A Comprehensive Survey of Candidate Waveforms for 5G, beyond 5G and 6G Wireless Communication Systems

The evolution of global mobile data over the past decades in broadcasting, Internet of Things (IoT), education, healthcare, commerce, and energy has put strong pressure on 3G/4G mobile networks to improve their service offerings. These generations of mobile networks were initially invented to meet the requirements of the above-mentioned applications. However, as the requirements in these applications continue to increase, new mobile technologies such as 5G (fifth generation), 5G and beyond (B5G, beyond fifth generation), and 6G (sixth generation) are still progressing and being experimented. These networks are very heterogeneous generations of mobile networks that will have to offer very high throughput per user, good energy efficiency, better traffic capacity per area, improved spectral efficiency, very low latency, and high mobility. To meet these requirements, the radio interface of future mobile networks will have to be flexible and rationalized the available frequency resources. Therefore, new modulation methods, access techniques and waveforms capable of supporting these technological changes are proposed. This review presents brief descriptions of the types of 5G, B5G, and 6G waveforms. The 5G consists of OFDM including its transmission techniques: generalized frequency division multiplexing (GFDM), filter bank based multi-carrier (FBMC), universal filtered multi-carrier (UFMC), and index modulation (IM). Meanwhile, the 6G covers orthogonal time frequency space (OTFS), orthogonal chirp division multiplexing (OCDM) and orthogonal time sequence multiplexing (OTSM). The networks’ potentialities, advantages, disadvantages, and future directions are outlined.

Linearized waveform inversion for vertical transversely isotropic elastic media:Methodology and multi-parameter crosstalk analysis

Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuities.More specifically,seismic migration estimates the reflectivity function(stacked average reflectivity or pre-stack angle-dependent reflectivity)from seismic reflection data.On the other hand,seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations.Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters.Although there exist many differences,pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.Usually,seismic migration and inversion techniques assume an acoustic or isotropic elastic medium.Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property.We present a linearized waveform inversion(LWI)scheme for weakly anisotropic elastic media with vertical transversely isotropic(VTI)symmetry.It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations(ΔVp_(0)/Vp_(0)/Vs_(0)/Vs_(0)/,Δ∈,Δδ)from the long-wavelength reference model.Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration.We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method.The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images.We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters.Especially,the Thomsen parameter is the most difficult to resolve.We also analyze the multi-parameter crosstalk using scattering radiation patterns.The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.

Underwater Pulse Waveform Recognition Based on Hash Aggregate Discriminant Network

Underwater pulse waveform recognition is an important method for underwater object detection.Most existing works focus on the application of traditional pattern recognition methods,which ignore the time-and space-varying characteristics in sound propagation channels and cannot easily extract valuable waveform features.Sound propagation channels in seawater are time-and space-varying convolutional channels.In the extraction of the waveform features of underwater acoustic signals,the effect of high-accuracy underwater acoustic signal recognition is identified by eliminating the influence of time-and space-varying convolutional channels to the greatest extent possible.We propose a hash aggregate discriminative network(HADN),which combines hash learning and deep learning to minimize the time-and space-varying effects on convolutional channels and adaptively learns effective underwater waveform features to achieve high-accuracy underwater pulse waveform recognition.In the extraction of the hash features of acoustic signals,a discrete constraint between clusters within a hash feature class is introduced.This constraint can ensure that the influence of convolutional channels on hash features is minimized.In addition,we design a new loss function called aggregate discriminative loss(AD-loss).The use of AD-loss and softmax-loss can increase the discriminativeness of the learned hash features.Experimental results show that on pool and ocean datasets,which were collected in pools and oceans,respectively,by using acoustic collectors,the proposed HADN performs better than other comparative models in terms of accuracy and mAP.

Co-Sharing Waveform Design for Millimeter-Wave Radar Communication Systems

Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.

Joint Design of ISAC Waveform Under PAPR Constraints

In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.

Simultaneous Waveform Inverse Modelling for Litho-Fluid Prediction in an Old Marginal, “Agbbo”Field, Onshore Niger Delta, Nigeria

