increasingly relevant. This comprehensive review, the first of its kind, serves as a foundational resource for researchers seeking to optimize LoRa systems within the IoT. The study has categorized these LoRa MPAs – including monopole, Planar Inverted F Antenna (PIFA), dipole, yagi-uda, and array – into single band, dual-band, multiband, and wearable antennas, thus providing substantial viewpoints on their diverse design architectures and performance characteristics. Through systematic tabulation, the review facilitates a thorough comparison of antenna advancements. Notably, the review addresses inherent challenges in LoRa MPAs, emphasizing critical aspects that necessitate attention, including the need for miniaturization and integration, advancements in substrate materials and fabrication techniques, and the imperative for reconfigurable and adaptive antennas. Various approaches to enhance antenna performance are explored, including the metamaterial incorporation, slot-based enhancements, Electromagnetic Band Gap (EBG), dielectric resonator antennas (DRAs), substrate material considerations, and corrugation techniques. Looking ahead, the paper explores the future trends and subtle considerations that are poised to shape the trajectory of LoRa MPAs. To the best of our knowledge, this paper represents the first comprehensive review on the multifaceted topic of LoRa MPAs, serving as a foundational resource for researchers in the field. [ABSTRACT FROM AUTHOR]

In this paper, a new simple practical technique for controlling the element excitation amplitudes of the array feeding network is presented. To implement this novel idea, an array with four rectangular microstrip patches operated at 3.25 GHz is fabricated. Genetic algorithm was used to determine the optimum excitation amplitudes of these four patches such that its array pattern has a minimum sidelobe level. An Arduino microcontroller was used to apply the optimized excitation amplitudes via programmable digital attenuators that connected to each adjustable element. Measured results show that the peak sidelobe level in the designed array pattern was reduced from -13.2 dB to more than -26 dB which is practically sufficient to eliminate the effect of any interfering signals. More important, the main beam and the directivity are not much affected by the sidelobe reduction. Thus, the technique is practically effective and it can be easily used in designing the adaptive beamforming antenna arrays for 5G and beyond wireless applications. [ABSTRACT FROM AUTHOR]

This paper proposes a power scaling (PS) technique aimed at mitigating the outage floor problem commonly encountered in multi-user full-duplex (FD) non-orthogonal multiple access (NOMA) systems. Two antenna modes denominated as adaptive antenna mode (AAM) and fixed antenna mode (FAM) are utilized in this work for L FD near users in close proximity. In addition, a combined method of selecting both antenna mode and near user integrated with PS is employed to improve the overall network performance. Moreover, a power allocation between the chosen near user and far user is considered. In the low-to-moderate power regions, by AAM and FAM, we achieve twice of full diversity gain and full diversity gain, respectively. The research presents mathematical expressions for deriving the average capacity and outage probability and supports the theoretical findings with simulation-based evidence. The results of this work show that PS method not only contributes to a greater spatial diversity but also leads to superior performance compared to traditional FD NOMA systems. Moreover, our proposed method overcomes the outage floor and capacity ceiling. Furthermore, the work can be developed to 6G massive MIMO technology in multi-user FD cooperative NOMA systems. [ABSTRACT FROM AUTHOR]

Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in situ radiation measurements resulting in site-customized antenna design and positioning, and consequently in a higher reliability of such HF grid communications. Drone-borne measuring systems are already known as a flexible solution, but are mostly restricted to higher frequency ranges where full-wave, wide-band probes are feasible. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity; corrections on these two effects are the key methodological steps. We show that despite a realized gain figure in the order of −20 dBi, such a probe can provide stable results for near-field measurements, even at input power levels as low as 1 mW. Compared to other similar approaches, our configuration provides a wider frequency band of operation, higher stability in terms of pattern diagram, and a lower cost. [ABSTRACT FROM AUTHOR]

Antennas play a crucial role in designing an efficient communication system. However, reducing the maximum sidelobe level (SLL) of the beam pattern is a crucial challenge in antenna arrays. Pattern synthesis in smart antennas is a major area of research because of its widespread application across various radar and communication systems. This paper presents an effective technique to minimize the SLL and thus improve the radiation pattern of the linear antenna array (LAA) using the chaotic inertia-weighted Wild Horse optimization (IERWHO) algorithm. The wild horse optimizer (WHO) is a new metaheuristic algorithm based on the social behavior of wild horses. The IERWHO algorithm is an improved Wild Horse optimization (WHO) algorithm that combines the concepts of chaotic sequence factor, nonlinear factor, and inertia weights factor. In this paper, the method is applied for the first time in antenna array synthesis by optimizing parameters such as inter-element spacing and excitation to minimize the SLL while keeping other constraints within the boundary limits, while ensuring that the performance is not affected. For performance evaluation, the simulation tests include 12 benchmark test functions and 12 test functions to verify the effectiveness of the improvement strategies. According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization. [ABSTRACT FROM AUTHOR]

