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The sixth-generation (6G) wireless communications and the Internet of Things (IoT) will connect thousands of devices through large antenna arrays. A large smart antenna (SA) requires high-power consumption. This paper suggests a new method of low-power antenna array design using a thinned smart antenna (TSA). Genetic algorithm (GA) and particle swarm optimization (PSO) are used for the optimal beamforming of TSA of dipole arrays. The GA and PSO are used with the least mean square (LMS) algorithm (GA-LMS, PSO-LMS), the recursive least square (RLS) algorithm (GA-RLS, PSO-RLS), and the sample matrix inversion (SMI) algorithm (GA-SMI, PSO-SMI). For GA-optimized TSAs of 20, 31, and 64 dipoles, the power savings are 15%, 25.8%, and 20.3%, respectively, with a side lobe level (SLL) reduction of 10.55 dB. For PSO-optimized TSAs of 20, 31, and 64 dipoles, the power savings are 25%, 22.6%, and 20.3%, respectively, with an SLL reduction of 8.5 dB. [ABSTRACT FROM AUTHOR]

This study presents an aperture-coupled slot-fed antenna specifically designed to operate in two frequency bands. It functions seamlessly within the 5.2-5.3 GHz and 5.9-6.1 GHz ranges, featuring unique characteristics: emitting monopole radiation at lower frequencies and transitioning to a broadside pattern at higher frequencies. The 5.2-5.3 GHz band is primarily used for high-speed Wi-Fi (IEEE 802.11 standards) and small cells in 5G networks, as well as radar systems. The 5.9-6.1 GHz band supports Intelligent Transportation Systems (ITS), vehicle-to-everything (V2X) communication, and C-band satellite uplink services. With a peak gain of 6.025 dBi, this compact antenna measures 25 mm×25 mm×1.6 mm (0.492λ×0.492λ×0.0315λ, where λ is the wavelength calculated at 5.9 GHz) and is precisely printed on two FR4 substrates, ensuring both performance and practicality. Thorough measurements of the constructed prototype show a remarkable alignment between simulated and measured results, confirming the antenna's reliability and precision. Its distinctiveness lies in its engineered adaptability, perfectly suited for applications requiring diverse patterns within dual-band scenarios. This adaptability allows for flexible signal reception, making it an ideal choice for situations demanding robust performance across multiple frequency ranges. Given its ability to offer varied pattern configurations, this antenna shows significant promise for applications where flexible and reliable signal reception is crucial. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to enhancing the isolation of adaptive array antennas. The primary focus is on overcoming the limitations of monopole antennas in adaptive array antennas, specifically addressing the challenges posed by mutual coupling between antenna elements and the constraints of decoupling structures. Based on characteristic mode analysis, we propose stepped monopole antennas with an innovation decoupling structure, which significantly reduces mutual coupling without significantly affecting the radiation patterns. The paper details the design and function of these antennas and the development of the decoupling structure and validates the approach through simulation and measurement results [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The swift growth of 5G communication networks necessitates creative approaches to improve dependability, effectiveness, and performance. This paper investigates how to enhance 5G network capabilities through the integration of antenna technology based on adaptive artificial intelligence (AI). Complicated and dynamic settings are frequently too difficult for conventional static antenna setups to handle. Adaptive antennas can dynamically modify their characteristics, such as beamforming and power regulation, in real-time to maximize signal quality and coverage by utilizing AI methods, such as machine learning and deep learning. Using both simulations and in-field testing, the study assesses how AI-based adaptive antennas affect important performance measures including spectrum efficiency, latency, bit-error rate and network throughput. The findings show that 5G networks' capacity and flexibility are greatly increased by AI-based adaptive antenna systems, making them more resistant to changing environmental factors and user density. This technology is expected to play a major role in enabling 5G and beyond network realization. [ABSTRACT FROM AUTHOR]

In this paper, we propose an underlay cognitive radio (CR) system that includes subscribers, termed secondary users (SUs), which are designed to coexist with the spectrum owners, termed primary users (PUs). The suggested network includes the PUs system and the SUs system. The coexistence between them is achieved by using a novel dynamic spectrum co-access multicarrier-based cognitive radio (DSCA-MC-CR) technique. The proposal uses a quadrature phase shift keying (QPSK) modulation technique within the orthogonal frequency-division multiplexing (OFDM) scheme that maximizes the system data rate and prevents data inter-symbol interference (ISI). The proposed CR transmitter station (TX) and the CR receiver node (RX) can use an advanced smart antenna system, i.e., a multiple-input and multiple-output (MIMO) system that provides high immunity against channel impairments and provides a high data rate through its different combining techniques. The proposed CR system is applicable to coexist within different existing communication applications like fifth-generation (5G) applications, emergence applications like the Internet of Things (IoT), narrow-band (NB) applications, and wide-band (WB) applications. The coexistence between the PUs system and the SUs system is based on using power donation from the SUs system to improve the quality of the PU signal-to-interference-and-noise ratios (SINRs). The green communication concept achieved in this proposal is compared with similar DSCA proposals from the literature. The simulations of the proposed technique show enhancement in the PUs system throughput and data rate along with the better performance of the SUs system. [ABSTRACT FROM AUTHOR]

