Offset Signal Research Articles

Dual-polarization carrier-assisted differential detection with asymmetric twin-SSB modulation and simplified receiver structure

Carrier-assisted differential detection (CADD) is a promising solution for high-capacity and cost-sensitive short-reach application scenarios, in which the optical field of a complex-valued double-sideband (CV-DSB) signal is reconstructed without using a local oscillator laser. In this work, we propose a polarization division multiplexed asymmetric twin single-sideband CADD (PDM-ATSSB CADD) scheme to realize the optical field recovery of the PDM CV-DSB signals. The polarization fading is solved by using a pair of optical bandpass filters (OBPFs) to suppress the unwanted other polarized offset carrier and signal, and the dual-polarization optical field is recovered by the CADD receiver. An asymmetric twin-SSB signal is used to relax the sharpness requirement of optical filter edges. We also propose a joint signal-signal beat interference (SSBI) iterative mitigation algorithm, which can effectively mitigate intra- and inter-polarization SSBI. The proposed PDM-ATSSB CADD scheme is validated for 30 Gbaud PDM asymmetric twin-SSB 16-ary quadrature amplitude modulation signals. We illustrate the parameter optimization process for PDM-ATSSB CADD, including optical delay and the number of iterations. The impacts of phase noise and relative intensity noise for laser and polarization impairment on PDM-ATSSB CADD are evaluated through numerical simulation. Compared with the PDM-symmetric-TSSB CADD (PDM-STSSB CADD), the required frequency gap to reach the 7% FEC threshold can be reduced by 1 GHz, and the OSNR sensitivity is improved by about 3 dB. Moreover, two simplified PDM-ATSSB CADD schemes are proposed and discussed, which could be considered hardware-efficient and integrative candidates for metro and inter-data center interconnects.

Automated Processing of Nano-Impact Electrochemistry Signals Using Data-Driven Template Matching

Nano-impact electrochemistry (NIE) is an advanced electrochemical technique that has gained significant attention in recent years due to its ability to investigate properties of individual entities, such as nanoparticles, cells, or even single molecules1 . A typical NIE experiment involves investigating entities freely moving in solution and colliding with an ultramicroelectrode held at a specific potential, allowing individual entities to be electrochemically detected during the collision.The typical NIE responses are the staircase and blip types (spikes),2 with the latter being more commonly observed in NIE experiments. Analysis of spike signals, however, is more complicated due to their irregular and asymmetric shapes. To analyze NIE signals, most studies rely on peak find functions using height threshold for spike identification3 coupled to peak area calculation based on the assumption that the spike shape follows certain distribution functions4. This approach only partially captures the information present in the NIE signal and may result in an inaccurate analysis as demonstrated in Scheme 1, left.To address this issue, we propose a new algorithm, which leverages unsupervised machine learning and image template-matching technology. The algorithm consists of several steps. First, the raw data are denoised. This is done by applying the time-frequency analysis to the data to identify the spike frequency and remove higher-frequency noise using a bandpass filter. Background subtraction is then conducted to align the denoised curve to an approximate zero baseline. Further, some of the current spikes are sampled using a conventional height threshold method to generate templates. A set of templates is generated by clustering the corresponding feature parameters. Template matching is carried out by computing the normalized cross-correlation coefficient of each template on the offset signal. Finally, once the two end points of the spikes have been well-defined parameters characterizing the shape of the current spikes are extracted. Optionally, a new set of templates can be generated for the rematch with the data.The developed algorithm permit precisely detecting the two sides of the spike and extracting critical shape-related parameters, leading to a more accurate and detailed analysis of the NIE signals (Scheme 1, right). Furthermore, by generating templates that reflect the distinguishing features of spikes, observed current signals can be classified into different types, revealing underlying physical phenomena. This method can aid in the standardization of data processing and NIE signal interpretation across various experiments and applications. It can also be used as a pre-processing step when training classification neural networks, which can automate the spike identification process and develop NIE models. As a result, the proposed algorithm has the potential to provide valuable insights into the properties of single entities and advance our understanding of electrochemical reactions at the nanoscale.Reference1. Baker LA. Perspective and Prospectus on Single-Entity Electrochemistry. J Am Chem Soc. 2018;140(46):15549-15559. doi:10.1021/jacs.8b097472. Kwon SJ, Zhou H, Fan FRF, Vorobyev V, Zhang B, Bard AJ. Stochastic electrochemistry with electrocatalytic nanoparticles at inert ultramicroelectrodes—theory and experiments. Phys Chem Chem Phys. 2011;13(12):5394-5402. doi:10.1039/C0CP02543G3. Little CA, Xie R, Batchelor-McAuley C, et al. A quantitative methodology for the study of particle–electrode impacts. Phys Chem Chem Phys. 2018;20(19):13537-13546. doi:10.1039/C8CP01561A4. Peak Finding and Measurement. https://terpconnect.umd.edu/~toh/spectrum/PeakFindingandMeasurement.htm Figure 1

