Search Results (397)

A gyroscopic stabilizer generates an anti-roll moment by regulating the precession angle of a high-speed rotor. By computing the precession-angle command in real time, the controller can effectively suppress roll motion. However, research on the application of gyroscopic stabilizers to floating wind turbines remains limited. In this study, the operating mechanism of a gyroscopic stabilizer is modeled, and frequency-domain stability analyses are conducted for the system dynamics both before and after the installation of the stabilizer. A pole-placement-based controller is designed to achieve active stabilization of wave-induced platform motions by adjusting the rotor precession angle. Based on wave spectrum analysis, numerical simulations are performed to compare system responses with and without the active controller under different sea conditions. The results demonstrate that the proposed anti-roll control strategy exhibits robust performance and can increase the roll reduction rate by at least a factor of two across a range of sea states. In addition, the anti-roll effectiveness is influenced by rotor speed and environmental conditions, with higher reduction rates achieved at higher rotor speeds, larger wave heights, and longer wave periods. In addition, we adopt a dual-gyro configuration to cancel yaw-interference moments, and the proposed controller is feedback-based (platform motion only), which is suitable for retrofit applications without requiring wave-preview sensors. Full article

Non-orthogonal multiple access (NOMA) has been identified as one of the key technologies for 6G capacity and latency gains. However, existing implementation challenges of the NOMA technique, related to carrier, timing, and phase offsets, successive interference cancellation (SIC) error propagation, packet loss dynamics, and host to software defined radios processing jitter, create obstacles in the practical implementation of NOMA. This paper bridges the gap between theory and hardware by introducing a complete two-user NOMA transmit–receive chain on a low-cost ADALM-Pluto software defined radio (SDR) platform. The proposed implementation integrates matched filtering, offset estimation and correction, SIC with waveform reconstruction and subtraction, and reliability reinforcement via rate-1/2 convolutional coding with Viterbi decoding. We have performed a complete validation of the proposed design in both downlink and uplink modes. We collected data regarding the packet-level and system-related metrics, such as end-to-end latency, bit error rate (BER), and success rate. Moreover, we demonstrate the implementation of the uplink NOMA without need for expensive GPS-disciplined oscillators by leveraging the Pluto Rev-C dual-transmit channels that share a common oscillator. We present detailed experimental results at 915 MHz with BPSK modulation for the downlink performance, and also show a full implementation of the uplink NOMA. We observe excellent reliability for the downlink setup and good reliability for the uplink system. Full article

To address the rigorous requirements of ultra-reliable low-latency communication (URLLC) in beyond 5G/6G networks, we propose an innovative architecture combining automatic repeat request (ARQ) protocol with a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) to enhance short-packet non-orthogonal multiple access (NOMA) communications. Specifically, retransmission mechanism provided by ARQ is utilized to mitigate packet errors stemming from practical system imperfections, i.e., imperfect channel state information (ipCSI), imperfect successive interference cancellation (ipSIC), and hardware impairments. Using the analytical foundation provided by finite blocklength (FBL) theory, expressions for two key performance metrics, i.e., the average block error rate (BLER) and effective throughput, are derived for two NOMA users. Simulation results validate the analytical derivations and demonstrate that the ARQ scheme provides significant reliability gains for each user and achieves synergistic gain with STAR-RIS technology. In addition, the effective throughput exhibits a peak at an optimal blocklength, balancing the reliability gain from a longer blocklength against the spectral efficiency loss from a lower coding rate. This optimal blocklength decreases with more STAR-RIS elements, as improved channel conditions reduce the need for long blocklengths. Full article

Overlapping illumination in multi-LED visible light communication (VLC) networks introduces cross-LED coupling that reshapes the received-signal composition and may trigger error propagation in successive interference cancellation (SIC) for layered ADO-OFDM NOMA. This work employs an overlap factor $\beta \in [0,1]$ to quantify the severity of overlap-induced cross-LED coupling and develops a $\beta$-aware resource-allocation framework for a dual-LED indoor downlink. The proposed design integrates channel-aware MCGAD user grouping with three-level coefficient adaptation, including the inter-LED power split $\eta$, the inter-layer ACO/DCO split $\rho$, and the intra-layer two-user NOMA coefficients $\alpha$. Monte Carlo evaluations over $\beta \in \{0,0.2,0.5\}$ show that stronger coupling drives the system into an interference-limited regime with a pronounced high-SNR BER floor for strong users after SIC; the proposed $\beta$-aware design consistently reduces this floor relative to a $\beta$-blind fixed-coefficient baseline. Meanwhile, the spectral-efficiency curves remain close to the baseline, with only a minor gap at moderate-to-high SNR, and the Shannon-rate energy-efficiency trends remain comparable across coupling scenarios. The grouping-and-allocation procedure is dominated by sorting and deterministic pairing, exhibiting $\mathcal{O}(UlogU)$ complexity and avoiding the combinatorial growth of exhaustive grouping. Full article