In smart homes, industrial automation, healthcare, agriculture, and environmental monitoring, IoT antenna systems improve communication efficiency and dependability. IoT antenna systems affect network performance and connection by affecting gain, directivity, bandwidth, efficiency, and impedance matching. Dipole, patch, spiral, metamaterial-based, and other antenna types are tested in IoT settings to identify their applicability, benefits, and downsides. Current antenna technology has challenges with frequency, bandwidth, size, weight, material choices, and energy efficiency, requiring new solutions. According to the study, interference control, power consumption, and dynamic IoT adaptation research are inadequate. Metamaterials, nanomaterials, and 3D printing may circumvent these antenna design limitations. AI and machine learning can improve antenna design real-time optimization and performance in complex settings. The paper explores how standards and regulatory frameworks affect IoT antenna system development to ensure future designs meet a fast-growing market. For the growing range of IoT applications, this research suggests more flexible and reconfigurable antennas that can function across numerous frequency bands. The report emphasizes antenna material and design innovation to improve durability, cut costs, and scale manufacturing. This research tackles these key elements to enable the next generation of antenna systems to meet IoT technology's expanding needs and increase networked devices' functionality, efficiency, and integration across industries. This comprehensive approach helps identify current trends and concerns and prepares for future IoT antenna system advancements, enabling smarter, more connected, and more efficient technologies. [ABSTRACT FROM AUTHOR]

The urge of modern communication system is to design and development of the smart antennas with adaptive radiation characteristics. The multifold capabilities of fourth‐dimensional antenna arrays can cater that much needed adaptiveness if properly designed. Compared to the conventional arrays, the fourth‐dimensional arrays have one added advantage as the 'Time' of all the switched‐on antenna elements can be managed to generate the required amplitude and phase tapering without even using attenuators and phase shifters. However, one inherent limitation of fourth‐dimensional control parameter is the generation of harmonics or sidebands. This article proposes various means of radiation pattern synthesis in fourth‐dimensional linear antenna arrays with pulse shifting, pulse splitting, and a combination of both. First of all, the pulse splitting and shifting techniques are combinedly proposed by reducing the sidelobe levels and sideband levels of the beamforming antenna arrays to enhance directivities and efficiencies. Then, this mathematical proposition of the direction finding fourth‐dimensional arrays is developed. Finally, broad nulls over a specific angle of arrival region are created for jamming and interference mitigation. For all these cases, the sidelobe level and the unwanted higher‐order sideband levels are suppressed to reduce the unwanted interferences and power losses. The optimal time schemes for all the synthesized patterns are generated by proposing a chaos‐based soft computing algorithm. The radiofrequency signals at each radiating array element are processed by the optimal time schemes proposed for specific applications. The outcomes are validated and compared with other state‐of‐the‐art works of this domain to prove the competency of the proposed work. The qualitative and quantitative comparisons presented for beamforming array is aimed for a good improvement over other reported works by targeting ultralow (less than −40 dB) sidelobe and sideband levels. For direction‐finding array, the proposed idea has also targeted ultralow sidelobes for the main as well as steered beam patterns. Furthermore, the null placement over a region has been aimed to cover more area for jamming and sidelobe reduction for interference mitigation. Overall, the optimal designs proposed for these advanced applications are beneficial for cutting‐edge communication systems. [ABSTRACT FROM AUTHOR]

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]

