Search Results (808)

This article is about better wireless network connectivity. The main goal is to provide wireless service to several use cases and scenarios that may not be adequately covered today. Some of the considered scenarios are home connectivity, street-based infrastructure, emergency situations, disaster areas, special event areas, and remote areas that suffer from problematic/inadequate network and possibly power infrastructure. A target system that we consider for such scenarios is that of an energy-efficient self-backhauled base station (also called a “portable access point—PAP”) that is mounted on a drone to aid/expand the land-based network. For the wireless backhaul link of the PAP, as well as for the fronthaul of the street-mounted base station, we consider newly built multi-active/multi-passive parasitic antenna arrays (MAMPs). These antenna systems lead to increased range/signal strength with low hardware complexity and power needs. This is due to their reduced number of radio frequency chains, which decreases the cost and weight of the base station system. MAMPs can show a performance close to traditional multiple input/multiple output (MIMO) systems that use as many antenna elements as RF chains and to phased arrays. They can produce a directional beam in any desired direction with higher gain and narrow beamwidth by just tuning the load values of the parasitic elements. The MAMP is designed based on radiation conditions which were produced during the research to ensure that the radiation properties of the array were good. Full article

We consider the wideband spectrum sensing within a multi-path propagation environment, where a multi-antenna base station (BS) is tasked with identifying the frequency positions of multiple narrowband transmissions distributed across a broad range of frequencies. To tackle this, we propose a sub-Nyquist sampling structure that incorporates a phased array system. Specifically, each antenna is connected to two separate sampling channels, i.e., one for direct sampling and another for delayed sampling, with the latter incorporating a specified time delay factor. The cross-correlation matrices associated with the samples, which are characterized by different time lags, are calculated. These matrices are represented in tensor form, and the factor matrices are extracted through CANDECOMP/PARAFAC (CP) decomposition. By these factor matrices, the carrier frequencies and the power spectra of the far-field signals of interest are estimated. Numerical simulations are conducted to evaluate the performance of the proposed method, and the results reveal the feasibility and effectiveness of the approach, demonstrating its potential for accurate and efficient wideband spectrum sensing in complex multi-path propagation environments. Full article

This paper proposes a dual-band patch antenna with combined self-decoupling and filtering properties, designed to suppress mutual coupling between two antenna elements both within the same dual-band and across different dual-bands. Initially, a dual-band aperture-coupled filtering patch antenna is designed, featuring a forked short-circuited SIR feedline with a quarter-wavelength open-ended stub and a U-shaped patch with two U-slots, which generate three controllable radiation nulls while introducing two additional resonant modes. The design steps are also provided in detail. Subsequently, the low mutual coupling phenomenon of two vertically placed aperture-coupled patch antennas is investigated, successfully developing a high-isolated dual-band two-element MIMO array I. Furthermore, the other quad-band two-element MIMO array II is designed, which utilizes the filtering response to significantly reduce mutual coupling across four bands. Finally, a dual-band filtering patch antenna element and two two-element MIMO arrays are fabricated and measured. The measurements and simulations validate the antenna’s low mutual coupling performance in multi-band MIMO arrays and demonstrate its strong potential for future wireless communication applications. Full article

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. Full article

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GBSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The framework explores optimization strategies for the partial sharing of antenna elements, specifically tailored for multi-mode radar applications, utilizing the desirability function to enhance performance across various operational modes. A novel machine learning initialization approach is introduced for rapid convergence. Key observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GBSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study emphasizes the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework. The proposed design framework for grid-spaced sparse arrays stands out for its superior efficiency and applicability in processing hardware compared to both uniform and non-uniform arrays. Full article