This paper investigates the performance of a multi-user multiple-input single-output (MU-MISO) broadcast channel under the practical constraints of imperfect, delayed, and quantized channel state information at the transmitter (CSIT). Conventional interference alignment (IA) strategies—classified into spatial (SIA), temporal (TIA), and message-domain (MIA) techniques— typically designed for specific, idealized CSI regimes and often rely on successive interference cancellation (SIC) at the receiver. However, the iterative structure of SIC is highly susceptible to error propagation, particularly under CSI uncertainty and high-order modulation. We propose Deep-STMIA, a novel end-to-end deep learning framework that jointly optimizes interference management across the space, time, and message domains. Using a neural network-based autoencoder architecture with structural message-domain regularization, Deep-STMIA learns to mitigate the catastrophic effects of error propagation and adapts to a continuum of CSIT conditions. Simulation results demonstrate that Deep-STMIA matches the performance of degrees-of-freedom (DoF) optimal benchmarks in extreme CSI regimes and significantly outperforms state-of-the-art baselines, such as rate-splitting multiple access (RSMA), in practical imperfect CSIT scenarios. Full article

We study the problem of joint sensing and secure communications in a reconfigurable intelligent surface (RIS)-based symbiotic radio (SR) system. In the considered system, a dual-functional radar and communication base station (DFRC-BS) achieves secure communications with multiple user terminals (UTs), and at the same time, performs a target sensing task. An RIS simultaneously assists the secure communications between the DFRC-BS and the multiple UTs and conveys its own data to the UTs by modulating the radio frequency signal from the DFRC-BS. Two different SR settings are investigated, namely, parasitic SR (PSR) and commensal SR (CSR). In both the PSR and the CSR situations, the echo signal from the sensing target is interfered by the backscattered signal from the RIS. We propose two strategies for the DFRC-BS to handle with the interference from the RIS, namely, (1) directly sensing without interference cancelation, and (2) performing interference cancelation before sensing. For both the two strategies, we aim to maximize the sum secrecy rate from the DFRC-BS to the multiple UTs while ensuring satisfactory performances for the sensing and the backscatter links. A block coordinate ascend algorithm is proposed to solve the established non-convex optimization problems. Simulation results reveal that at the DFRC-BS, performing interference cancelation leads to an improved system performance. Furthermore, compared with PSR, CSR leads to a higher sum secrecy rate between the DFRC-BS and the UTs. Full article

Space-based automatic dependent surveillance–broadcast (ADS-B) systems offer the potential for comprehensive global aircraft surveillance. However, they face substantial challenges due to severe signal collisions resulting from the simultaneous reception of asynchronous ADS-B transmissions from multiple aircraft within a satellite’s expansive coverage area. Traditional collision mitigation approaches, such as serial interference cancellation and multichannel blind source separation, often have high computational costs, impose strict signal structure constraints, or rely on multiple-antenna configurations, all of which limit their practicality in satellite scenarios. To address these limitations, this paper proposes two novel deep learning–based models, designated SplitNet-2 and SplitNet-3. SplitNet-2 leverages a Transformer-inspired self-attention architecture specifically designed to separate two overlapping ADS-B signals, while SplitNet-3 employs a convolutional residual U-shaped network optimized for disentangling three simultaneous, colliding signals. Extensive simulations under realistic satellite reception conditions demonstrate that the proposed models significantly outperform conventional methods, achieving lower bit error rates (BERs) and improved demodulation accuracy. These advancements offer a promising solution to the critical problem of underdetermined signal separation in space-based ADS-B reception and significantly enhance the reliability and coverage of satellite-based ADS-B surveillance systems. Full article

In multi-module boost power factor correction (PFC) systems, current ripple is commonly mitigated by applying fixed 180° interleaving between modules; however, this approach relies on matched inductors and ideal symmetry. In practical implementations, inductor mismatch and duty-cycle variations prevent full cancellation, leading to residual ripple that increases losses and electromagnetic interference. To address this issue, several research works have proposed centralized coordination or high-speed communication among units. However, an explicit converter model is necessary, which makes the system more complicated and expensive. To resolve this problem, this paper presents an extremum seeking optimization method for reducing high-frequency ripple in multi-module PFC systems without requiring explicit converter models. The ripple minimization problem is formulated as a nonlinear, time-varying optimization task, where the relative switching phases of the modules are adaptively tuned. The proposed extremum seeking algorithm perturbs the phase shift, evaluates a ripple-based cost function, and updates the phases iteratively. A harmonic analysis is developed to characterize the dependence of ripple on duty ratio, inductor values, and phase displacement. Simulation results show that the method effectively reduces the RMS ripple current across balanced and mismatched operating conditions. In a three-unit system, applying the proposed technique lowered the current THD to 1.29% compared to 1.44% achieved with a fixed phase-shift approach. These findings demonstrate that extremum seeking optimization provides a mathematically rigorous and practically implementable solution for decentralized ripple minimization in multi-module boost PFC systems. Full article