Simultaneous waveform inversion was used to predict lithofacies and fluid type across the field. Very often, characterizing reservoirs in terms of lithology and fluid type using conventional methods is replete with uncertainties, especially in marginal fields. An approach is employed in this study that integrated rock physics and waveform inverse modelling for lithology and fluid-type characterization to appropriately identify potential hydrocarbon saturated zones and their corresponding lithology. Seismic and well-log data were analyzed using Hampson Russel software. The method adopted includes lithofacies and fluid content analysis using rock physics parameters and seismic simultaneous inverse modelling. Rock physics analysis identified 2 broad reservoirs namely: HDZ1 and HDZ2 reservoirs. Results from the inverse modelling showed that low values of acoustic impedance from 19,743 to 20,487 (ft/s)(g/cc) reflect hydrocarbon-bearing reservoirs while medium to high values shows brine and shale respectively, with brine zone ranging from 20,487 to 22,531 (ft/s)(g/cc) and shale above 22,531 (ft/s)(g/cc). Two lithofacies were identified from inversion analysis of Vp/Vs and Mu-Rho, namely: sand and shale with VpVs 1.95 values respectively. Mu-Rho > 12.29 (GPa)(g/cc) and <12.29 (GPa) (g/cc) represent sand and shale respectively. From 3D volume, it was observed that a high accumulation of hydrocarbon was observed to be saturated at the north to the eastern part of the field forming a meandering channel. Sands were mainly distributed around the northeastern to the southwestern part of the field, that tends to be away from Well 029. This was also validated by the volume of rigidity modulus (Mu-Rho) showing high values indicating sands fall within the northeastern part of the field.

Upper-mantle velocity structures beneath the Tibetan Plateau and surrounding areas inferred from triplicated P waveforms

P-wave waveforms in the distance range between 12°and 30°were analyzed to investigate upper-mantle P velocity structures beneath the Tibetan Plateau and surrounding areas.The waveform data from 504 earthquakes with magnitudes larger than 5.0 between 1990 and 2005 that occurred within 30°from the center of the Plateau were modelled.We divided the study area into 6 regions and modeled upper-mantle-distance P waveforms with turning points beneath each region separately.The results show that the uppermantle P-wave velocity structures beneath India,the Himalayas,and the Lhasa Terrane are similar and contain a high-velocity lid about 250 km thick.The upper-mantle velocities down to 200 km beneath the Qiangtang Terrane,the Tarim Basin,and especially the Songpan-GarzêTerrane are lower than those in the south.The 410-km discontinuity beneath these two terranes is elevated by about 20 km.Highvelocity anomalies are found in the transition zone below 500 km under the Lhasa and Qiangtang Terranes.The results suggest that the Tibetan Plateau was generated by thrusting of the Indian mantle lithosphere under the southern part of Tibet.Portions of the thickened Eurasian mantle lithosphere were delaminated;they are now sitting in the transition zone beneath southern Tibet and atop of the 410-km discontinuity underneath northern Tibet.

Simutaneous radar imaging and velocity measuring with step frequency waveforms

The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolution range profile since this waveform is greatly sensitive to the Doppler shift. The velocity measurement performance of the four styles is analyzed with two pulse trains consisted of positive and negative step frequency waveforms. The velocity of targets can be estimated first coarsely by using the pulse trains with positive-positive step frequency combination, and then fine by positive-negative combination. Simulation results indicate that the method can accomplish the accurate estimation of the velocity with efficient computation and good anti-noise performance and obtain the good HRRP simultaneously.

Inversion of ocean-bottom seismometer(OBS) waveforms for oceanic crust structure: a synthetic study

The waveform inversion method is applied-- using synthetic ocean-bottom seismometer （OBS） data--to study oceanic crust structure. A niching genetic algorithm （NGA） is used to implement the inversion for the thickness and P-wave velocity of each layer, and to update the model by minimizing the objective function, which consists of the misfit and cross-correlation of observed and synthetic waveforms. The influence of specific NGA method parameters is discussed, and suitable values are presented. The NGA method works well for various observation systems, such as those with irregular and sparse distribu- tion of receivers as well as single receiver systems. A strategy is proposed to accelerate the convergence rate by a factor of five with no increase in computational complex- ity; this is achieved using a first inversion with several generations to impose a restriction on the preset range of each parameter and then conducting a second inversion with the new range. Despite the successes of this method, its usage is limited. A shallow water layer is not favored because the direct wave in water will suppress the useful reflection signals from the crust. A more precise calculation of the air-gun source signal should be considered in order to better simulate waveforms generated in realistic situa- tions; further studies are required to investigate this issue.

Effects of output waveforms on penetration for Nd :YAG laser welding

By using a Nd: YAG laser welding system devised for transmitting continuous, rectangular and pulsed waveforms, comprehensive and deep investigation is focused on the effects of several parameters of rectangular waveform and pulsed output wave superimposed on a rectangular waveform on the penetration depth of weld. Research results indicate that the average power, duty cycle, frequency and peak power of rectangular wave affect the weld penetration depth to different extent. Results of experiments and analysis also indicate that the pulse delay time, pulse width and the power ratio of pulse to rectangular waveform seriously influence the penetration when the pulsed wave is superimposed on a rectangular waveform.

