Electronics Letters最新文献

This letter introduces an innovative approach for minimizing energy consumption in multi-unmanned aerial vehicles (multi-UAV) networks using deep reinforcement learning, with a focus on optimizing the age of information (AoI) in disaster environments. A hierarchical UAV deployment strategy that facilitates cooperative trajectory planning, ensuring timely data collection and transmission while minimizing energy consumption is proposed. By formulating the inter-UAV network path planning problem as a Markov decision process, a deep Q-network (DQN) strategy is applied to enable real-time decision making that accounts for dynamic environmental changes, obstacles, and UAV battery constraints. The extensive simulation results, conducted in both rural and urban scenarios, demonstrate the effectiveness of employing a memory access approach within the DQN framework, significantly reducing energy consumption up to 33.25% in rural settings and 74.20% in urban environments compared to non-memory approaches. By integrating AoI considerations with energy-efficient UAV control, this work offers a robust solution for maintaining fresh data in critical applications, such as disaster response, where ground-based communication infrastructures are compromised. The use of replay memory approach, particularly the online history approach, proves crucial in adapting to changing conditions and optimizing UAV operations for both data freshness and energy consumption.

Convolutional neural network (CNN)-based models have shown significant progress in low light image enhancement. However, many existing models possess a large number of parameters, making them unsuitable for deployment on terminal devices. Moreover, adjustments to brightness, contrast, and colour in images are often non-linear, and convolution is not the best at capturing complex non-linear relationships in image data. To address these issues, a model based on an end-to-end custom non-linear transform network (CNTNet) is proposed. CNTNet combines a custom non-linear transform layer with CNN layers to achieve image contrast and detail enhancement. The CNT layer in this model introduces transformation parameters at multiple scales to manipulate input images within various ranges. CNTNet progressively processes images by stacking multiple non-linear transform layers and convolutional layers while integrating residual connections to capture and leverage subtle image features. The final output is generated through convolutional layers to obtain enhanced images. Experimental results of CNTNet demonstrate that, while maintaining a comparable level of image quality evaluation metrics to mainstream models, it significantly reduces the parameter count to only 2K.

This paper introduces a novel software-based approach to enhancing stack smashing protection in C/C++ applications, specifically targeting return-oriented programming attacks, which remain a significant threat to firmware and software security. Traditional canary-based protections are vulnerable to brute-force and format string attacks. Additionally, many stack protection mechanisms require access to the source code or recompilation, complicating the security of existing binaries. This paper proposes a new method, aptly named $�{\text{StackGuard}}^{+}$, that modifies the canary-based protection mechanism by altering the code responsible for canary insertion and verification. This change ensures the integrity of the return address while maintaining the original code size, allowing for seamless interoperability without the need for recompilation or additional hardware. The approach can be automated using a Python script, which modifies existing canary-based binaries with only 26 bytes of machine code on the $�\times$86-64 platform. Moreover, this approach can be easily adapted to other platforms, including $�\times$86 and ARM64.

In mobile communication networks for integrated sensing and communication, site planning of access points fundamentally determines both communication quality and sensing performance. This paper aims to tackle the AP placement problem under the setting of cell-free massive multiple-input multiple-output, which represents a promising direction for network architecture evolution. Seeking a balance between the sum-throughput of communication and the Cramér–Rao lower bound of target sensing, the access points are first pre-placed by solving a convex optimization and further adjusted with optimal angular geometry. The final step involves employing nearest neighbour projection to refine access point positions in the cell-free massive multiple-input multiple-output system, ensuring alignment with integrated sensing and communication requirements. The numerical results show that the proposed algorithm achieves 90% of the optimal communication sum-rate and 95% of the optimal target localization accuracy.

To address the variable initial state and trail length this paper first presents a robust PD-type open-closed-loop iterative learning control (ILC) law for a multiple-input-multiple-output (MIMO) linear discrete-time system. It is demonstrated that the convergence condition is dependent on the PD-type feed-forward learning gains, while an appropriate feedback learning gain can improve the ILC convergence performance. As a special case of PD-type open-closed-loop ILC law, P-type and D-type open-closed-loop ILC laws are deduced. The three developed ILC laws ensure that as the number of iterations approaches infinity, the expectation of ILC tracking error will be constrained within a limited range, where the boundary is proportional to the initial state variation. Through a numerical simulation, the effectiveness of the proposed ILC laws is illustrated.