A unique multiple-input-multiple-output (MIMO) adaptive intelligent antenna for vehicular communications is addressed in this article. It has a high degree of transparency that can be integrated with the windscreen for intelligent vehicular communications. The proposed diversity antenna has four monopole radiators oriented in orthogonal directions to obtain polarisation diversity. The optically transparent nature is realised using a soda-lime substratum of size 50 × 50 mm2 coated with Transparent Conductive Oxides (TCO). The Aluminium Zinc Oxide (AZO) is sputtered on top of a Fluorine Tin Oxide (FTO) to enhance the material's conductivity with dual-conductive layer. The fabricated MIMO antenna has a bandwidth of 10 GHz and functions in the entire UWB range (2 to 12 GHz). By incorporating concentric circles into the ground, high confinement between nearly located antenna elements is achieved. The antenna has a peak gain of 2.9 dBi as measured. The Envelope Correlation Coefficient (ECC) of the antenna in the entire Ultra-wideband (UWB) region attributed to the TCO material shows a very low correlation among the antenna elements. Because of diversity gain of the proposed vehicular antenna is ˃ 9.8 dB, it can also operate with low transmission power. The findings indicate that the antenna is pertinent for current intelligent vehicles that require multiple communications without aesthetic hindrance. [ABSTRACT FROM AUTHOR]

The design of arrays capable of receiving wideband signals differs from arrays that can only receive narrowband signals. These arrays must be able to receive signals with an instant bandwidth of several GHz across the entire operating frequency, such as High‐Resolution Radars or Terahertz in 6G communication systems. In these arrays, using a time delay line structure leads to an increase in beamformer coefficients, resulting in high computational complexity. This poses a challenge for beamforming in wideband systems. Additionally, classic Wideband beamformers face other factors, such as poor performance in the presence of input direction of arrival error, array calibration error, and requiring too many snapshots to reach the steady state of the beamformer. Therefore, the robustness of wideband adaptive beamforming using deep unfolding model‐based technique is focused on, which has not been discussed before. The advent of deep unfolding, an innovative technique, amalgamates iterative optimization approaches with elements of neural networks. The aim is to deftly maneuver through various tasks across disciplines such as machine learning, signal and image processing, and telecommunication systems. Also, the network training method is done to become more robust against the mentioned factors. In the proposed structure, the constraints of the previous methods have been evaluated. It is observed to have better performance compared to other classic algorithms. Also, with the investigations of the proposed method with other conventional deep learning methods, it was observed that in some cases the proposed structure performance is equal to the conventional deep learning method and sometimes better. [ABSTRACT FROM AUTHOR]

This research paper covers a comprehensive investigation into the design, analysis, and performance evaluation of frequency reconfigurable antennas. The relentless advancement of wireless communication technology has necessitated the development of antennas that can adapt seamlessly to a wide range of operating frequencies. The proposed antenna design incorporates a circular ring configuration with a PIN diode for dynamic frequency tuning. The reconfigurable element allows for versatile operation across multiple frequency bands, avoiding the requirement for separate antennas and simplifying system integration. The performance evaluation encompasses key parameters such as radiation pattern, gain, bandwidth, and efficiency, assuring optimal performance across the specified frequency range. The measured and simulated results validate the accuracy and effectiveness of the recommended structure. The research findings contribute to the state-of-the-art advancements in frequency reconfigurable antenna engineering, enabling efficient wireless communication systems for several applications, such as cellular networks, WLANs, satellite communication systems, and cognitive radio networks. [ABSTRACT FROM AUTHOR]

Smart antenna and digital antenna systems are considered as a crucial technology for current and future communication systems supporting 5G/6G and nonterrestrial‐networks communications. Based on the information of the received signal/s, smart antenna systems toward the radiation pattern to the desired direction/s. This technique is known as adaptive beamforming. The theories and the applications of adaptive beamforming are taught in engineering educational courses. This paper proposes a set of real‐time interactive experiments for adaptive beamforming algorithms in antenna array processing subject. The proposed experiments can be performed with the computer‐aided experimental studies tool prepared in the MATLAB® environment. The users can easily make comparisons and can perform trade‐offs between different types of adaptive beamforming algorithms, scenarios, and antenna architecture. This is used as a teaching tool for a graduate course on adaptive beamforming algorithms. [ABSTRACT FROM AUTHOR]

Fast radio bursts (FRBs) are extraordinary astrophysical phenomena characterized by short radio pulses that last only a few milliseconds, yet their power can surpass that of 500 million suns. To date, most detected FRBs originate from beyond our galaxy. However, if an FRB were to originate within the Milky Way, it could be detected using small antennas. In this paper, we propose a compact and ad-hoc antenna array designed for the efficient detection and localization of FRBs within the Milky Way. The antenna operates within the 1200–1800 MHz range and consists of three sub-arrays placed in an L-shape for source localization, occupying a total volume of 8 0 × 2 5 × 6 cm 3 . Each sub-array consists of 4 miniaturized, dual-polarized, half-space radiation antenna elements, forming a one-dimensional array that allows shaping the radiation pattern to match the form of the Milky Way without exhibiting grating lobes. A prototype was constructed and characterized to validate the design. The measured results exhibit good agreement with the simulations. In addition to having a custom elongated radiation pattern, the array has attractive merits, such as low reflections at the input ports, high radiation efficiency, and a distribution that inhibits the existence of phase ambiguities, thus facilitating source localization. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks are self-organizing networks that do not rely on fixed infrastructure. Smart antennas employ advanced beamforming technology, enabling ultra-long-range directional transmission in wireless networks, which leads to lower power consumption and better utilization of spatial resources. The media access control (MAC) protocol design using smart antennas can lead to efficient usage of channel resources. However, during ultra-long-distance transmissions, there may be significant transport delays. In addition, when using the time division multiple access (TDMA) schemes, it can be difficult to manage conflicts arising from adjacent time slot advancement caused by latency compensation in ultra-long-range propagation. Directional transmission and reception can also cause interference between links that reuse the same time slot. This paper proposes a new distributed dynamic TDMA protocol called State Interaction-based Slot Allocation Protocol (SISAP) to address these issues. This protocol is based on slot states and includes TDMA frame structure, slot allocation process, interference self-avoidance strategy, and slot allocation algorithms. According to the simulation results, the MAC layer design scheme suggested in this paper can achieve ultra-long-distance transmission without conflicts. Additionally, it can reduce the interference between links while space multiplexing. Furthermore, the system exhibits remarkable performance in various network aspects, such as throughput and link delay. [ABSTRACT FROM AUTHOR]

