Search Results (347)

With the advancement of wireless communication technology, the significance of efficient and accurate channel estimation methods has grown substantially. Recently, deep learning-based methods are being adopted to estimate channels with higher precision than traditional methods, even in the absence of prior channel statistics. In this paper, we propose two deep learning-based channel estimation models, CAMPNet and MSResNet, which are designed to consider channel characteristics from a multiscale perspective. The convolutional attention and multiscale parallel network (CAMPNet) accentuates critical channel characteristics by utilizing parallel multiscale features and convolutional attention, while the multiscale residual network (MSResNet) integrates information across various scales through cross-connected multiscale convolutional structures. Both models are designed to perform robustly in environments with complex frequency domain information and various Doppler shifts. Experimental results demonstrate that CAMPNet and MSResNet achieve superior performance compared to existing channel estimation methods within various channel models. Notably, the proposed models show exceptional performance in high signal-to-noise ratio (SNR) environments, achieving up to a 48.98% reduction in mean squared error(MSE) compared to existing methods at an SNR of $25\mathrm{dB}$. In experiments evaluating the generalization capabilities of the proposed models, they show greater stability and robustness compared to existing methods. These results suggest that deep learning-based channel estimation models have the potential to overcome the limitations of existing methods, offering high performance and efficiency in real-world communication environments. Full article

In this paper, the idea of a radar based on orthogonal frequency division multiplexing (OFDM) is applied to 5G NR Positioning Reference Signals (PRS). This study demonstrates how the estimation of the communication channel using the PRS can be applied for the identification of objects moving near the 5G NR receiver. In this context, this refers to a 5G NR base station capable of detecting a high-speed train (HST). The anatomy of a 5G NR frame as a sequence of OFDM symbols is presented, and different PRS configurations are described. It is shown that spectral analysis of time-varying channel impulse response weights, estimated with the help of PRS pilots, can be used for the detection of transmitted signal reflections from moving vehicles and the calculation of their time and frequency/Doppler shifts. Different PRS configurations with varying time and frequency reference signal densities are tested in simulations. The peak-to-noise-floor ratio (PNFR) of the calculated radar range–velocity maps (RVM) is used for quantitative comparison of PRS-based radar scenarios. Additionally, different echo signal strengths are simulated while also checking various observation window lengths (FFT lengths). This study proves the practicality of using PRS pilots in remote sensing; however, it shows that the most dense configurations do not provide notable improvements, while also demanding considerably more resources. Full article

Experts and scholars from various nations have proposed studying low Earth orbit (LEO) satellite signals as the space-based signals of opportunity (SOPs) for navigation and positioning. This method serves as a robust alternative in environments where global navigation satellite systems (GNSS) are unavailable or compromised, providing users with high-precision, anti-interference, secure, and dependable backup navigation solutions. The rapid evolution of LEO communication constellations has spurred the development of SOPs positioning technology using LEO satellites. However, this has also led to a substantial increase in the number of LEO satellites, thereby reintroducing the traditional challenge of satellite selection. This research thoroughly examines three critical factors affecting positioning accuracy: satellite observable time, satellite elevation, and position dilution of precision (PDOP). It introduces a strategic approach for selecting satellites in LEO SOPs navigation and positioning. Simulation outcomes confirm that this satellite selection strategy effectively identifies visible satellites, ensuring precise positioning through LEO SOPs. Full article

Deep-water reverberation caused by multiple reflections from the seafloor and sea surface can affect the performance of active sonars. To detect a moving target under reverberation conditions, a reverberation suppression method using multipath Doppler shift in deep water and wideband ambiguity function (WAF) is proposed. Firstly, the multipath Doppler factors in the deep-water direct zone are analyzed, and they are introduced into the target scattered sound field to obtain the echo of the moving target. The mesh method is used to simulate the deep-water reverberation waveform in time domain. Then, a simulation model for an active sonar based on the source and short vertical line array is established. Reverberation and target echo in the received signal can be separated in the Doppler shift domain of the WAF. The multipath Doppler shifts in the echo are used to estimate the multipath arrival angles, which can be used for target localization. The simulation model and the reverberation suppression detection method can provide theoretical support and a technical reference for the active detection of moving targets in deep water. Full article