Safety Evaluation of the Combined Effect of Offset Left-Turn Lanes and Flashing-Yellow-Arrow Signals at Signalized Intersections on Multilane Divided Highways in Alabama Using the Empirical Bayes Method

The present study conducted an empirical Bayes (EB) before–after analysis to investigate the combined effects of the offset left-turn lanes and flashing-yellow-arrow (FYA) signals implemented at signalized intersections on multilane, divided highways in Alabama. A total of 35 signalized intersections were selected for the EB safety analysis. Among them, 30 intersections were classified as a reference group and five were classified as a treatment group. The reference group includes intersections which have not undergone any left-turn treatments from the period of 2010 to 2020, while the treatment group includes those improved with offset left-turn lanes and FYA signal implementation concurrently during years in that period. Safety performance functions were developed with data collected at reference-group intersections to predict crashes at such intersections under a no-treatment scenario. A study focus was then given to understanding the change in crash frequency before and after the combined treatments for the treatment-group intersections, using the EB method. Results show that the combined left-turn treatments (i.e., implementing offset left-turn lanes coupled with FYA signals) could reduce different types of crashes effectively. There was a substantial reduction of 27% in total crashes (crash modification factor [CMF] = 0.73), a 43% decrease in left-turn crashes (CMF = 0.57), and a 36% reduction in total injury crashes (CMF = 0.64) after the treatments. These findings were supported by their respective standard errors, which are 0.060, 0.101, and 0.106 for total, left-turn, and total injury crashes, respectively, and all the CMFs are statistically significant at 95% confidence intervals.

Multi-mode detection of iodine based on Au@Ag nanoparticle array with highly sensibility and stability using plasmonic surface lattice resonances

Designing a sensor to rapidly and simply detect iodine (I2) in liquid and gaseous phase with excellent sensitivity, high stability, and low cost at room temperature is highly desirable. Herein, a two-dimensional Au@Ag nanoparticle ordered array was prepared by template method combined with chemical reduction for detecting I2 at room temperature. Due to the ordered structure, a plasmonic surface lattice resonances (PSLR) peak appeared in extinction spectrum of the Au@Ag nanoparticle ordered array. When the ordered array exposed to I2, the Ag shell would react with I2 to form AgI, thus leading to a change in the dielectric medium surrounding the Au nanoparticles. This change would cause a variation of color and a shift of PSLR peak, realizing multi-mode detection of liquid and gaseous I2 at room temperature without any sophisticated instrument. With the increase of I2 concentration, the color of the Au@Ag nanoparticle array changed from red to yellow-green. Meantime, the PSLR peak displayed highly sensitive redshift with a larger offset (about 156 nm) and intense signal strength. Moreover, due to the ordered array structure, the PSLR peak possessed good uniformity and stability. Therefore, the PSLR peak was more suitable for detecting I2 in a large concentration region. Furthermore, the practical application of the present prepared Au@Ag nanoparticle array was explored by detecting gaseous I2 at room temperature. It was found that the Au@Ag nanoparticle array possessed high sensitivity to gaseous I2 with a detection limit reaching to trace level (1 ppb), suggesting tremendous potential for real-world application.

