Wireless Systems Research Articles

Deep learning-driven channel coding: enhancing performance in LDS-CDMA and NOMA systems

This paper presents an innovative approach to channel coding for LDS-CDMA and NOMA systems through the integration of deep learning techniques. By leveraging neural networks within the channel coding process, the proposed model achieves substantial improvements in error correction, leading to a significant reduction in Bit Error Rate (BER) and computational complexity when compared to traditional methods such as Unpunctured Turbo Trellis Coded Modulation (UTTCM). The results demonstrate that the deep learning-based system is particularly effective in challenging communication environments, such as those with low Signal-to-Noise Ratios (SNR) and high levels of multi-user interference, where it outperforms conventional coding techniques. This research underscores the potential of deep learning to enhance the efficiency and adaptability of wireless communication systems, particularly as networks evolve towards 6G and beyond. The flexibility offered by this approach allows for improved handling of dynamic and complex environments, ensuring higher data throughput and reduced latency. Future work may focus on implementing the proposed model in real-time applications, as well as investigating its synergy with emerging technologies like massive MIMO and NOMA, which could lead to even greater performance enhancements in next-generation communication systems.

The realization of power stabilization and reactive power minimization for wireless charging system under high coils misalignment

The realization of power stabilization and reactive power minimization for wireless charging system under high coils misalignment

A Bidirectional Simultaneous Wireless Power and Data Transfer System with Non-Contact Slip Ring

A Bidirectional Simultaneous Wireless Power and Data Transfer System with Non-Contact Slip Ring

YOLO-RWY: A Novel Runway Detection Model for Vision-Based Autonomous Landing of Fixed-Wing Unmanned Aerial Vehicles

In scenarios where global navigation satellite systems (GNSSs) and radio navigation systems are denied, vision-based autonomous landing (VAL) for fixed-wing unmanned aerial vehicles (UAVs) becomes essential. Accurate and real-time runway detection in VAL is vital for providing precise positional and orientational guidance. However, existing research faces significant challenges, including insufficient accuracy, inadequate real-time performance, poor robustness, and high susceptibility to disturbances. To address these challenges, this paper introduces a novel single-stage, anchor-free, and decoupled vision-based runway detection framework, referred to as YOLO-RWY. First, an enhanced data augmentation (EDA) module is incorporated to perform various augmentations, enriching image diversity, and introducing perturbations that improve generalization and safety. Second, a large separable kernel attention (LSKA) module is integrated into the backbone structure to provide a lightweight attention mechanism with a broad receptive field, enhancing feature representation. Third, the neck structure is reorganized as a bidirectional feature pyramid network (BiFPN) module with skip connections and attention allocation, enabling efficient multi-scale and across-stage feature fusion. Finally, the regression loss and task-aligned learning (TAL) assigner are optimized using efficient intersection over union (EIoU) to improve localization evaluation, resulting in faster and more accurate convergence. Comprehensive experiments demonstrate that YOLO-RWY achieves AP50:95 scores of 0.760, 0.611, and 0.413 on synthetic, real nominal, and real edge test sets of the landing approach runway detection (LARD) dataset, respectively. Deployment experiments on an edge device show that YOLO-RWY achieves an inference speed of 154.4 FPS under FP32 quantization with an image size of 640. The results indicate that the proposed YOLO-RWY model possesses strong generalization and real-time capabilities, enabling accurate runway detection in complex and challenging visual environments, and providing support for the onboard VAL systems of fixed-wing UAVs.

A Dynamic Beamforming at 5.4 GHz: Design and Validation of an Integrated Metasurface Reflectarray-Horn Antenna System for Wireless Communications

A Dynamic Beamforming at 5.4 GHz: Design and Validation of an Integrated Metasurface Reflectarray-Horn Antenna System for Wireless Communications

Retraction Note: Enhancing quality of service in wireless systems using iterative weighted least squares with fuzzy logic integration algorithm

Retraction Note: Enhancing quality of service in wireless systems using iterative weighted least squares with fuzzy logic integration algorithm

HCTC: Hybrid Convolutional Transformer Classifier for Automatic Modulation Recognition