Nociceptors are receptors that detect injurious stimuli and are necessary to convey such information from the periphery to the central nervous system. While nociception has been extensively studied in various taxa, there is relatively little electrophysiological evidence for the existence of nociceptors in decapod crustaceans. This study investigated putative nociceptive responses in the shore crabs, specifically their response to mechanical and noxious chemical stimuli. Extracellular multi-unit electrophysiological recordings were conducted from the anterior ganglion and the circumesophageal connective ganglia to assess nociceptive responses. Soft tissues at the joints of the chelae, antennae, and walking legs were stimulated using acetic acid (noxious stimulus) and von Frey hairs (mechanical stimulus), while nearby ganglion activity was recorded. The results indicate the existence of nociceptors in the tested areas, with mechanical stimuli eliciting shorter, more intense neural activity compared with acetic acid. Although acetic acid triggered responses in all areas, the antennae and antennules did not respond to mechanical stimuli. Though we acknowledge the challenges of conducting in vivo electrophysiological recordings, future research should focus on further characterizing nociceptor activity because the results suggest the presence of nociceptors. Full article

A new dual-band low-noise amplifier (LNA) operating at L1/E1 1.575 GHz and L5/E5 1.192 GHz center frequencies for global navigation satellite system receivers is proposed. A doubled common-source amplifier architecture is used with a single input, shared gate inductor, and two outputs to split the RF signal into separate RX channels. The main advantage of the proposed circuit is compatibility with widespread multi-band antennas with single RF connectors dedicated to high-precision applications, as well as the possibility to use cheap SAW filters with small footprints to build low-cost, highly accurate GNSS receiver modules. The input and both outputs are well matched to 50 Ω impedance. The LNA is designed with a 110 nm CMOS process, consuming 6.13 mA current from a 1.5 V supply. The measured noise figures and voltage gains of the dual-band LNA are, respectively, NF1/NF5 = 3.23/3.5 dB and G1/G5 = 21.22/18.2 dB in the band of interest for each channel. The measured impedance matching at the input (S11) and output (S22) of the dual-band low-frequency amplifier is as follows: S11_L1 = −23.89, S11_L5 = −8.42, S22_L1 = −12.65, S22_L5 = −15.08. The one-decibel compression points are L1 band PdB1 = −37.71 dBm and L5 band PdB5 = −34.72 dBm, respectively. Full article

In this paper, a planar, bow-tie antenna with an enhanced bandwidth and a bi-directional radiation pattern is proposed. The concept of multi-resonance is applied by implementing the superposition of three different bow-tie components with various radii and flare angles in an overlapped fashion into a single element, resulting in a significant increase in bandwidth. The antenna has an electrical size, kr, of 1.10, calculated at the lowest frequency of operation. The proposed antenna is simulated, and a prototype is fabricated for verification by measurement. The result is a wide −10 dB bandwidth of 80.3% (1.23–2.88 GHz) from the measurements. The antenna also maintains a bi-directional radiation pattern, with a negligible difference between the forward and backward realized gains, within the entire −10 dB bandwidth. The measured realized gain values in the forward and backward directions are between 1.5 dBi and 3.7 dBi over the −10 dB bandwidth. The comparison of the measurement and simulation results shows good agreement. Full article

To mitigate inter-symbol interference (ISI) caused by Faster-than-Nyquist (FTN) technology in a multiple input multiple output (MIMO) optical wireless communication (OWC) system, we propose an ISI cancellation algorithm that combines multi-head self-attention (MHSA), a one-dimensional convolutional neural network (1D CNN), and bi-directional long short-term memory (Bi-LSTM). This hybrid network extracts data features using 1D CNN and captures sequential information with Bi-LSTM, while incorporating MHSA to comprehensively reduce ISI. We analyze the impact of antenna numbers, acceleration factors, wavelength, and turbulence intensity on the system’s bit error rate (BER) performance. Additionally, we compare the waveform graphs and amplitude–frequency characteristics of FTN signals before and after processing, specifically comparing sampled values of four-pulse-amplitude modulation (4PAM) signals with those obtained after ISI cancellation. The simulation results demonstrate that within the Mazo limit for selecting acceleration factors, our proposal achieves a 7 dB improvement in BER compared to the conventional systems without deep learning (DL)-based ISI cancellation algorithms. Furthermore, compared to systems employing a point-by-point elimination adaptive pre-equalization algorithm, our proposal exhibits comparable BER performance to orthogonal transmission systems while reducing computational complexity by 31.15%. Full article