In the Internet of Vehicles (IoV), age of information (AoI) has become a vital performance metric for evaluating the freshness of information in communication systems. Although many studies aim to minimize the average AoI of the system through optimized resource scheduling schemes, they often fail to adequately consider the queue characteristics. Moreover, vehicle mobility leads to rapid changes in network topology and channel conditions, making it difficult to accurately reflect the unique characteristics of vehicles with the calculated AoI under ideal channel conditions. This paper examines the impact of Doppler shifts caused by vehicle speeds on data transmission in error-prone channels. Based on the M/M/1 and D/M/1 queuing theory models, we derive expressions for the age of information and optimize the system’s average AoI by adjusting the data extraction rates of vehicles (which affect system utilization). We propose an online optimization algorithm that dynamically adjusts the vehicles’ data extraction rates based on environmental changes to ensure optimal AoI. Simulation results have demonstrated that adjusting the data extraction rates of vehicles can significantly reduce the system’s AoI. Additionally, in the network scenario of this work, the AoI of the D/M/1 system is lower than that of the M/M/1 system. Full article

The recent rapid development of low Earth orbit (LEO) constellation-based navigation techniques has enhanced the ability of position, navigation, and timing (PNT) services in deep attenuation and interference environments. However, existing navigation modulations face the challenges of high acquisition complexity and do not improve measurement precision at the same signal strength. We propose a pulsed orthogonal time frequency space (Pulse-OTFS) signal, which naturally converts continuous signals into pulses through a special delay-Doppler domain pseudorandom noise (PRN) code sequence arrangement. The performance evaluation indicates that the proposed signal reduces at least 89.4% of the acquisition complexity. The delay measurement accuracy is about 8 dB better than that of the traditional binary phase shift keying (BPSK) signals with the same bandwidth. It also provides superior compatibility and anti-multipath performance. The advantages of fast acquisition and high-precision measurement are verified by processing the real signal in the developed software receiver. As Pulse-OTFS occupies only one time slot of a signal period, it can be easily integrated with OTFS-modulated communication signals and used as a navigation signal from broadband LEO satellites as an effective complement to the global navigation satellite system (GNSS). Full article

Unlike terrestrial radio, the speed of sound in the ocean is relatively slow, which results in mobile underwater M-ary spread spectrum communication typically exhibiting significant and variable multipath effects along with strong Doppler effects, leading to rapid carrier phase shifts in the received signal that severely impact decoding accuracy. This study aims to address the issue of rapid carrier phase shifts caused by significant time-varying Doppler shifts during mobile underwater M-SS communication. This paper innovatively proposes a method for updating matched filters based on correlation cost factors. By calculating the correlation cost factors for each received symbol, the method guides the direction of Doppler estimation and updates the matched filters. After identifying the optimal match, the received symbols are shifted, correlated, and decoded. Simulation and sea trial results indicate that this method demonstrates higher computational efficiency and improved decoding accuracy compared to traditional Doppler estimation matched filters under low signal-to-noise ratio conditions, and exhibits greater robustness under complex motion conditions. Full article

Aiming at the problem of estimating the speed of M-ary Phase Shift Keying (MPSK) communication radiated sources and their carrying platform targets, this paper proposes a data-assisted and inter-symbol spectrum analysis-based speed estimation method for MPSK communication radiated sources. The method first demodulates a signal-carrying message symbol from the received MPSK signal; then segments the signal according to the symbol synchronization information and the symbol period; and then compensates the phase of the symbol waveform corresponding to the message data according to the demodulated message symbol; finally combines the phase-compensated symbol waveform data into a two-dimensional matrix and finds the Doppler frequency of the data at the same sampling moment of different symbols using the vertical Fourier transform to obtain the moving target speed. The speed measurement accuracy and anti-noise performance of the method are analyzed through simulation experiments, and the simulation results show that the speed measurement accuracy of the method is 98.5%. Full article