Automatic modulation recognition (AMR) methods used in advanced wireless communications systems can identify unknown signals without requiring reference information. However, the acceptance of these methods depends on the accuracy, number of parameters, and computational complexity. This study proposes a hybrid convolutional transformer classifier (HCTC) for the classification of unknown signals. The proposed method utilizes a three-stage framework to extract features from in-phase/quadrature (I/Q) signals. In the first stage, spatial features are extracted using a convolutional layer. In the second stage, temporal features are extracted using a transformer encoder. In the final stage, the features are mapped using a deep-learning network. The proposed HCTC method is investigated using the benchmark RadioML database and compared with state-of-the-art methods. The experimental results demonstrate that the proposed method achieves a better performance in modulation signal classification. Additionally, the performance of the proposed method is evaluated when applied to different batch sizes and model configurations. Finally, open issues in modulation recognition research are addressed, and future research perspectives are discussed.

Intelligent-Reflecting-Surface-Assisted Single-Input Single-Output Secure Transmission: A Joint Multiplicative Perturbation and Constructive Reflection Perspective

Due to the inherent broadcasting nature and openness of wireless transmission channels, wireless communication systems are vulnerable to the eavesdropping of malicious attackers and usually encounter undesirable situations of information leakage. The problem may be more serious when a passive eavesdropping device is directly connected to the transmitter of a single-input single-output (SISO) system. To deal with this urgent situation, a novel IRS-assisted physical-layer secure transmission scheme based on joint transmitter perturbation and IRS reflection (JPR) is proposed, such that the secrecy of wireless SISO systems can be comprehensively guaranteed regardless of whether the reflection-based jamming from the IRS to the eavesdropper is blocked or not. Moreover, to develop a trade-off between the achievable performance and implementation complexity, we propose both element-wise and group-wise reflected perturbation alignment (ERPA/GRPA)-based IRS reflection strategies, respectively. In order to evaluate the achievable performance, we analyze the ergodic secrecy rate (ESR) and secrecy outage probability (SOP) of the SISO secure systems with the ERPA/GRPA-based JPRs, respectively. Finally, by characterizing the simulated and numerical ESR and SOP performance results, our proposed scheme is compared with the benchmark scheme of random phase-based reflection, which strongly demonstrates the effectiveness of our proposed scheme.

Deep-Unfolded Tikhonov-Regularized Conjugate Gradient Algorithm for MIMO Detection

In addressing the multifaceted problem of multiple-input multiple-output (MIMO) detection in wireless communication systems, this work highlights the pressing need for enhanced detection reliability under variable channel conditions and MIMO antenna configurations. We propose a novel method that sets a new standard for deep unfolding in MIMO detection by integrating the iterative conjugate gradient method with Tikhonov regularization, combining the adaptability of modern deep learning techniques with the robustness of classical regularization. Unlike conventional techniques, our strategy treats the Tikhonov regularization parameter, as well as the step size and search direction coefficients of the conjugate gradient (CG) method, as trainable parameters within the deep learning framework. This enables dynamic adjustments based on varying channel conditions and MIMO antenna configurations. Detection performance is significantly improved by the proposed approach across a range of MIMO configurations and channel conditions, consistently achieving lower bit error rate (BER) and normalized minimum mean square error (NMSE) compared to well-known techniques like DetNet and CG. The proposed method has superior performance over CG and other model-based methods, especially with a small number of iterations. Consequently, the simulation results demonstrate the flexibility of the proposed approach, making it a viable choice for MIMO systems with a range of antenna configurations, modulation orders, and different channel conditions.

A Design Review for Biomedical Wireless Power Transfer Systems with a Three-Coil Inductive Link through a Case Study for NICU Applications

This paper outlines a design approach for biomedical wireless power transfer systems with a focus on three-coil inductive links for neonatal intensive care unit applications. The relevant literature has been explored to support the design approach, equations, simulation results, and the process of experimental analysis. The paper begins with a brief overview of various power amplifier classes, followed by an in-depth examination of the most common power amplifiers used in biomedical wireless power transfer systems. Among the traditional linear and switching amplifier classes, class-D and class-E switching amplifiers are highlighted for their enhanced efficiency and straightforward implementation in biomedical contexts. The impact of load variation on these systems is also discussed. This paper then explores the basic concepts and essential equations governing inductive links, comparing two-coil and multi-coil configurations. In the following, the paper discusses foundational coil parameters and provides theoretical and experimental analysis of both two-coil and multi-coil inductive links through step-by-step measurement techniques using lab equipment and addressing the relevant challenges. Finally, a case study for neonatal intensive care unit applications is presented, showcasing a wireless power transfer system operating at 13.56 MHz for powering a wearable device on a patient lying on a mattress. An inductive link with a transmitter coil embedded in a mattress is designed to supply power to a load at distances ranging from 4 cm to 12 cm, simulating the mattress-to-chest distance of an infant. the experimental results of a three-coil inductive link equipped with a Class-E power amplifier are reported, demonstrating power transfer efficiency ranging from 75% to 25% and power delivery to a 500 Ω-load varying from 340 mW to 25 mW over various distances.