A new method for coseismic offset detection from GPS coordinate time series

Currently, the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes. This is followed by the process of differencing the average GPS coordinate time series data, with a time interval of 3 to 5 days before and after the earthquake. In the face of the huge amount of GPS coordinate time series data today, the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome. To address this problem, we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference. Firstly, we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers. Secondly, we eliminate other signals and errors in the GPS coordinate time series, such as trend and seasonal signals, leaving the coseismic offset signals as the primary signal. The resulting coordinate time series is then modeled using the first-order difference and data stacking method. The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series. The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California, USA. The results demonstrate the efficacy of our proposed method, successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.

WAFER: A new method to retrieve sun-induced fluorescence based on spectral wavelet decompositions

Sun-induced fluorescence (SIF) as a close remote sensing based proxy for photosynthesis is accepted as a useful measure to remotely monitor vegetation health and gross primary productivity. It is therefore important to develop methods that allow for its precise and reliable retrieval from radiance measurements with spectral resolutions that have been increasing over the past few years. Retrieval methods are catching up to the increasing complexity of the available datasets making use of their whole information extent (spectral, spatial and temporal) but the comparability of different SIF retrievals and consistency across scales is still limited.In this work we present the new retrieval method WAFER (WAvelet decomposition FluorEscence Retrieval) based on wavelet decompositions of the measured spectra of reflected radiance as well as a reference radiance not containing fluorescence. By comparing absolute absorption line depths by means of the corresponding wavelet coefficients, a relative reflectance is retrieved independently of the fluorescence, i.e. without introducing a coupling between reflectance and fluorescence. The fluorescence can then be derived as the remaining offset. This method can be applied to arbitrary chosen wavelength windows in the whole spectral range, such that all the spectral data available is exploited, including the separation into several frequency (i.e. width of absorption lines) levels and without the need of extensive training datasets.At the same time, the assumptions about the reflectance shape are minimal and no spectral shape assumptions are imposed on the fluorescence, which not only avoids biases arising from wrong or differing fluorescence models across different spatial scales and retrieval methods but also allows for the exploration of this spectral shape for different measurement setups.WAFER is tested on a synthetic dataset as well as several diurnal datasets acquired with a field spectrometer (FloX) over an agricultural site. We compare the WAFER method to two established retrieval methods, namely the improved Fraunhofer line discrimination (iFLD) method and spectral fitting method (SFM) and find a good agreement with the added possibility of exploring the true spectral shape of the offset signal and free choice of the retrieval window. On our synthetic dataset, WAFER seems to outperform the SFM and works best in a spectral window only containing solar Fraunhofer lines where we achieve a relative retrieval error of 10% on average. Applied to the real dataset, the method returns reasonable diurnal cycles for SIF and can, due to the decoupling of reflectance and fluorescence retrieval, reveal interesting trends at times when vegetation canopies may experience a midday depression that remain largely unobserved with current methods.

Noise Characteristics and Denoising Methods of Long-Offset Transient Electromagnetic Method

The advantages of the long-offset transient electromagnetic method include deep detection and sensitive response to resistivity anomalies. It is widely used in underground mineral resources exploration, fluid identification in petroleum reservoirs, hydraulic fracturing, and dynamic residual oil and gas monitoring. After the primary field signal is turned off, grounded electrodes or coils are used to observe the secondary eddy field. The secondary field signal decays quickly and has a large dynamic range and a wide frequency band but is easily affected by various natural and human electromagnetic interferences. Therefore, noise reduction and distortion correction are important issues in the processing of transient electromagnetic data. This paper proposes a systematic noise interference suppression process. Multi-period and positive–negative bipolar signal stackings were used to remove random noise and suppress DC offset signals. Then, a time-domain inverse digital recursive method was applied to remove characteristic frequency signals, e.g., power frequency signals and their harmonic interference. A standard noise-free signal was constructed through forward modeling simulation and verified by adding different types of noise. Finally, high-quality transient electromagnetic secondary field attenuation signals were obtained through overlapping windowing technology. We applied this algorithm to obtain electromagnetic data from dynamic monitoring of hydraulic fracturing in Fuling shale gas and from a copper–iron metal mine in Daye City, demonstrating its effectiveness.