Underwater unmanned vehicles are complementary with human presence and manned vehicles for deeper and more complex environments. An autonomous underwater vechicle (AUV) has automation and long-range capacity compared to a cable-guided remotely operated vehicle (ROV). Navigation of AUVs is challenging due to the high absorption of radio-frequency signals underwater and the absence of a global navigation satellite system (GNSS). As a result, most navigation algorithms rely on inertial and acoustic signals; precise localization is then costly in addition to being independent from acoustic data communication. The purpose of this paper is to propose and analyze the performance of a novel low-cost simultaneous communication and localization algorithm. The considered scenario consists of an AUV that acoustically sends sensor or status data to a single fixed beacon. By estimating the Doppler shift and the range from this data exchange, the algorithm can provide a location estimate of the AUV. Using a robust state estimator, we analyze the algorithm over a survey path used for AUV mission planning both in numerical simulations and at-sea experiments. Full article

This paper introduces a new method for estimating the maximum Doppler shift using decision feedback channel estimation (DFCE). In highly mobile environments, which are expected to be covered beyond 5G and 6G systems, the relative movement between the transmitter and receiver causes Doppler shifts. This leads to inter-carrier interference (ICI), significantly degrading communication quality. To mitigate this effect, systems that estimate the maximum Doppler shift and adaptively adjust communication parameters have been extensively studied. One of the most promising methods for maximum Doppler shift estimation involves inserting pilot signals at both the beginning and end of the packet. Although this method achieves high estimation accuracy, it introduces significant latency due to the insertion of the pilot signal at the packet’s end. To address this issue, this paper proposes a new method for rapid estimation using DFCE. The proposed approach compensates for faded signals using channel state information obtained from decision feedback. By treating the compensated signal as a reference, the Doppler shift can be accurately estimated without the need for pilot signals at the end of the packet. This method not only maintains high estimation accuracy but also significantly reduces the latency associated with conventional techniques, making it well-suited for the requirements of next-generation communication systems. Full article

We investigate the dynamics of electrons initially counter-propagating to an ultra-fast ultra-intense near-infrared laser pulse using a model for radiation reaction based on the classical Landau–Lifshitz–Hartemann equation. The electrons, with initial energies of 1 GeV, interact with laser fields of up to ${10}^{23}$ W/${\mathrm{cm}}^2$. The radiation reaction effects slow down the electrons and significantly alter their trajectories, leading to distinctive Thomson scattering spectra and radiation patterns. It is proposed to use such spectra, which include contributions from harmonic and Doppler-shifted radiation, as a tool to measure laser intensity at focus. We discuss the feasibility of this approach for state-of-the-art and near-future laser technologies. We propose using Thomson scattering to measure the impact of radiation reaction on electron dynamics, thereby providing experimental scenarios for validating our model. This work aims to contribute to the understanding of electron behavior in ultra-intense laser fields and the role of radiation reaction in such extreme conditions. The specific properties of Thomson scattering associated with radiation reaction, shown to be dominant at the intensities of interest here, are highlighted and proposed as a diagnostic tool, both for this phenomenon itself and for laser characterization in a non-intrusive way. Full article

In 2023, we proposed the modified delay and Doppler profiler (mDDP) as an inter-carrier interference (ICI) countermeasure for underwater acoustic orthogonal frequency division multiplexing (OFDM) mobile communications in a multipath environment. However, the performance improvement in the computer simulation and pool experiments was not significant. In a subsequent study, the accuracy of the channel transfer function (CTF), which is the input for the mDDP channel parameter estimation, was considered insufficient. Then a sequential ICI canceling mDDP was devised. This paper presents simulations of underwater OFDM communications using an iterative one- to three-step mDDP. The non-reflective pool experiment conditions are a two-wave multipath environment where the receiving transducer moves at a speed of 0.25 m/s and is subjected to a Doppler shift in the opposite direction. As NumCOL, the number of taps in the multitap equalizer which removes ICI, was increased, the bit error rate (BER) of 0.0526661 at NumCOL = 1 was significantly reduced by a factor of approximately 45 to a BER of 0.0011655 at NumCOL = 51 for the sequential ICI canceling mDDP. Full article