Alkali-activated concrete (AAC), produced from industrial by-products like fly ash and slag, offers a promising alternative to traditional Portland cement concrete by significantly reducing carbon emissions. Yet, the inherent variability in AAC formulations presents a challenge for accurately predicting its compressive strength using conventional approaches. To address this, we leverage machine learning (ML) techniques, which enable more precise strength predictions based on a combination of material properties and cement mix design parameters. In this study, we curated an extensive dataset comprising 1756 unique AAC mixtures to support robust ML-based modeling. Four distinct input variable schemes were devised to identify the optimal predictor set, and a comparative analysis was performed to evaluate their effectiveness. After this, we investigated the performance of several popular ML algorithms, including random forest (RF), adaptive boosting (AdaBoost), gradient boosting regression trees (GBRTs), and extreme gradient boosting (XGBoost). Among these, the XGBoost model consistently outperformed its counterparts. To further enhance the predictive accuracy of the XGBoost model, we applied four state-of-the-art optimization techniques: the Gray Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), beetle antennae search (BAS), and Bayesian optimization (BO). The optimized XGBoost model delivered superior performance, achieving a remarkable coefficient of determination (R²) of 0.99 on the training set and 0.94 across the entire dataset. Finally, we employed SHapely Additive exPlanations (SHAP) to imbue the optimized model with interpretability, enabling deeper insights into the complex relationships governing AAC formulations. Through the lens of ML, we highlight the benefits of the multi-faceted synergistic approach for AAC strength prediction, which combines careful input parameter selection, optimal hyperparameter tuning, and enhanced model interpretability. This integrated strategy improves both the robustness and scalability of the model, offering a clear and reliable prediction of AAC performance. Full article

This communication introduces a versatile, multi-service, shared-aperture antenna system for multiple vehicle applications. The design comprises three antenna elements: a rotatable microstrip antenna for global positioning system (GPS) communication, a cross-dipole circularly polarized antenna for satellite communication in the S-band, and a pattern reconfigurable antenna for V2V (vehicle-to-vehicle) communication. These antennas collectively support GPS, satellite communication (Satcom), and V2V communication in a single, shared-aperture design. This shared-aperture antenna system offers cost savings and occupies less space compared to using separate antennas for each service. The microstrip antenna covers the 1575 MHz frequency band used for GPS communication. The cross-dipole circularly polarized antenna provides continuous wideband coverage for S-band satellite communication. The pattern reconfigurable antenna, tailored for the specific application scenario, covers the 5.9 GHz V2V working frequency band (5.855–5.925 GHz). Practical testing and simulation results confirm the effectiveness of this antenna system for the intended applications. In summary, the microstrip antenna has a bandwidth of 1.565–1.578 GHz and a realized gain of 7 dBi with radiation efficiency of 81%, the cross-dipole antenna has a bandwidth of 2.2–3.8 GHz (53.3%) and a realized gain of 8.3 dBi with radiation efficiency of 90%, and the pattern reconfigurable antenna has a 5.8–6 GHz bandwidth and a realized gain of 3.7 dBi with radiation efficiency of 85%, and the isolation between antennas with different frequencies is 25 dB, 20 dB, and 30 dB in three frequency bands. Full article