Offset double-sideband signal field recovery at low CSPR using filter-assisted direct detection

The offset double-sideband (DSB) scheme has attracted attention because it can achieve field recovery at low carrier-to-signal power ratio (CSPR) and improve the spectral efficiency (SE) of self-coherent detection. In this paper, an offset DSB filter-assisted direct detection (FADD) scheme is proposed and studied for the first time, which uses an optical bandpass filter (OBPF) to filter out the optical carrier as the local oscillator for the receiver. As such, signal-signal beat interference (SSBI) can be eliminated. Since the offset DSB signal has a large frequency gap, the requirement for the bandwidth of the OBPF is not high. The performance of the proposed offset DSB FADD scheme is evaluated for 16-QAM signals. It is comprehensively compared with offset DSB carrier-assisted differential detection (CADD) scheme in terms of OSNR sensitivity, optimal CSPR, and receiver power sensitivity. In addition, the effect of frequency gap compression is significant as SSBI is completely eliminated from the system, thereby utilizing as many low-frequency resources as possible and improving SE. Finally, the proposed offset DSB FADD scheme is resilient to the wavelength offset up to several GHz between the transmitter laser and the center wavelength of the OBPF.

A Frequency-Domain I/Q Imbalance Calibration Algorithm for Wideband Direct Conversion Receivers Using Low-Cost Compensator

The amplitude and phase imbalances of the in-phase (I) and quadrature (Q) branches inherent in the direct conversion receiver structure cause the generation of image frequency interference signals. In this paper, a frequency-domain I/Q imbalance calibration algorithm is proposed for wideband direct conversion receivers. The I/Q imbalance model is rebuilt by applying the infinitesimal method and FFT algorithm. The mathematical expressions for the exact computation of the I/Q imbalance parameters are derived based on the frequency-domain statistical properties of the baseband signal. The two phase parameters, frequency-dependent I/Q imbalance (FD-IQI) and frequency-independent I/Q imbalance (FI-IQI), are separated according to the parity properties of the imbalance parameter. To avoid the interference from the transmitter, the receiver impairment estimation is performed using a frequency offset (FO) DC training signal, and a low-cost real-valued compensation (RVC) filter is introduced to correct the impairments of the received signal. The performances of the proposed calibration model are evaluated through simulations and experiments. The simulation results show that the image rejection ratio (IRR) is improved to 80-120 dBc and can also exceed 40 dBc at high noise levels. The experimental results based on the CX9261A evaluation board show that the average IRR of the multi-tone signal is increased by 24.99 dB, and the IRR of the wideband signal is increased by 19.08 dB.

Closed loop simulations on recoverability of climate trends in next generation gravity missions

SUMMARY Gravity field satellite missions are unique observation systems to directly measure mass transport processes on Earth and to gather valuable information for climate research. Next Generation Gravity Missions (NGGMs) are expected to be launched within this decade, setting high anticipation for an enhanced monitoring capability that will improve the spatial and temporal resolutions of gravity observations significantly. They will allow for an evaluation of long-term trends in the Terrestrial Water Storage (TWS) signal. The results of this study are based on a time-series of global changes in soil moisture and snow obtained from future climate projections until the year 2100 of a coupled climate model taking part in the CMIP6 (Coupled Model Intercomparison Project Phase 6). For different mission concepts, namely in-line single-pair missions and a Bender double-pair mission, the recoverability of a time variable mass signal is evaluated, considering realistic noise assumptions, simulated over several decades. The results show that a single-pair mission can fulfill the target requirements for the long-term trend, set by the user community, after 70 yr while a double pair already achieves it after 30 yr of observation. After 100 yr of double-pair constellations the globally averaged RMS (polar areas excluded) improves, compared to a single-pair mission, by a factor of 5 for the linear trend, 2.5 for annual amplitude, and 1.8 for the phase observation. In addition, regional investigations indicate that the simple parameter model consisting of offset, linear trend, and annual signal coefficients, as it was used in this study, in several cases might not be able to capture the whole time-variable signal sufficiently, due to the presence of interannual signals. Hence, advanced, locally more adaptable parameter models need to be considered for a better parametrization of local effects in the future.