Arbitrary Waveforms Based on Front Panel of Agilent 33250A Function/Arbitrary Waveform Generator

Agilent 33200A family of function/arbitrary waveform generators are widely used in labs for creating arbitrary waveforms.Flexible applications of function/arbitrary waveform generator 33250A which is made by Agilent company are expatiated.There are three methods of transferring waveform data to arbitrary waveform generator 33250A,among which,the front panel method can produce a simple interface for arbitrary waveforms and is applicable to the composition of a small amount of linear waveform segment,and the progress of this method is explained in detail.This way is convenient and can be widely used,and it will offer some good guidance in library works.

Study on atomic layer etching of Si in inductively coupled Ar/Cl_2 plasmas driven by tailored bias waveforms

Plasma atomic layer etching is proposed to attain layer-by-layer etching, as it has atomic-scale resolution, and can etch monolayer materials. In the etching process, ion energy and angular distributions（IEADs） bombarding the wafer placed on the substrate play a critical role in trench profile evolution, thus importantly flexibly controlling IEADs in the process. Tailored bias voltage waveform is an advisable method to modulate the IEADs effectively, and then improve the trench profile. In this paper, a multi-scale model, coupling the reaction chamber model,sheath model, and trench model, is used to research the effects of bias waveforms on the atomic layer etching of Si in Ar/Cl2 inductively coupled plasmas. Results show that different discharge parameters, such as pressure and radio-frequency power influence the trench evolution progress with bias waveforms synergistically. Tailored bias waveforms can provide nearly monoenergetic ions, thereby obtaining more anisotropic trench profile.？？？

Photonic generation of arbitrary waveforms based on incoherent wavelength-to-time mapping

We demonstrate experimentally a radio frequency arbitrary waveform generator using the incoherent wavelength-to-time mapping technique. The system is implemented by amplitude modulation of a broadband optical resource whose spectrum is reshaped by a programmable optical pulse shaper and transmitted over a single mode fiber link. The shape of the generated waveform is controlled by the optical pulse shaper, and the fiber link introduces a certain group velocity delay to implement wavelength-to-time mapping. Assisted by the flexible optical pulse shaper, we obtain different shapes of optical waveforms, such as rectangle, triangle, and sawtooth waveforms. Furthermore, we also demonstrate ultra-wideband generation, such as Gaussian monocycle, doublet, and triplet waveforms, using the incoherent technique.

Construction of Zero Autocorrelation Stochastic Waveforms

Stochastic waveforms are constructed whose expected autocorrelation can be made arbitrarily small outside the origin. These waveforms are unimodular and complex-valued. Waveforms with such spike like autocorrelation are desirable in waveform design and are particularly useful in areas of radar and communications. Both discrete and continuous waveforms with low expected autocorrelation are constructed. Further, in the discrete case, frames for Cd are constructed from these waveforms and the frame properties of such frames are studied.

Construction of Energy-Optimal Smooth Monophasic Defibrillation Pulse Waveforms Using Cardiomyocyte Membrane Model

The goal is to help create smooth energy-optimal monophasic pulse waveforms for defibrillation using the Luo-Rudy cardiomyocyte membrane computer model. The waveforms were described with the help of the piecewise linear function. Each line segment provides a transition from one present level of the transmembrane potential to the next with a minimal energy value. The duration of the last segment was defined as a minimum duration at which an action potential occurs. Monophasic waveforms of segments 3, 10 and 29 were built using different increments of the transmembrane potential. The pulse energy efficiency was evaluated according to their threshold energy ratios in mA2·ms/cm4. There was virtually no difference between the threshold energy ratios of the three waveforms constructed and those of the previously studied energy-optimal half- sine waveform: 241 - 242 and 243 mA2·ms/cm4. The pulse waveform constructed is characterized by a low rise and fall as the duration of the rise is ~1.5 times longer than that of the fall. Conclusion: Energy-optimal smooth monophasic pulse waveforms have the same threshold energy ratio as the optimal half-sine one which was studied before. The latter is equivalent to the first phase of biphasic quasisinusoidal Gurvich-Venin pulse which has been used in Russia since 1972. Thus, the use of the Luo-Rudy cardiomyocyte membrane model appears to offer no possibilities for a substantial increase in the energy efficiency (threshold energy ratio reduction) of the classical monophasic defibrillation pulse waveforms.