High-speed electrical wireline links, spanning Serializer/Deserializer backplanes and cables, chip-to-chip and die-to-die interfaces, wide-parallel single-ended (SE) buses, and simultaneous-bidirectional (SBD) buses, increasingly operate under severe insertion loss, long channel memory, and strong multi-lane interference. Equalization is therefore a central enabler for reliable symbol recovery in the presence of inter-symbol interference (ISI), echo, and near-/far-end crosstalk. This review synthesizes recent principles, architectures, and silicon-proven implementations of wireline equalizers with an emphasis on practical hardware constraints. It further organizes key research trajectories in high-speed wireline communications across three domains: (i) Time-domain equalization and detection for ISI-limited channels, spanning feed-forward equalizers, latency-relaxed decision-feedback equalization architectures that mitigate stringent feedback-loop constraints, and partial-response signaling combined with reduced-complexity maximum-likelihood sequence detection to enhance resilience against extended channel memory. (ii) Advanced modulation and frequency-domain processing, marking the transition from conventional 4-level pulse-amplitude modulation toward higher-order constellations and multicarrier techniques, notably discrete multitone and orthogonal frequency-division multiplexing, which necessitates modulation-aware frequency-domain equalization and adaptive bit- and power-loading algorithms. (iii) Crosstalk and echo mitigation for dense SE and SBD systems, including cancellation filtering in a multiple-input multiple-output framework and coding-aided interference suppression approaches. Across these domains, we present the fundamental trade-offs between equalization performance, algorithmic convergence, power-area efficiency, and latency. Full article

To address the challenges of ambient light interference and slow overload recovery in transimpedance amplifiers (TIAs) for automotive Light Detection and Ranging (LiDAR) systems, this paper proposes a high-performance TIA with integrated ambient light cancellation and fast recovery capabilities. The core design includes an adaptive ambient light cancellation (ALC) loop that eliminates background currents up to 3 mA without relying on AC coupling capacitors, achieving a low-frequency cutoff frequency of 321 kHz to ensure the signal-to-noise ratio (SNR) of weak target signals. A multi-stage clamping and current transfer mechanism is employed to realize rapid overload recovery: under 100 mA heavy overload conditions, the recovery time is controlled around 8.7 ns, and the pulse broadening is limited to 2.7 ns, avoiding measurement blind zones. Implemented in a 0.18-μm SiGe BiCMOS process, the proposed TIA occupies a compact area of 0.15 mm², with a transimpedance gain of 80 dBΩ (10 kΩ) and a −3 dB bandwidth of 421 MHz. The input-referred noise current spectral density is 4.7 $\mathrm{pA}/\sqrt{\mathrm{Hz}}$, and the integrated equivalent input noise current from 1 Hz to 250 MHz is 73.6 nA_rms. Operating over a temperature range of −40 ℃ to 125 ℃, the TIA meets the rigorous requirements of automotive-grade applications. Performance comparisons with commercial products and state-of-the-art designs demonstrate its competitive ambient light rejection and fast recovery capabilities, validating its potential for use in direct time-of-flight (dToF) LiDAR systems for autonomous driving. Full article

A photonic frequency discrimination and phase identification system based on an on-chip dual Mach–Zehnder modulator (MZM) is proposed. By utilizing the power cancellation (PCD) condition, the system achieves high-precision frequency discrimination and phase identification of multi-frequency radio frequency (RF) signals. The system adopts an on-chip dual-MZM architecture, effectively reducing phase interference in signal transmission caused by environmental factors. This is achieved through precise bias control and the adjustment of the local oscillator (LO) signal’s optical path delay using a tunable optical delay line (TODL), ensuring that the dual MZM operates in the phase inversion condition. When the LO frequency matches that of an RF signal, a significant power attenuation is observed at the system output. The phase of the RF signal is extracted from the corresponding PCD. Experimental results demonstrate that the system achieves a bandwidth of 30 GHz, a frequency resolution of 700 kHz, and a frequency resolution error of less than 498 kHz, with a phase identification range from 0° to 65°. With high integration, the system demonstrates excellent accuracy in multi-frequency signal measurement and phase identification, offering a reliable solution for complex RF scenarios. Full article