In the landscape of wireless communication, smart antennas, or adaptive array antennas, have emerged as vital components, offering heightened gains and spectral efficiency in advanced communication systems such as 5G and beyond. However, augmenting network coverage, capacity, and quality of service remains a pressing concern amid advancing communication technologies and escalating user demands. Array antennas with reduced sidelobe levels, high directivity, and increased beam steering capabilities are sought after to address these challenges. This paper explores convex optimization as a potent tool for array synthesis problems, offering robust performance and solution efficiency. By formulating optimization problems as convex programming, sidelobe reduction challenges can be efficiently addressed. The paper presents a comprehensive investigation into convex optimization-based approaches for array pattern nulling, assessing their performance and computational efficiency in various scenarios. Numerical examples demonstrate the efficacy of the proposed methods in maintaining the main lobe, controlling sidelobe levels, and placing nulls at interfering directions, thereby advancing the state-of-the-art in smart antenna technology. [ABSTRACT FROM AUTHOR]

The process of smart antenna synthesis involves the automatic selection of the optimal antenna type and geometry in order to enhance antenna performance. A model for intelligent antenna selection employs an optimizable K-nearest neighbors (KNN) classifier to determine the optimal antenna choice. To optimize the utilization of different learner types, the geometric parameters of the antenna are presented as the final step prior to the construction of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model, which involves the integration of five distinct primary learners. The classification of three distinct types of antennas, namely helical antenna, pyramidal horn antenna, and rectangular patch antenna, is performed using an optimizable K-nearest neighbors (KNN) classifier. Additionally, an ANFIS approach is employed to determine the optimal size parameters for each antenna. The accuracy is used to evaluate the performance of an optimizable KNN classifier, whereas Mean Squared Error and Mean Absolute Percentage Error are used to evaluate the performance of an ANFIS. The proposed technique demonstrates high performance in parameter prediction and antenna categorization, achieving a Mean Absolute Percentage Error of less than 3% and an accuracy exceeding 99.16%. The recommended methodology holds significant potential for widespread application in the development of practical smart antennas. [ABSTRACT FROM AUTHOR]

The increasing need for high-speed telecommunications has motivated extensive research on fifth-generation (5G) technology. Many industries require quick data throughput, low latency, and consistent radiation patterns utilizing 5G techniques. This article proposes an antenna with two simulations and measurements for different 5G applications. It is tiny and operates at a wide frequency range of 1 to 9 GHz, making it suitable for various modern systems. The results obtained from this antenna were superior to those proposed in previous articles. It is observed that the reflection coefficient ratio is much less than -10 dB for both the simulation and measurement sides at all frequencies. In addition, the highest value of the reflection coefficient is -82 dB at 8 GHz. The antenna's maximum gain and efficiency are 9.8 dB and 98%, respectively. Thus, the best antenna performance when measuring the voltage standing wave ratio (VSWR) parameter at 8 GHz is up to 0.3. It has been discovered that the measured radiation pattern is nearly omnidirectional and matches the simulated radiation pattern exactly. The discrepancies between the design proposed and the authors' designs in other recent works are that it is based on a spatial and aperture technique for both the patch and ground layers. Therefore, the antenna achieved good results of wide bandwidth, high efficiency, gain, etc. Furthermore, it has been concluded that the antenna is well-suited for many applications within the 5G Internet of Things (IoT) ecosystem. [ABSTRACT FROM AUTHOR]

The growing interest of the scientific community in surveying and monitoring submerged assets is motivated by the increasing demand for high-resolution products with certified accuracies. While many instrumental and methodological solutions for documenting, monitoring, and studying archaeological and cultural heritage through geomatics techniques are already available for the terrestrial environment, the challenge remains open to the underwater context. High-resolution capability and accurate positioning are still difficult to achieve in these environments. This paper discusses the limitations of positioning and georeferencing techniques in the underwater environment. It explores how existing methods and new instruments can be used to perform accurate topographic surveys of ground control points (GCPs) in very shallow waters (within 5 m depths), which can support the photogrammetric reconstruction of underwater assets. This research presents two innovative prototypes: a self-built plastic marker for topographic use in the underwater environment and a self-built aluminum pole for topographic use in the marine environment. The prototypes are tested and validated with a tilt-compensating smart antenna to reduce planar and altimetric errors when the pole is not perfectly level and to work independently of the shore proximity required when using a total station to perform said measurements. [ABSTRACT FROM AUTHOR]

The paper examines the application of adaptive antennas in wireless communication systems with particular attention to how well they can transmit and receive signals by dynamically adjusting radiation patterns. The review covers a range of artificial intelligence (AI) approaches that have been used to enhance adaptive antenna performance in beamforming, channel estimation, interference mitigation, and spectrum utilization. Besides adaptive antennas' potential to improve wireless communication systems, the paper also discusses their limitations, including computational complexity, interference sensitivity, and the significance of precise channel state information (CSI) estimates. [ABSTRACT FROM AUTHOR]