Investigation of Temperature at Al/Glass Fiber-Reinforced Polymer Interfaces When Drilling Composites of Different Stacking Arrangements

This attempt covers an investigation of cutting temperature at interfaces of Fiber Metal Laminates (FMLs) made of glass fiber-reinforced polymer (GFRP) stacked with an Al2020 alloy. GFRP/Al/GFRP and Al/GFRP/Al composite stacks are both investigated to highlight the effect of stacking arrangement on thermal behavior within the interfaces. In a first test series, temperature history is recorded within the metal/composite stack interfaces using preinstalled thermocouples. In a second test series, a wireless telemetry system connected to K-type thermocouples implanted adjacent to the cutting edge of the solid carbide drill is used to record temperature evolution at the tool tip. Focus is put on the effects of cutting speed and stacking arrangement on the thrust force, drilling temperature, and delamination. From findings, the temperature histories show high sensitivity to the cutting speed. When cutting Al/GFRP/Al, the peak temperature is found to be much higher than that recorded in GFRP/Al/GFRP and exceeds the glass transition point of the GFRP matrix under critical cutting speeds. However, thrust force obtained at constitutive phases exhibits close magnitude when the stacking arrangement varies, regardless of cutting speed. Damage analysis is also discussed through the delamination factor at different stages of FML thickness.

New Trust Based Smart Data Forwarding Mechanism in Vehicular Delay Tolerant Network

Vehicular Delay Tolerant Network (VDTN) is the growing field with a considerable possibility to handle future wireless application’s requirements. Using vehicles for the data communication purpose can be contemplated as a substitute for the wired and wireless systems. This paper proposes a trust-based data forwarding mechanism for Vehicular Delay Tolerant Network (VDTN). Data forwarding in VDTN requires every vehicular or stationary node to participate in data forwarding. But some time malicious nodes show non-cooperative behaviour in data forwarding. Therefore, malicious nodes must be identified specifically to accelerate the data forwarding. A threshold based social skeleton membership process along with new trust-based data forwarding mechanism is proposed in this paper. We reveal that the social skeleton members perform better in data forwarding in terms of data delivery ratio, data delay and data overhead. Simulation results demonstrate that the trust-based data forwarding improves the data delivery ratio with trust-based data forwarding approach. After simulation a comparative analysis of two different scenarios is presented with epidemic routing, prophet routing and spray and wait routing.

Wideband circularly polarized dielectric resonator antenna with multi-functional metasurface assistance for low profile

ABSTRACT A low-profile broadband circularly polarized (CP) dielectric resonator antenna (DRA) is proposed, utilizing DR reutilization and metasurface (MS) techniques. Two resonant frequencies and an AR minimum are achieved simultaneously, by exciting a rectangular DR with an inclined corner-truncated coupling slot, for it generates nearly degenerated TE111 modes. For significant bandwidth enhancement and low profile, a new resonator is formed by reusing the DR and loading an MS above, which works in orthogonal TM modes. To increase the axial ratio bandwidth (ARBW) further without enlarging the antenna size， two parasitic patches are printed on two adjacent side walls of the DR. To verify the rationality and feasibility, the antenna is fabricated and measured. The fabricated prototype possesses the profile of 0.06λ 0 (λ 0 is the free-space wavelength at the center frequency). The measured impedance bandwidth (IBW) and ARBW are 36.05% (4.23 ~ 6.09 GHz) and 22.46% (4.9 ~ 6.14 GHz), respectively. The proposed antenna has both broadband characteristics and a low profile, making it easy to integrate into space-limited wireless communication systems with high data rates.