This paper proposes a novel hybrid beamforming (HBF) structure for gain-aware grouping transmit antennas and users in multiuser multiple-input single-output (MU-MISO) systems. In the conventional HBF structure, all transmit antennas form a beam to each user. In this case, the gain of each antenna varies depending on the location of the base station and each user, and the transmit power after the digital beamformer is allocated to the antenna with the smallest gain. Signals transmitted from antennas with small gains are susceptible to noise and interference. Therefore, this paper proposes an HBF structure in which only the antenna with the highest gain forms the beam for each user. In the proposed scheme, the transmitting antennas are grouped and the beam is formed only by the group of antennas with the highest gain for each user. Simulation results show that the proposed scheme can reduce the number of phase shifters used on the transmit side compared to the conventional HBF scheme while maintaining sum-rate performance when the number of transmit antennas and users are the same. It was also shown that there is a trade-off between the reduction in the number of phase shifters used to form the beam and the improvement in performance as the number of transmit antennas increases. Furthermore, it is shown that when antenna selection is used, although there is a trade-off between the number of phase shifters and performance improvement, the number of phase shifters can be reduced while maintaining performance even when the number of transmit antennas increases. Full article

This study introduces distance metrics for quantized-channel-based precoding in multiuser multiantenna systems, aiming to enhance spectral efficiency in dense cellular networks. Traditional metrics, such as the chordal distance, face limitations when dealing with scenarios involving limited feedback and multiple receive antennas. We address these challenges by developing distance measures that more accurately reflect network conditions, including the impact of intercell interference. Our distance measures are specifically designed to approximate the instantaneous rate of each user by estimating the unknown components during the quantization stage. This approach enables the associated users to efficiently estimate their achievable rates during the quantization process. Our distance measures are specifically designed for block diagonalization precoding, a method known for its computational efficiency and strong performance in multi-user multiple-input and multiple-output systems. The proposed metrics outperform conventional distance measures, particularly in environments where feedback resources are constrained, as is often the case in 5G and emerging 6G networks. The enhancements are especially significant in dense cellular networks, where accurate channel state information is critical for maintaining high spectral efficiency. Our findings suggest that these new distance measures offer a robust solution for improving the performance of limited-feedback-based precoding in cellular networks. Full article

This study introduces a novel antenna based on the binary operation of a modified circular patch in conjunction with the Koch fractal. The antenna is intended for applications in the sub-6 GHz band, partial C-band, and X-band. The low-cost antenna is fabricated on a 1.6-mm-thick FR-4 substrate. A frequency-selective surface (FSS) is used to overcome the decreased values of the gain and bandwidth due to the fractal operations. The introduced split ring resonator (SRR) and the antenna substrate dimension reduction reduce the bandwidth and antenna gain. The air gap between the FSS and the antenna not only enhances the antenna gain but also controls the frequency tuning at the design frequency. The antenna size is miniaturized to 36.67%. A monopole antenna ground loaded with an SRR results in improved closest tuning (3.44 GHz) near the design frequency. The antenna achieves a peak gain of 9.37 dBi in this band. The FSS-based antenna results in a 4.65 dBi improvement in the gain value with the FSS. The measured and simulated plots exhibit an excellent match with each other in all three frequency bands at 2.96–4.72 GHz. These bands cover Wi-MAX (3.5 GHz), sub-6 GHz n77 (3300–3800 MHz), n78 (3300–4200 MHz), and approximately n79 (4400–4990 MHz), in addition to C-band applications. Full article

Wireless hierarchical federated learning (WHFL) is an implementation of wireless federated Learning (WFL) on a cloud–edge–client hierarchical architecture that accelerates model training and achieves more favorable trade-offs between communication and computation. However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. In this paper, we propose a secure finite block-length (FBL) approach for the multi-antenna URLLC-WHFL, and characterize the relationship between privacy, utility, and PLS of the proposed scheme. Simulation results show that when the eavesdropper’s CSI is perfectly known by the edge server, our proposed FBL approach not only almost achieves perfect secrecy but also does not affect learning performance, and further shows the robustness of our schemes against imperfect CSI of the eavesdropper’s channel. This paper provides a new method for the URLLC-WHFL in the presence of PLS. Full article