In order to improve the communication quality and transmission rate of WLAN, the key technologies of smart antenna in WLAN based on adaptive array are proposed. The adaptive array is used to suppress the WLAN interference signal, and the feedback from the output is used to adjust the weight loaded on the signal, and the optimal weight corresponding to the linear constraint minimum variance is obtained to achieve beamforming optimization. On this basis, the optimal antenna selection algorithm and the sub-optimal antenna selection algorithm are designed, and the sub-channel matrix with the maximum capacity can be obtained by repeated iterative calculation, so as to realize the smart antenna selection and further optimize the performance of WLAN. Experimental results show that the smart antenna signal has 100% coverage in WLAN compared with conventional methods. When the transmission rate is greater than 35 mb/s, the delay of the study method is not jitter compared to the contrast method. When the transmission rate is greater than 35 mb/s, the packet loss rate of the proposed method remains stable, while the packet loss rate of the two comparison methods begins to increase. When the transmission rate is greater than 12 mb/s, the throughput of the proposed method is more stable than the other methods. In conclusion, this method has the characteristics of large signal coverage, low delay, low packet loss rate and high throughput, and can be widely used in practice. The contribution of this study is that the weight of the antenna array can be dynamically adjusted through the adaptive algorithm, thus optimizing the quality of the received signal and improving the receiving sensitivity. [ABSTRACT FROM AUTHOR]

The rise of smart antennas made it imperative to use adaptive beam forming, but single-element failure in array antenna disturbs the radiation pattern. Hence, to achieve adaptive beam forming, detecting and locating faults in an antenna array is a must for correction in the radiation pattern. The presented work in this paper provides real-time monitoring and alert for fault occurrence in antenna arrays. Fault detection is performed by an optimized Convolutional Neural Network (CNN), and the Thingspeak web service is utilized to store fault detection information on the cloud to get the visualization of faults. Voice over Internet Protocol (VoIP) Application programming interface (API) provides an alert in real-time once the fault is detected. The filter kernel parameters, number of convolutional layers, and dense layers of the fully connected neural network are tuned to minimize the mean square error (MSE). 16 element (4 × 4) planar microstrip array antenna is simulated on Ansys HFSS, and by introducing discontinuity, i.e. one type of defect in the corporate feed network, a training and testing set of 374 samples considering single element fault are used to train the CNN Model with a 0.3 validation split. Further performance of the same model by changing the last layer of a fully connected layer is evaluated to check the effectiveness of model when two elements are faulty. [ABSTRACT FROM AUTHOR]

In this paper a comparative study, restricted to one-dimensional stationary case, between several Direction of Arrival (DOA) estimation algorithms of narrowband signals is presented. The informative signals are corrupted by an Additive White Gaussian Noise (AWGN), to show the performance of each method by applying directly the algorithms without pre-processing techniques such as forward-backward averaging or spatial smoothing. [ABSTRACT FROM AUTHOR]

With the increase in demand for high data rates and high bandwidth because of multiple users all over the globe, the technology has moved toward the next-generation of wireless communication. This rapid advancement of wireless communication technologies has led to the emergence of 5G networks, which promise significantly higher data rates, lower latency, and enhanced connectivity. Researchers believe that five essential techniques can enable 5G. Beamforming is one of those essentials, as it plays a vital role in achieving reliable and high-capacity communication. This review article portrays a comprehensive analysis of the 5G beam-former Microstrip Patch Antenna array techniques for communication systems. The paper comprises of a deep overview of the fundamental concepts and principles of beamforming, including analog, hybrid, and digital beamforming techniques. It explores the advantages and disadvantages of each approach and discusses their suitability for 5G applications. An in-depth examination of various beamforming techniques employed in 5G, encompassing traditional beamforming, massive Multiple- Input-Multiple-Output beamforming, hybrid beamforming, and adaptive beamforming. The discussion encompasses the strengths, weaknesses, and performance trade-offs of each technique, along with their applicability in diverse deployment scenarios and applications. The review of multiple couplers that are used for the feeding of the antenna is discussed with included hybrid coupler, Wilkinson power divider, branch line coupler, and butler matrix in beamformer smart antenna for 5G/6G communications. Numerous beamforming techniques are compared based on their merits, demerits, and applications. Moreover, the dielectric substrate utilized to design the beamformer was also reviewed. The findings presented in this paper serve as a valuable resource for the researcher, scholars, and engineers working in the field of 5G wireless communications and antenna designing, facilitating the development and deployment of efficient and robust beamforming solutions for future 5G networks. [ABSTRACT FROM AUTHOR]

Space‐time adaptive processing (STAP) array has found extensive use in the global navigation satellite system for interference suppression. Nevertheless, the conventional space‐time array necessitates multiple antennas and time delay taps, resulting in a heavy burden on both hardware and computation resources. Thus, lowering the cost and complexity of STAP becomes a considerable problem demanding prompt solutions. This work designs a space‐time array reconfiguration scheme based on the joint selection strategy of the antenna and delay tap to address this problem. The reconstructed array can induce a high signal to interference plus noise power ratio (SINR) when using fewer antennas and delay taps. The space‐time correlation coefficient (STCC) is first presented to manifest the influence of reconfiguration on output SINR. Then, we formulate the space‐time array reconfiguration mathematical model, aiming to minimise STCC. Two reconfiguration methods are provided to solve the optimal array configuration of antennas and delay taps that can reach the minimum STCC and maximum SINR. The optimal antenna‐delay tap pairs are finally selected to comprise the reconstructed array. Substantial simulation experiments verify that the presented scheme and strategy are effective and reliable in space‐time array reconfiguration. [ABSTRACT FROM AUTHOR]