This letter presents a wirelessly powered LED driving circuit for a smart contact lens system. Since photobiomodulation has been investigated for ocular disease treatment by irradiating light with a specific wavelength, a smart contact lens equipped with a µLED and its controller IC can be utilized as a phototherapy system. The proposed circuit design facilitates constant-current generation to drive the LED and incorporates a wirelessly powered system. The system can be turned on and off in synchronization with an external wireless power source, providing controllability for the LED's irradiation period and intensity. The IC is fabricated in the 180-nm CMOS process with a die area of 1.0 mm² and integrated into the smart contact lens with an external loop antenna and a far red/NIR LED. The measurement demonstrates the irradiation period of the LED is successfully controlled by the external source, with current levels from 0.53 mA to 1.4 mA, thereby confirming the feasibility of the phototherapy system.

In this letter, the working mechanism of suggested bandpass filters with connected symmetric short-circuit stub multimode resonators is described. Because of the design flexibility, the suggested bandpass filters' centre frequencies may be modified based on the design approach. Meanwhile, the suggested bandpass filters have reduced insertion losses and compact sizes. A prototype is built and tested with six passbands centred at 1.57/2.38/3.55/5.14/5.83/6.78 GHz to confirm the design and analysis. Good agreement between the simulated, and measured results is observed, indicating that the proposed structure can be applied in the field of communication, information, and automation.

In this letter, a novel integrated sensing and communication (ISAC) scenario with wireless power transfer (ISAC-WPT) is investigated. In this new setup, an access point simultaneously employs communication and sensing beams to serve a communication user, detect an RFID tag, and power an energy receiver. The objective is to design the sensing and communication beams to minimize the total transmit power while satisfying the requirements of tag detection, communication, and energy harvesting. To address the corresponding non-convex problem, the constraints are reformulated into convex second-order cone constraints, thereby obtaining the globally optimal solution. To further reduce computational complexity, zero-forcing is employed to design the beamforming vectors, followed by solving a convex optimization problem to determine the optimal power allocation between sensing and communication beams. The simulation results demonstrate the effectiveness of the proposed beamforming designs, highlighting the potential of ISAC-WPT Backscatter RFID systems.

The multi-stage noise shaping (MASH) ΣΔ ADC has a good potential to achieve high-order noise shaping (NS) and high resolution. However, it suffers from quantization noise leakage caused by the mismatch between the analogue NS filter and the digital cancellation filter, which greatly degrades the ADC performance. The sturdy MASH topology of the ΣΔ ADC can solve the leakage issue, but it cannot be implemented using the NS SAR ADC due to structural limitations. This paper proposes a sturdy MASH 2-0 NS SAR to solve the noise leakage issue. The 4^th-order NS is achieved by only using a 2-0 topology, which is hardware efficient. Instead of eliminating the first-stage quantization error, the proposed sturdy MASH 2-0 NS SAR shapes it, achieving better robustness to PVT variables. Furthermore, owing to the first-stage 2^nd-order NS capability, the impairments of the residue amplifier, including the gain error and nonlinearity, are 2^nd-order shaped. The proposed 4^th-order sturdy MASH 2-0 NS SAR is implemented in a 28 nm CMOS process, which achieves a SNDR of 85.6 dB and a SFDR of 101.3 dB with 10 MHz BW at OSR of 10, resulting in a Schreier FoM of 178.8 dB/179.4 dB (in SNDR/DR) with power consumption of 4.8 mW.

This paper presents a low-profile patch antenna with dual-axis wide-beam characteristics. The antenna includes a microstrip patch antenna and four parasitic patch elements. The study demonstrates that both the E-plane and H-plane beams can be extended by strategically placing these parasitic patches. The length and distance of these parasitic patch elements play a crucial role in achieving the desired wide-beam characteristics. A prototype antenna operating at 5.8 GHz is fabricated and measured in an anechoic chamber to validate the concept and design parameters. The measured results confirm the extension of half-power beamwidth in the E-plane to 123$�{}^{\circ }$ (133%) and in the H-plane to 120$�{}^{\circ }$ (153%).