Frequency-hopping (FH) communication is widely employed in modern wireless communication systems due to its strong resistance to interference. Accurate detection of FH signals is therefore essential for effective spectrum monitoring and reliable communication in complex electromagnetic environments. However, real-world electromagnetic environments are highly complex and dynamic, with substantial noise and multiple interfering signals coexisting. These conditions pose significant challenges to frequency-hopping signal detection, particularly in terms of low signal-to-noise ratios and co-channel interference. To address these challenges, this paper proposes a frequency-hopping signal detection method based on time–frequency cancellation and the Hough transform. The received signals are first preprocessed using time–frequency cancellation and singular value decomposition to suppress noise and fixed-frequency interference. Subsequently, the time–frequency characteristics of the preprocessed signals are extracted, and the time–frequency cancellation ratio is computed to perform an initial determination of the presence of frequency-hopping signals. To further reduce false detections caused by multiple interference sources, the Hough transform is applied to analyze the time–frequency spectrum in greater detail. By jointly exploiting the geometric and statistical characteristics of the signals, accurate detection of frequency-hopping signals is achieved. Experimental results demonstrate that the proposed method enables precise detection of frequency-hopping signals under challenging electromagnetic conditions. Full article

In this paper, we propose a two-way hybrid satellite–terrestrial relay scheme employing Fountain codes (FCs). In the proposed model, a satellite and a ground user exchange data through a group of terrestrial relay stations, in the presence of an eavesdropper. In the first phase, the satellite and the ground user simultaneously transmit their encoded packets to the relay stations. The relay stations then apply a successive interference cancelation (SIC) technique to decode the received packets. To reduce the quality of the eavesdropping links, a cooperative jammer is employed to transmit jamming signals toward the eavesdropper during the first phase. Next, one of the relay stations which can successfully decode the encoded packets from both the satellite and the ground user is selected for data forwarding, by using a partial relay selection method. Then, this selected relay performs an XOR operation on the two encoded packets, and then broadcasts the XOR-ed packet to both the satellite and the user in the second phase. We derive exact closed-form expressions of outage probability (OP), system outage probability (SOP), intercept probability (IP), and system intercept probability (SIP), and realize simulations to validate these expressions. This paper also studies the trade-off between OP (SOP) and IP (SIP), as well as the impact of various system parameters on the performance of the proposed scheme. Full article

Nonlinear signal models are widely used in power amplifier predistortion, full-duplex self-interference cancellation, and other scenarios. The parallel Hammerstein (PH) model is a typical nonlinear signal model, but its serial and parallel hybrid architecture brings difficulties in performance analysis and coefficient estimation. This paper focuses on the performance analysis and coefficient estimation of the PH model for nonlinear systems with memory effects, such as power amplifiers. By comparing the PH model with the memory polynomial (MP) model under identical basis functions, we analyze its performance across varying numbers of parallel branches, nonlinear orders, and memory depths. Using singular value decomposition (SVD), we derive a closed-form expression for the PH model’s performance under underdetermined conditions, establishing its relationship to the non-zero singular values of the MP model’s coefficient matrix. Based on this, we propose a coefficient generation method combining SVD and least squares (LS), which directly computes coefficients and assesses performance during execution. Simulations confirm the method’s effectiveness, showing that selecting branches associated with larger singular values achieves near-optimal performance with reduced complexity. Full article

We study UAV-assisted 5G uplink connectivity for disaster response, in which a UAV (unmanned aerial vehicle) acts as an aerial base station to restore service to ground users. We formulate a joint control problem coupling UAV kinematics (bounded acceleration and velocity), per-subchannel uplink power allocation, and uplink non-orthogonal multiple access (UL-NOMA) scheduling with adaptive successive interference cancellation (SIC) under a minimum user-rate constraint. The wireless channel follows 3GPP urban macro (UMa) with probabilistic line of sight/non-line of sight (LoS/NLoS), realistic receiver noise levels and noise figure, and user equipment (UE) transmit-power limits. We propose a bounded-action proximal policy optimization with generalized advantage estimation (PPO-GAE) agent that parameterizes acceleration and power with squashed distributions and enforces feasibility by design. Across four user distributions (clustered, uniform, ring, and edge-heavy) and multiple rate thresholds, our method increases the fraction of users meeting the target rate by 8.2–10.1 percentage points compared to strong baselines (OFDMA with heuristic placement, PSO-based placement/power, and PPO without NOMA) while reducing median UE transmit power by $64.6\%$. The results are averaged over at least five random seeds, with $95\%$ confidence intervals. Ablations isolate the gains from NOMA, adaptive SIC order, and bounded-action parameterization. We discuss robustness to imperfect SIC and CSI errors and release code/configurations to support reproducibility. Full article