The generalized sidelobe cancellation (GSC) is a commonly used adaptive beamforming technology, which can be used in antenna arrays. Due to the error of the direction of arrival of the received signal and the spacing error of the received array elements, the signal received by the array antenna has a mismatch of steering vectors, which leads to that the GSC method cannot accurately aim at the expected signal and suppress the interference signal. In order to improve the robustness of GSC algorithm, a new adaptive beamforming algorithm named SGSC (Sequential Quadratic Programming-Generalized Side Lobe Cancellation) is proposed in this paper. In this method, firstly, the mismatching expected signal steering vector is corrected by the stepwise quadratic programming, so that the auxiliary antenna can effectively block the expected signal. Then, the optimal weight vector is obtained by combining the corrected steering vector with the GSC, so that the expected signal components of the auxiliary antenna and of the main antenna can be avoided from being cancelled due to mismatch errors. Finally, the simulation results based on MATLAB show that the new algorithm can point the desired signal more accurately and suppress the interference signal more obviously in the presence of mismatch error, which shows the effectiveness of the method. [ABSTRACT FROM AUTHOR]

In this paper a wide-band, small size and high gain modified patch antenna array and a single element antenna for fifth Generation (5G) millimetre-wave (mm-wave) applications have been presented. The designing of single element antenna and array antenna is based on the Adaptive Neuro-Fuzzy Inference systems (ANFIS). The ANFIS technique is used to estimate the dimensions of the single element as well as the spacing between patch antenna elements in antenna array. The single element's operating frequency is 28 GHz, While the array antenna covers the frequency band from 23.6 to 29.2 GHz, resonating at 25 and 28 GHz. The antenna array was designed and simulated using the Rogers RT duroid 5880 Substrate, which has a dielectric constant of 2.2, a loss tangent tan (δ) of 0.0009, and thickness of 0.508 mm. The proposed single element patch antenna has a size of 4 × 4.8 × 0.508 mm 3 with wideband range from 23 to 38.6 GHz (15.6 GHz) with a gain of 4.17 dB. Based on these properties, the single element is expanded into a six-element array with a compact size of 13.2 × 23.8 × 0.508 mm 3 in order to enhance the gain and to make the antenna radiation pattern directional. The designed antenna array has a wide-band from 23.6 to 29.2GHz (5.6 GHz) and a high gain of 11 dB, making it as strong candidate for future mm-wave applications. [ABSTRACT FROM AUTHOR]

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace. [ABSTRACT FROM AUTHOR]

An important element of modern telecommunications is wireless radio networks, which enable mobile subscribers to access wireless networks. The cell area is divided into independent sectors served by directional antennas. As the number of mobile network subscribers served by a single base station increases, the problem of interference related to the operation of the radio link increases. To minimize the disadvantages of omnidirectional antennas, base stations use antennas with directional radiation characteristics. This solution allows you to optimize the operating conditions of the mobile network in terms of reducing the impact of interference, better managing the frequency spectrum and improving the energy efficiency of the system. The work presents an adaptive antenna algorithm used in mobile telephony. The principle of operation of adaptive systems, the properties of their elements and the configurations in which they are used in practice are described. On this basis, an algorithm for controlling the radiation characteristics of adaptive antennas is presented. The control is carried out using a microprocessor system. The simulation model is described. An algorithm was developed based on the Mathcad mathematical program, and the simulation results of this algorithm, i.e., changes in radiation characteristics as a result of changing the mobile position of subscribers, were presented in the form of selected radiation characteristics charts. [ABSTRACT FROM AUTHOR]

This letter investigates the properties of a novel multi-band fractal antenna with a triangular geometry that can expand its bandwidth, provide multiband functionality, and enable the best smart antenna technology. The antenna employs an FR4 as support with dimensions of 75×75 mm2 and a thickness of 1.6 mm. A microstrip line with an impedance of 50 ohms feeds the patch. The high-frequency structure simulator (HFSS) is applied to develop and simulate the patch. The vector network analyzer AVR ROHDE and SCHWARZ ZVB20 carried out the experimental tests of the prototype antenna. The suggested antenna’s simulation results show that it runs on five main frequency bands: 1.840 GHz, 2.770 GHz, 2.940 GHz, 4.330 GHz, and 5.790 GHz, with a high gain that can exceed 6.01dB and an efficiency of 82%. In the operational bands, the voltage standing wave ratio (VSWR) is between one and two. The results from the simulation and the experiment are extremely similar. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced approach for sound localization is proposed, which fuses automatic extraction of array signal characteristic frequencies and adaptive weighting. The method refines the autoregressive power spectral estimation algorithm and improves density-based spatial clustering of applications with noise algorithm for characteristic frequency extraction. Adaptive weighting technique is introduced to alleviate the problem of frequency mismatch in the localization process. The initial weight of narrowband signals is calculated and normalized using the frequency domain amplitude integration of narrowband signals, followed by adaptive threshold correction to eliminate invalid narrowband signal weights. The adaptive weight vector improves the localization method's accuracy and interference suppression. The effectiveness and universality of the proposed method are demonstrated with test data from dry transformers and pumps, and its applicability is shown to extend to various spatial spectrum estimation algorithms and deep learning-based sound source localization techniques. • Enhanced approach for abnormal machine sound localization developed using automatic extraction and adaptive weighting. • Characteristic frequency extraction improved through refined autoregressive algorithm and density-based clustering. • Frequency mismatch in localization addressed by adaptive weighting technique. • Method's effectiveness validated with test data from various machines. • Applicability demonstrated for different spatial spectrum estimation and deep learning-based localization techniques. [ABSTRACT FROM AUTHOR]