A combined denoising method of empirical mode decomposition and singular spectrum analysis applied to Jason altimeter waveforms: A case of the Caspian Sea

During the satellite pulse propagation and reception, the altimeter waveform is inevitably affected by noise. To reduce the noise level in Jason altimeter waveforms, we used singular spectrum analysis(SSA),empirical mode decomposition(EMD), and the combination of SSA and EMD to obtain the denoised waveforms. The advantages of the combined method were verified and the accuracy of the mean sea surface height(MSSH) model was improved. Comparing the denoising effect of the three methods, the results show that the signal-to-noise ratio(SNR), correlation coefficient and root-mean-square error are effectively improved by the combination of SSA and EMD. The sea surface heights(SSHs) were remeasured with a 50% threshold retracker of denoised waveforms, and the MSSH model of the Caspian Sea with a grid of 1’× 1’was established from the retracked SSHs of Jason-1/2/3. Taking the mean value of the four models as a control, it is found that the model calculated by the combined denoising method has the highest accuracy. This indicates that using the combined denoising method to reduce the noise level is beneficial to improve the accuracy of the MSSH model.

Fault Plane Identification Using Three Components Local Waveforms

A research has been conducted to estimate earthquake source parameters that occurred on June 3rd, 13th, 18th and 19th, 2008. The data used to determine the parameters of earthquakes source are three components local waveform that are recorded by three MY broadband stations (IPM, KOM and KUM) and PSI, Poseidon. In this research, we report a focal mechanism of events using three components local waveform analysis. The seismogram data are inverted to achieve the earthquake source parameters. Source parameters of earthquakes extracted after the reduction variant of each event are over 56%. To identify the fault plane, the HC-plot method is used.

High Resolution MIMO-HFSWR Radar Using Sparse Frequency Waveforms

In high frequency surface wave radar (HFSWR) applications, range and azimuth resolutions are usually lim-ited by the bandwidth of waveforms and the physical dimension of the radar aperture, respectively. In this paper, we propose a concept of multiple-input multiple-output (MIMO) HFSWR system with widely sepa-rated antennas transmitting and receiving sparse frequency waveforms. The proposed system can overcome the conventional limitation on resolutions and obtain high resolution capability through this new configura-tion. Ambiguity function (AF) is derived in detail to evaluate the basic resolution performance of this pro-posed system. The advantages of the system of fine resolution and low peak sidelobe level (PSL) are demon-strated by the AF analysis through numerical simulations. The impacts of Doppler effect and the geometry configuration are also studied.

Performances of Micropower UWB Radar Using Orthogonal Waveforms

Radars and their applications were, for a long time, reserved to national defense, air security or weather service domains. For a few years, with the emergence of new technologies, radar applications have been developed and have become known in the civil domain. In particular, the arrival of UWB—Ultra-Wideband technology allows the design of compact and low-cost radars with multiple fields of application. In this paper, we focus on road applications, such as driving assistance with the objective of increasing safety and reducing accidents. In classical UWB radar systems, Gaussian and monocycle pulses are commonly used. In previous works, original waveforms based on orthogonal functions (Hermite and Gegenbauer) were proposed. These provide a good spatial resolution, suitable for radar detection. Another advantage of these waveforms is their multiple access capability, due to their orthogonality. The aim of the study presented in this article is to compare simulation and experimental results obtained, especially for short-range anticollision radar application, using these waveforms in one part and Gaussian and monocycle pulses in the other part. The originality of this paper relies on the new approach. Indeed, this comparison study using these waveforms has never been done before. Finally, some examples of real experiments in a real road environment with different waveforms are presented and analysed.

Microseismic event waveform classification using CNN-based transfer learning models

The efficient processing of large amounts of data collected by the microseismic monitoring system(MMS),especially the rapid identification of microseismic events in explosions and noise,is essential for mine disaster prevention.Currently,this work is primarily performed by skilled technicians,which results in severe workloads and inefficiency.In this paper,CNN-based transfer learning combined with computer vision technology was used to achieve automatic recognition and classification of multichannel microseismic signal waveforms.First,data collected by MMS was generated into 6-channel original waveforms based on events.After that,sample data sets of microseismic events,blasts,drillings,and noises were established through manual identification.These datasets were split into training sets and test sets according to a certain proportion,and transfer learning was performed on AlexNet,GoogLeNet,and ResNet50 pre-training network models,respectively.After training and tuning,optimal models were retained and compared with support vector machine classification.Results show that transfer learning models perform well on different test sets.Overall,GoogLeNet performed best,with a recognition accuracy of 99.8%.Finally,the possible effects of the number of training sets and the imbalance of different types of sample data on the accuracy and effectiveness of classification models were discussed.