Adaptive TLS-OQSM technology of a wireless optical MIMO communication system over an oceanic vertical turbulence channel

Adaptive TLS-OQSM technology of a wireless optical MIMO communication system over an oceanic vertical turbulence channel

Integrated Microstrip Patch Antenna with a Frequency-Selective Surface Utilizing Hospital Textile Materials for Reduced Specific Absorption Rate in Wearable Wireless Communication Systems

Integrated Microstrip Patch Antenna with a Frequency-Selective Surface Utilizing Hospital Textile Materials for Reduced Specific Absorption Rate in Wearable Wireless Communication Systems

Automated wireless system for monitoring the technical condition of chimneys

The present paper considers the technology of monitoring the technical condition of chimneys in order to identify areas of increased heat losses. The technology involves an automated wireless monitoring system that includes an unmanned aircraft with additional equipment. Aim. To study the operation safety of reinforced concrete chimneys used in hazardous industrial facilities. The presented monitoring technology tackles the task of prompt identification of defects and damages to reduce the risks of potentially hazardous conditions. While developing technology for monitoring the technical condition, special attention is paid to its autonomy and intelligence. At the first stage, sensors, coordinators and remote thermometry system are installed with the transmission of data on the temperature of the chimney trunk to the control center. At the next stage, the outer surface of the chimney is examined using an unmanned aicraft equipped with a thermal imaging camera to verify information about heat losses. The final stage involves creating a thermogram of the object and a scheme of the possible locations of the identified defects in order to plan repair works. In addition, the paper introduces main advantages of the suggested technology.

A compact coupling-fed omnidirectional wideband filtering antenna with high selectivity

ABSTRACT This paper presents a compact coupling-fed omnidirectional wideband filtering antenna with high selectivity for modern wireless communication systems. The antenna integrates a coupling-fed driven patch with a symmetrical printed Г-shaped dipole, facilitating wideband performance and high selectivity through multiple coupling paths. Coupling-fed structure introduces radiation nulls (RNs), achieving an operating bandwidth of 54.5% for |S11| ≤ −10 dB and out-of-band suppression of −9 dB without requiring additional circuits. Simulations and experiments validate the antenna’s performance, demonstrating multiple resonant frequencies and consistent omnidirectional radiation patterns. Compared to traditional designs, it offers superior bandwidth and selectivity, making it suitable for integration into planar RF circuits in applications such as Wi-Fi 6, 5 G, and radar systems.

Smart Home

The concept of a smart home integrates wireless electronic systems that connect household devices to a central interface, enabling remote control via smartphones or wall panels through Wi-Fi networks. This paper explores the core components of smart homes, including smart devices such as speakers, thermostats, lighting, and security systems, as well as the role of mobile applications in managing these devices. The paper discusses the various applications of smart homes, from home automation and security monitoring to energy management and health-focused initiatives.

A 2–36 GHz CMOS LNA with π-Network-Based wideband interstage matching technique for software-defined radio systems

With the advance in wireless communication, next-generation software-defined radio (SDR) systems require transceivers to operate in both sub-6GHz and millimeter-wave (mmWave) band and support multiple standards. However, bridging sub-6GHz frequencies with millimeter-wave bands exceeding 30 GHz remains a challenge for conventional wideband LNAs. To surmount this, a 2–36 GHz CMOS low-noise amplifier (LNA) designed for SDR systems is introduced in this paper. An innovative wideband input matching network capable of spanning both frequency domains is proposed. The methodology effectively mitigates the impact of vast parasitic capacitances, achieving wideband input matching against Electrostatic Discharge (ESD) and on-chip decoupling capacitor parasitic. In addition, a π-network-based wideband interstage matching technique is adopted to extend bandwidth of gain. A tri-stage prototype of the proposed LNA, designed using a 40-nm CMOS process, is designed to validate our design strategies. The post-simulation outcomes reveal a peak gain of 14 dB with a -3dB bandwidth ranging from 2 to 36 GHz, equating to a fractional bandwidth of 178 %. The Noise Figure (NF) is commendably uniform across the frequency spectrum, stabilizing at 5 dB. Furthermore, the third-order input intercept point (IIP3) is −4.2dBm to -3dBm across the bandwidth. The performance is achieved with a power of 19.4 mW and within a core area of 0.1 mm2.

A High‐Performance 3D Eight‐Port THz‐MIMO Antenna System Verified With Machine Learning for Enhanced Wireless Communication Systems

A High‐Performance 3D Eight‐Port THz‐MIMO Antenna System Verified With Machine Learning for Enhanced Wireless Communication Systems