Development of the Digital Health Literacy Instrument: Measuring a Broad Spectrum

The current signal capture algorithm uses the correlation function of the signal to achieve capture, which not only has high processing complexity, but also leads to low synchronous capture accuracy. In order to improve the adaptability of the binary offset carrier signal capture algorithm and to improve the defects of the traditional capture algorithm, the spectrum correction-based binary offset carrier signal capture algorithm will be studied. Based on the established binary offset carrier signal model, the signal tracking capture loop is designed. After the spectral correction processing of the signal, the judgment loop is designed based on the bandwidth folding principle to realize the signal capture. The simulation experiments show that the average capture rate of the studied signal capture algorithm is 95.63%, and the main peak amplitude of the captured signal is higher and the capture effect is better.

Analysis of Annual Deformation Characteristics of Xilongchi Dam Using Historical GPS Observations

Global Positioning System (GPS) has been confirmed to be a feasible tool to measure displacement of civil engineering structures. In this paper, we report on an analysis of annual deformations of a pumped-storage power station dam using historical GPS observations. Data spanning more than nine years are resolved using the GAMIT (GPS at MIT) software, and a GPS time-series method is employed to extract linear trends and annual cycle signals. It is evident that the monument located on the main dam has a linear trend, with rates of 1.0 mm/yr and 1.8 mm/yr in east and up directions, respectively. Annual cycles with amplitudes larger than 0.5 mm are shown in coordinate components at all monitoring stations. However, the annual amplitude can be 30–84% lower when a monitoring station whose monument materials and height are similar to other monitoring stations is chosen as the reference station. This suggests that differential thermal expansion of monuments could be 30% to 80% and even higher in baseline time series. A spurious offset style annual signal with 5 mm amplitude that is highly correlated with annual temperature variance is observed in the east–west direction of the monitoring station located at the east side of the reservoir. This suggests that upper ground layer movement correlated with temperature could be responsible for these annual cycles. Meanwhile, no periodic correlations are observed between the water level data and the baseline time series.

Algebraic method of regional green wave coordinated control

This study proposes an algebraic method of regional green wave coordinated control (AM-RGWCC) that can operate efficiently. The research on regional green wave coordinated control (RGWCC) has gradually become a hot spot, improving the overall operational efficiency of the control area more comprehensively and systematically. We usually encounter the difficulties of many constraints, high complexity, and low efficiency when using the modeling method to solve the RGWCC problem. AM-RGWCC is developed in this study to overcome these challenges. The overall coordinated effect is assured by realizing the comprehensive optimization of phase sequence, offset, and common signal cycle. A step-by-step design of AM-RGWCC is established to reduce the complexity by analyzing the comprehensive influence of offset difference and bias distance on the green wave bandwidth. Finally, the case study shows that for a three-by-three road network, an ideal scheme can be obtained by AM-RGWCC to maximize the green wave bandwidth in one second. The green wave bandwidth of each intersection accounts for more than 84%. The results illustrate that the coordinated effect and solving efficiency are significantly improved. The proposed algebraic method will have certain advantages in the RGWCC design of a large-scale road network.