This paper introduces an 8-element linear array designed for adaptive array applications, using least mean square (LMS) algorithm to enhance the directivity of the array. Microstrip antenna has been optimized at 2.3 GHz, a pivotal frequency ranges relevant to 4G and 5G applications. This design is thoughtfully extended to encompass 8-elements, achieved through the art of parameterization using computer simulation technology (CST) microwave studio. This geometry of 8-element exhibits considerable promise, significantly elevating the gain from 6.13 dBi for a single element to an impressive 15.5 dBi for all eight-element array. To further empower the array's adaptability and beam-steering capabilities, the LMS algorithm is simulated. This intelligent algorithm computes complex weights, thoughtfully with various angles, including those for the interested user at 60° and 30°, as well as potential interferers at 10° and 15°, as simulated in MATLAB. These meticulously calculated weights are effectively applied to antenna elements using CST, facilitating beam steering in various directions. During CST simulations, notable peaks in performance emerge at 54° and 28°, strategically aligned with nulls at 10° and 15°. Remarkably, these results exhibit a remarkable degree of concurrence with those obtained through MATLAB simulations, affirming effectiveness of the proposed adaptive array design. [ABSTRACT FROM AUTHOR]

Consider a decode‐and‐forward wireless relay system assisted by an intelligent reflection surface (IRS), where a robust design on receive beamforming at the relay and reflection coefficients at the IRS is studied. The worst‐case signal‐to‐noise ratio maximization problem is formulated, subject to the reflection coefficients (with either continuous or discrete phases) constraints, under the assumption of imperfect channel state information for all channels. To cope with the hard problem, an equivalent nonconvex quadratic optimization problem with a simpler form is derived, and then the Cauchy‐Schwarz inequality is applied to update the beamforming and a cyclic process is proposed to update the reflection coefficients, where a closed‐form optimal solution is computed in each step. It turns out that the proposed algorithm achieves a locally optimal solution for the robust design problem. Simulation results show that the proposed robust design outperforms an existing non‐robust design and two robust designs via semidefinite relaxation technique. [ABSTRACT FROM AUTHOR]

Adaptive antenna arrays are widely used to protect Global Navigation Satellite System (GNSS) receivers from interference. However, conventional blind anti-jamming array processing methods can cause satellite signal attenuation, which reduces signal tracking precision and measurement accuracy. To alleviate this problem, this paper proposes the noncoherent channel combining method for GNSS signal tracking with an adaptive antenna array. A two-stage processing architecture is applied in the proposed method, where the first stage implements interference suppression, and the second stage achieves noncoherent channel combining. The proposed method has the advantage of blind characteristics that can be implemented without any other auxiliary information. It also reveals a unified processing architecture for anti-jamming array processing methods. Thus, a detailed comparison and analysis of the proposed method with several typical blind anti-jamming methods is performed. Simulation results demonstrate the effectiveness of the proposed method and its superiority over existing methods in terms of tracking performance. [ABSTRACT FROM AUTHOR]

Estimating the direction of arrival (DOA) is crucial for signal localization in various applications including wireless communications, mobile communications, radar, sonar, and smart antenna technology. This study investigates the performance of the MUSIC (Multiple Signal Classification) and CAPON algorithms for DOA estimation utilizing different array geometries. The incorporation of sparse arrays aims to enhance DOA estimation performance in terms of robustness (addressing mutual coupling effects) and degrees of freedom (resolving sources as effectively as possible with the same number of array elements). Through simulations, we compare the DOA estimation performance of various arrays, such as Uniform Linear Array (ULA), Coprime, Cascaded, and Nested arrays. Additionally, we demonstrate that the choice of array geometry can impact the performance of DOA algorithms. The results present pseudo spectra for DOA estimation methods across all considered array configurations. This study endeavors to identify the algorithm that delivers superior accuracy across different array configurations, which holds significant implications for practical applications requiring precise DOA estimation. [ABSTRACT FROM AUTHOR]

Autonomous remote sensing systems establish communication links between nodes. Ensuring coverage and seamless communication in highly dense environments is not a trivial task as localization, separation, and tracking of targets, as well as interference suppression, are challenging. Therefore, smart antenna systems fulfill these requirements by employing beamforming algorithms and are considered a key technology for autonomous remote sensing applications. Among many beamforming algorithms, the recursive least square (RLS) algorithm has proven superior convergence and convergence rate performances. However, the tracking performance of RLS degrades in the case of dynamic targets. The forgetting factor in RLS needs to be updated constantly for fast target tracking. Additionally, multiple beamforming algorithms can be combined to increase tracking performance. An improved hybrid constant modulus RLS beamforming algorithm with an adaptive forgetting factor and a variable regularization factor is proposed. The forgetting factor is updated using the low-complexity yet robust adaptive moment estimation method (ADAM). The sliding-window technique is applied to the proposed algorithm to mitigate the steady-state noise. The proposed algorithm is compared with existing RLS-based algorithms in terms of convergence, convergence rate, and computational complexity. Based on the results, the proposed algorithm has at least 10 times better convergence (accuracy) and a convergence rate two times faster than the compared RLS-based algorithms. [ABSTRACT FROM AUTHOR]