According to the critical challenges for accessing streaming multimedia over wireless technologies such as lower ranges of data throughput and unacceptable rates for delay and packet losses, it was necessary to implement a system that makes some processes for these challenges, with considerations of coverage and capacity limitations that definitely will have a direct effect on the overall system quality. In this paper, we discuss the effect of applying radio resource management (RRM) technique and smart antenna modes through the fifth-generation (5G) radio link on the voice streaming packets flow in a network where many scenarios were simulated by OPNET while maintaining the quality of the network, regardless of the data load inside it. Also, we have a proposed algorithm to utilize RRM and smart antenna modes over 5G networks. On the other hand, we make a detailed eleven scenarios divided into two phases to discuss the effect of these parameters on quality as (i) RRM Coverage and system capacity, and (ii) smart antenna modes in terms of coverage and capacity. The results of simulation prove that adding RRM and smart antenna modes to the proposed networks over 5G radio link verifies a considerable evolution in the network on data flow of streaming voice packets, also including that end to end delay, packet delay variations, and throughput realize the overall requirements for quality of service (QoS) to access multimedia streaming services through a wide range of 5G bandwidth. The proposed system support monotonically response of delay all over the time of simulation for all QoS metrics. [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]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The object of the study is the process of adapting a multi-channel correlation sidelobe canceller to work in conditions of radio-electronic countermeasures based on the Gram-Schmidt orthogonalization procedure. The proposed approach allows developing a fast, recursive algorithm for searching for optimal values of weight coefficients. Such an algorithm will ensure fast adaptation of the sidelobe canceller to a complex interference-target situation, which can change rapidly. The obtained result of the coefficient of suppression of active noise interference in a constant value approaches the optimal value determined by the Wiener-Hopf equation, which indicates the effectiveness of the proposed approach. By using the Gram-Schmidt orthogonalization procedure, it was possible to obtain high stability of the procedures for calculating the optimal values of weight coefficients, in contrast to other considered approaches. The proposed approach can be practically implemented in existing radar systems for suppressing active noise interference. During the study, it was found that the adaptive multi-channel correlation sidelobe canceller in a steady-state mode works similarly to adaptive phased antenna arrays - it has the same efficiency in spatial signal selection and in compensation of active noise interference. When suppressing four active noise interference, the suppression coefficient is –23.35 dB. With an increase in the number of interferences at the input of the four-channel sidelobe canceller, the suppression level deteriorates rapidly. With five, six, seven, eight interferences – –22.90 dB, –21.54 dB, –20 dB, –17.02 dB, respectively. Such changes are due to the number of active interferences, which is greater than the number of compensation channels [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]

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]

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]

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]

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]

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]

Future smart reconfigurable antennas (RAs) (Haupt R-L and Lanagan M (2013) Reconfigurable antennas. IEEE Antennas and Propagation Magazine 55, 49–61) will likely be fully multipurpose and controlled by software and equipped with machine learning skills that can discern and respond to alterations in the radio frequency environment. Cognitive radio utilizations will be accomplished using a new generation of antenna technology and communication protocols. The effective use of frequencies and the use of polarization diversity and radiation pattern reconfigurability to send data over existing congested frequencies will be major advantages for such applications. The usage of antennas that can be reconfigured in multiple-input multiple-output (MIMO) channels will enhance channel capacity while simultaneously improving channel efficiency and lowering costs (Christodoulou C-G, Tawk Y, Lane S-A and Erwin S-R (2012) Reconfigurable antennas for wireless and space applications. Proceedings of the IEEE 100, 2250–2261). There are a lot of antennas used both at the transmitter and at the receiver front end in a MIMO system. The benefit of employing such arrangements is that different types of information can be conveyed at a similar time, boosting the spectral efficiency of communication in a multipath situation. The coding rate, modulation level, and transmission signaling method of a MIMO system can all be changed in response to changing channel circumstances and user needs. In a MIMO context, polarization reconfigurable/frequency-reconfigurable/radiation pattern RA increase the degree of freedom and enhancing the system's performance. The usage of such antennas greatly enhances capacity by enabling a choice of various polarization configurations and pattern diversity. Antenna arrays that can be reconfigured are also an appealing MIMO system solution that needs to retain robust communication channels, particularly in portable gadgets where the area is limited. [ABSTRACT FROM AUTHOR]

With the increasing demand for smarter antenna design in advanced technology applications, well-designed antennas have been an important factor in enhancing system performance. Most traditional antenna design requires multiple iterations and extensive testing to produce a final product. Machine learning (ML) algorithms have been used as an alternative to predict the optimal design parameters, but the outcome depends highly on the ML model efficiency. With recent development in machine learning algorithms and the availability of data for antenna design, we investigated different machine learning algorithms for optimizing the output strength of three basic antennae by analyzing the signal strength of the antenna for various antenna parameters. Different regression-based ML models were used to learn the behaviors and efficiency of three different antennas and to predict the output strength (S11) for different ranges of frequencies. The experiment compared and analyzed these ML regression algorithms for three different antennas: shot antenna, patch antenna, and bowtie antenna. In addition, the paper also provides comparison of ensemble ML models for performance analysis using the best three ML algorithms from the preliminary study. This study optimizes antenna parameters and quicker and smarter antenna design procedure using ML algorithms as compared to traditional design methods. [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]

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]

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]

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]

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]

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]

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]