Influence of low-energy magnons on magnon Hanle experiments in easy-plane antiferromagnets

Antiferromagnetic materials host pairs of spin-up and spin-down magnons which can be described in terms of a magnonic pseudospin. The close analogy between this magnonic pseudospin systems and that of electronic charge carriers led to the prediction of fascinating phenomena in antiferromagnets. Recently, the associated dynamics of antiferromagnetic pseudospin has been experimentally demonstrated and, in particular, the first observation of the magnon Hanle effect has been reported. We here expand the magnonic spin transport description by explicitly taking into account contributions of finite-spin low-energy magnons. In our experiments we realize the spin injection and detection process by two Platinum strips and investigate the influence of the Pt-strips on the generation and diffusive transport of magnons in films of the antiferromagnetic insulator hematite. For both a 15 nm and a 100 nm thick film, we find a distinct signal caused by the magnon Hanle effect. However, the magnonic spin signal exhibits clear differences in both films. In contrast to the thin film, for the thicker one, we observe an oscillating behavior in the high magnetic field range as well as an additional offset signal in the low magnetic field regime. We attribute this offset signal to the presence of finite-spin low-energy magnons.

3 × 3 MIMO Fiber–Wireless System in W-Band With WDM/PDM RoF Transmission Capability

We propose and demonstrate a 3 × 3 full multiple-input multiple-output (MIMO) fiber–wireless system in the W-band with wavelength-division multiplexing (WDM) and polarization-division multiplexing (PDM) radio-over-fiber (RoF) transmission capability. The system is realized using two highly stable RoF links based on the optical self-heterodyne method and PDM transmission in one of the RoF links. We experimentally demonstrate and confirm satisfactory performances for a 3 × 3 MIMO offset quadrature amplitude modulation-based filter-bank multicarrier signal. Total capacities of approximately 110 and 132 Gb/s, corresponding to spectral efficiencies of approximately 8.5 and 10.2 bits/s/Hz, respectively, are achieved for the system using antennas placed in the same and alternately different polarizations, respectively. The system is applicable to WDM and combined WDM/PDM RoF transmissions. It provides a scalable solution for facilitating large-scale MIMO signal transportation and can be a promising solution for future mobile transport and radio access networks in high-frequency bands.

Lagged teleconnections of climate variables identified via complex rotated Maximum Covariance Analysis

AbstractA proper description of ocean-atmosphere interactions is key for a correct understanding of climate evolution. The interplay among the different variables acting over the climate is complex, often leading to correlations across long spatial distances (teleconnections). In some occasions, those teleconnections occur with quite significant temporal shifts that are fundamental for the understanding of the underlying phenomena but which are poorly captured by standard methods. Applying orthogonal decomposition such as Maximum Covariance Analysis (MCA) to geophysical data sets allows to extract common dominant patterns between two different variables, but generally suffers from (i) the non-physical orthogonal constraint as well as (ii) the consideration of simple correlations, whereby temporally offset signals are not detected. Here we propose an extension, complex rotated MCA, to address both limitations. We transform our signals using the Hilbert transform and perform the orthogonal decomposition in complex space, allowing us to correctly correlate out-of-phase signals. Subsequent Varimax rotation removes the orthogonal constraints, leading to more physically meaningful modes of geophysical variability. As an example of application, we have employed this method on sea surface temperature and continental precipitation; our method successfully captures the temporal and spatial interactions between these two variables, namely for (i) the seasonal cycle, (ii) canonical ENSO, (iii) the global warming trend, (iv) the Pacific Decadal Oscillation, (v) ENSO Modoki and finally (vi) the Atlantic Meridional Mode. The complex rotated modes of MCA provide information on the regional amplitude, and under certain conditions, the regional time lag between changes on ocean temperature and land precipitation.