Since the software‐defined radio digital beamforming (DBF) system is the newest tendency in fifth‐generation (5G) development and based on its flexibility applied to antenna arrays, this research paper presents a smart antenna array architecture operating in C‐band (3.48 GHz). In developing DBF for 5G access points with beamforming capacities, it is first necessary to perform an accurate approach that identifies the position of the desired user and affects the beamforming processing. In this article, a feasible approach is represented to evaluate and test three angle‐of‐arrival algorithms. To ensure the robustness of the system, the system structure with its four main components, the transmit subsystem, the synchronization subsystem, the receive subsystem, and data processing are described in detail. This article presents a reasonably inexpensive prototype DBF in conjunction with a Universal Software Radio Peripheral B210 board. Experimental measurements and results confirm the suggested methodology. [ABSTRACT FROM AUTHOR]

Receiver channels amplitude and phase calibration in smart antennas is a crucial process to achieve the systems requirement. The implementation of these functions in a programmable device and the procedures for selecting its parameters is not a widely disseminated topic in the specialized literature. This work solves the previous problem by implementing the calibration algorithm in FPGA based on the requirements to guarantee the estimation of the direction of arrival (DOA) with super resolution. The design implemented in Hardware Description Language (HDL) corrects in real time the amplitude and phase errors between channels of the multichannel reception system with low latency and resource consumption. Experimental verification with real signals demonstrates that the errors obtained after calibration are within the expected range and corroborates the effectiveness of the design. [ABSTRACT FROM AUTHOR]

To improve radio access capability, sky connections relying on satellites or unmanned aerial vehicles (UAV), as well as high-altitude platforms (HAP) will be exploited in 6G wireless communication systems, complementing terrestrial networks. For long-distance communication, a large smart antenna will be used that is characterized by high amounts of power consumed by digital beamformers. This paper focuses on reducing power consumption by relying on a thinned smart antenna (TSA). The performance of TSA is investigated in the sub-6 GHz band. The differential evolution (DE) algorithm is used to optimize excitation weights of the individual dipoles in the antenna array and these excitation weights are then used in TSA for beamforming, with signal processing algorithms deployed. The DE technique is used with the least mean square, recursive least square and sample matrix inversion algorithms. The proposed method offers almost the same directivity, simultaneously ensuring lower side lobes (SLL) and reduced power consumption. For a TSA of 20, 31, and 64 dipoles, the power savings are 20%, 19.4%, and 17.2%, respectively. SLL reductions achieved, in turn, vary from 5.2 dB to 8.1 dB. [ABSTRACT FROM AUTHOR]

In disaster-prone areas, damaged infrastructure requires impromptu communications leveraging lightweight and adaptive antennas. Accordingly, we introduce a bi-stable deployable quadrifilar helix antenna that passively reconfigures its radiation characteristics in terms of pattern and polarization. The proposed structure is composed of counter-rotating helical strips, connected by rotational joints to allow a simultaneous change in the helix height and radius. Each helical strip is composed of a fiber-reinforced composite material to achieve two stable deployed states that are self-locking. The reconfiguration between an almost omnidirectional pattern and a circularly polarized directive pattern enables the antenna to be suitable for both terrestrial and satellite communication within the L-band. More specifically, the presented design in infrastructure-less areas achieves satellite localization with directive circularly polarized waves and point-to-point terrestrial connectivity with an almost omnidirectional state. Hence, we present a portable, agile, and passively reconfigured antenna solution for low-infrastructure areas. Impromptu communications are indispensable for disaster-prone regions with damaged infrastructure. Here, the authors propose a mechanically actuated bi-stable reconfigurable quadrifilar helix antenna suitable for both terrestrial and satellite L-band communications. [ABSTRACT FROM AUTHOR]

Now a days, huge amount of data is communicated through channels in wireless network. It requires an efficient parallel operation for the optimal utilization of frequency, time allocation and coding model for signal subspace factorization in smart antenna. In view of this requirement, an efficient reconfigurable optimal source detection and beam allocation algorithm (RoSDBA) is proposed. The proposed algorithm is able to allocate desired signal to the user space to reduce the noise and also for efficient allocation of subspace to remove disturbance in all directions. The proposed method efficiently utilizes the antenna array elements by accurate identification and allocation of antenna array elements such as individual radiators, radiation beam, signal strength, and disturbance factor. With respect to simulation analysis, the proposed method shows better performance for the resolution, radiation beam allocations, identification bias, distribution factor and time taken for the detection of various array arrangements and source numbers. [ABSTRACT FROM AUTHOR]

This manuscript presents high performance dual polarized eight-element multiple input multiple output (MIMO) fifth generation (5G) smartphone antenna. The design consists of four dual-polarized microstrip diamond-ring slot antennas, positioned at corners of printed circuit board (PCB). Cheap Fr-4 dielectric with permittivity 4.3 and thickness of 1.6mm is used as substrate with overall dimension of 150 × 75 × 1.6 mm3. In mobile system due to limited space mutual coupling between nearby antenna elements is an issue that distort MIMO antenna performance. Defected ground structure is used to control coupling. The defected ground structure has advantages like ease of fabrication, compact size and high efficiency as compare to other techniques. Less than 30dB coupling is achieved for adjacent elements. The -10 dB impedance bandwidth of 700 MHz is achieved for all radiating elements ranging from 3.3 GHz to 4.1 GHz. The value is about 900MHz for -6dB. The proposed antenna offers good results in terms of fundamental antenna parameters like reflection coefficient, transmission coefficient, maximum gain, total efficiency. The antenna achieved average gain more than 3.8dBi and average radiation efficiency more than 80% for single dual polarized element. The antenna provides sufficient radiation coverage in all sides. The MIMO antenna characteristics like diversity gain (DG), envelope correlation coefficient (ECC), total active reflection coefficient (TARC) and channel capacity are calculated and found according to standards. Furthermore, effect of user on antenna performance in data-mode and talk-mode are studied. Proposed design is fabricated and tested in real time. The measured results shows that proposed design can be used in future smartphones applications. The design is compared with some of the existing work and found to be the best one in many parameters and can be used for commercial use. [ABSTRACT FROM AUTHOR]