Solar-induced chlorophyll fluorescence (SIF) is highly correlated with photosynthesis and can be used for estimating gross primary productivity (GPP) and monitoring vegetation stress. The far-red band of the solar Fraunhofer lines (FLs) is close to the strongest SIF emission peak and is unaffected by chlorophyll absorption, making it suitable for SIF intensity retrieval. In this study, we propose a retrieval window for far-red SIF, significantly enhancing the sensitivity of data-driven methods to SIF signals near 757 nm. This window introduces a weak O₂ absorption band based on the FLs window, allowing for better separation of SIF signals from satellite spectra by altering the shape of specific singular vectors. Additionally, a frequency shift correction algorithm based on standard non-shifted reference spectra is proposed to discuss and eliminate the influence of the Doppler effect. SIF intensity retrieval was achieved using data from the GOSAT satellite, and the retrieved SIF was validated using GPP, enhanced vegetation index (EVI) from the MODIS platform, and published GOSAT SIF products. The validation results indicate that the SIF products provided in this study exhibit higher fitting goodness with GPP and EVI at high spatiotemporal resolutions, with improvements ranging from 55% to 129%. At low spatiotemporal resolutions, the SIF product provided in this study shows higher consistency with EVI and GPP spatially. Full article

In this article, a deep neural network (DNN)-based underwater acoustic (UA) communication receiver is proposed. Conventional orthogonal frequency-division multiplexing (OFDM) receivers perform channel estimation using linear interpolation. However, due to the significant delay spread in multipath UA channels, the frequency response often exhibits strong non-linearity between pilot subcarriers. Since the channel delay profile is generally unknown, this non-linearity cannot be modeled precisely. A neural network (NN)-based receiver effectively tackles this challenge by learning and compensating for the non-linearity through NN training. The performance of the DNN-based UA communication receiver was tested recently in river trials in Western Australia. The results obtained from the trials prove that the DNN-based receiver performs better than the conventional least-squares (LS) estimator-based receiver. This paper suggests that UA communication using DNN receivers holds great potential for revolutionizing underwater communication systems, enabling higher data rates, improved reliability, and enhanced adaptability to changing underwater conditions. Full article

A comprehensive study was conducted at a wave energy device test site located off the northeastern coast of Taiwan to assess the influence of oceanic currents on experimental equipment. A bottom-mounted 600 kHz acoustic Doppler current profiler, equipped with integrated temperature and pressure sensors, was deployed at a depth of approximately 31 m. This study, spanning from 6 June 2023 to 11 May 2024, recorded ocean current profiles by assembling data from 50 pings every 10 min, with a resolution of one meter per depth layer. The findings reveal that variations in water levels were predominantly influenced by the M2 tidal constituent, followed by the O1, K1, and S2 tides. Notably, seawater temperature fluctuations at the seabed were modulated by tides, especially the M2 tide. A significant drop in seawater temperature was also observed as the typhoon passed through the south of Taiwan. In terms of sea surface currents, the measured maximum current speed was 71.89 cm s⁻¹, but the average current speed was only 15.47 cm s⁻¹. Tidal currents indicated that the M4 and M2 tides were the most significant, with semimajor axes and inclination angles of 8.48 cm s⁻¹ and 102.60°, and 7.00 cm s⁻¹ and 97.76°, respectively. Seasonally, barotropic tidal currents were the strongest in winter. Additionally, internal tides were identified, with the first baroclinic mode being dominant. The zero-crossing depths varied between 14 and 18 m. During the summer, the M2 baroclinic tidal current displayed characteristics of the second baroclinic mode, with zero-crossing depths at approximately 7 m and 22 m. This node aligns with results from the empirical orthogonal function analysis and correlates with the depths’ significant shifts in seawater temperature as measured by a conductivity, temperature, and depth instrument. Despite the velocities of internal tides not being strong, the directional variance between surface and bottom flows presents critical considerations for the deployment and operation of moored wave energy devices. Full article