An ultra-wideband ultra-low phase noise frequency synthesizer

In order to solve the problems of frequency band expansion in direct frequency synthesis method and serious additional deterioration of phase noise in phase-locked frequency synthesis method, a mixer phase-locked frequency synthesizer combining direct analog frequency synthesis and phase-locked frequency synthesis is designed. In order to reduce the frequency multiplication times of the phase detector and optimize the phase noise of the output signal, the frequency synthesizer uses a comb spectrum generator to excite an offset signal with ultra-low phase noise for mixing. In the meantime, the error-lock problem is solved in ultra-wideband mixing phase-locked loop (PLL). An ultra-wideband frequency synthesizer with frequency band 12 GHz–24 GHz and step of 100 MHz is designed in this paper. The experimental test of the frequency synthesizer shows that the phase noise of the frequency synthesizer is better than -116 dBc/Hz@1 kHz at low frequency 12 GHz, and −109 dBc/Hz@1 kHz at high frequency 24 GHz. This phase noise is basically the same as the direct analog frequency synthesis method and is 20 dB better than the conventional phase-locked scheme. The frequency synthesis method has the advantages of ultra-wideband and ultra-low phase noise, and it can be used in the high performance electronic equipment.

Improved MBOC modulations based on periodic offset subcarrier

With the development of global navigation satellite systems, the modernization of global navigation satellite systems has arrived, which takes the binary offset carrier modulation and related evolution as the typical feature. Moreover, the performance of multiplexed binary offset carrier modulation is related to global navigation satellite systems service. In the paper, an improved multiplexed binary offset carrier modulation based on period offset subcarrier was proposed, called MBOC-POS, where the subcarrier periodic shifting binary offset carrier modulation is used as the lower-order component instead of sine-binary offset carrier modulations. Meanwhile, the different implementations of MBOC-POS modulations are analysed and compared with traditional multiplexed binary offset carrier multiplexed binary offset carrier signals in multipath mitigation, tracking accuracy, anti-interference and compatibility. By simulation and analysis, the performance of reconstructed MBOC-POS modulation has been improved. Especially, for the mismatch reception, the Gabor bandwidth increases by 29.5% and the multipath error envelope is reduced by 35% with the filter bandwidth of 10 MHz. Therefore, the multiplexed binary offset carrier MBOC-POS modulation proposed in the paper can be used as a new option for MBOC modulations and next-generation signal design.

Reduced Complexity Frequency Ambiguity Resolution and Synchronization Signal Detection for 5G NR-V2X Communication Systems

This article presents a reduced-complexity sequential integer carrier frequency offset (ICFO) and sidelink primary synchronization signal (S-PSS) detection scheme in the 5G new radio vehicle-to-everything system. To perform the ICFO detection without information about S-PSS, a two-dimensional detection problem of the ICFO and S-PSS is reduced to two one-dimensional subproblems. Such a design allows us to sequentially detect them and relieves the computational burden of the proposed joint detection scheme. We use both analytical and numerical examples to validate the usefulness of the proposed sequential detector. The simulation results show that the proposed method attains target detection performance with significantly reduced complexity at the cost of increased processing time, as compared to the conventional methods.

Indirect learning Hammerstein HPA predistorter for wideband GNSS signals

Compared with the traditional GPS L1 C/A signal, the existing and emerging new-generation wideband GNSS signals suffer more severe distortions due to the nonlinear characteristics of a high-power amplifier (HPA) in the satellite transmitter. HPA nonlinearity can lead to in-band signal distortion and out-of-band spectral regrowth, which degrade the ranging performance of a GNSS receiver. Researchers have reported power loss, correlation peak asymmetries, lock point bias as well as carrier tracking error caused by the HPA nonlinearity. However, few pre-distortion approaches that compensate for the HPA nonlinear effects have been presented in the GNSS field. We first take BDS-3 B2 asymmetric constant envelope binary offset carrier signal as an example to present the HPA nonlinear effects on wideband GNSS signals. Then, the design principle of a predistorter is investigated, and a Hammerstein predistorter is proposed to eliminate the nonlinear HPA with memory. Finally, we compare the constellation diagram, power spectrum, correlation function, code tracking bias with and without the Hammerstein predistorter. The comparison results demonstrate that a digital predistorter is a potential solution to compensate the HPA nonlinear distortions for wideband GNSS signals. This pre-distortion approach is of great significance that can effectively guarantee the nominal signal quality in space not only during the maintenance of the current GNSSs but also for the future emerging local or global navigation systems.