A rectangular monopole antenna with an extended ground, excited by Coplanar Waveguide (CPW) and backed by a 6 × 6 array of fractal artificial magnetic conductor (AMC) unit cells, resonating at 5.8 GHz in Industrial, Scientific, and Medical (ISM) band, is presented in this manuscript. To attain the objective of proposing a compact and economical antenna solution for employment in wearable biomedical domain, a novel approach of utilizing both surfaces of the same dielectric for engraving antenna element as well as AMC array is adopted. It results in the elimination of layers of expensive substrate (RO3003) and of thick separator (foam) between antenna and AMC array. During measurement in open space, the proposed antenna system exhibited an impedance bandwidth of 570 MHz with a gain of 7.9 dBi. While a total realized gain of 7.5 dBi, amounting to a gain enhancement of about 3 dB as compared to that of monopole alone, is observed when the integrated antenna system is placed just over a three-layer rectangular human body equivalent model. Specific absorption rate values, as calculated at 5.8 GHz and averaged over 1 and 10 g of human tissue, are 0.0117 and 0.00244 W/kg, respectively. Obtained results strongly advocate the use of the proposed antenna system in smart wearable healthcare devices. [ABSTRACT FROM AUTHOR]

A coaxially pin-fed multiband fractal square antenna is proposed in this paper. The designed antenna resonates in five bands: 5 GHz, 10 GHz, 13.2 GHz, 16 GHz, and 20.5 GHz. The multibands are achieved by using a fractal square antenna. The fractal square is formed from an initial square patch and then optimized with increasing fractal iterations to resonate at these bands. The fractal property of the design also helps in the miniaturisation of the antenna. The proposed antenna has gain ranging from 4.9 dB to 9.7 dB and radiation efficiencies from 70% to 98%. The proposed antenna is simulated using the CST microwave studio. The antenna is then fabricated, and its performance parameters are measured. After finding a match between simulated and measured results, the same antenna and its array are tested in a MATLAB simulation environment for direction of arrival (DOA) and adaptive beamforming (AB) at all five bands. Using different DOA and AB algorithms, the performance of the antenna array is evaluated. The ability to accurately estimate the DOA of all signals delivered to the adaptive array antenna allows it to maximise its performance in terms of recovering the required transmitted signal and suppressing any interference signal. Then, the beam of the antenna is modified using the DOA algorithm to generate a beam in the desired direction and nulls in the unwanted direction for proposed satellite communications. [ABSTRACT FROM AUTHOR]

This research article designs and develops a planar small-size antenna design for smart Internet of Things (IoT) communication with long-range technology (LoRa). The proposed system is best suited for transceiver systems in this automation and sensing era. In the proposed antenna, the ground, the radiating element, and the stub feed are designed on the same side of the substrate, keeping in mind that it can print the LoRa module. The design consists of a meandered monopole, a dipole structure as a ground, and a stub feed. A different design approach is employed to get an optimized result. The antenna is made up of a rectangular feed stub to which a connecting wire is attached. The overall dimension of the antenna is 55 m × 55 m × 1.6 mm. To verify the proposed design, an antenna was fabricated and measured, which covers the LoRa frequency band at 868 MHz, providing a sufficient bandwidth of 10 MHz and a gain of more than 0.5 dB in the operating band. A designed antenna is implemented for sensor data communication with the LoRa module device and device interface Arduino platform. The antenna is connected as a transmitter and receiver one by one to verify its performance with machine-to-machine communication using the LoRa module. The size, bandwidth, and radiation efficiency of this antenna are better than the antennas in the literature. The designed antenna is successfully implemented with LoRa connectivity and communicates the data up to 8 km in line-of-sight communication, more than 1 km in urban environments, and approximately 250 m of connectivity in building areas. [ABSTRACT FROM AUTHOR]

Multiband antenna arrays have the capability of effectively working in multiple frequency bands and thus significantly simplify the antenna system. To further reduce the system overhead, this paper discusses the joint design of antenna selection and adaptive beamforming for multiband antenna arrays, where the sidelobe level is also controlled so as to alleviate the effect of unknown sporadic interference. Based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion and sidelobe level constraints, the proposed multiband sparse array design is formulated into a nonconvex constrained nonlinear optimization problem with an l 0 , 2 -mixed norm regularization. This problem ensures that the same antenna positions are selected at all operating frequencies while the beamformer weights of each frequency are optimized independently. By exploiting the semi-definite relaxation and the reweighted l 1 , ∞ -norm approximation, the problem is converted into a series of convex subproblems and is then effectively solved by the proposed iterative reweighted method. Numerical results show that the proposed multiband sparse array significantly reduces the sidelobe levels in all operating frequencies while maintaining the maximum SINR, so it provides superior performance of interference suppression. [ABSTRACT FROM AUTHOR]