Random Phase Shifts Research Articles

Phase reconstruction by phase shift estimation with reliable parameter minimization

Abstract Achieving a balance between accuracy and speed in phase reconstruction is a challenging problem. In phase-shifting interferometry, increasing the speed by reducing the number of phase shifts while maintaining high accuracy is highly desirable. We propose an accurate and efficient two-step phase reconstruction method utilizing random phase shift. This method directly estimates the phase shift through reliable parameter minimization, allowing for easy and precise phase reconstruction. Simulations and experiments demonstrate the superior performance of our method across various scenarios, outperforming well-known two-step phase-shifting algorithms. We expect this paper to provide a general and powerful tool for phase reconstruction.

Energy efficiency optimization for 6G multi-IRS multi-cell NOMA vehicle-to-infrastructure communication networks

Intelligent Reflecting Surfaces (IRS), software-controlled metasurfaces, have emerged as an upcoming sixth-generation (6G) wireless communication technology. IRS intelligently manipulates and optimizes signal propagation using a large-scale array of intelligent elements, enhancing signal coverage, increasing capacity, mitigating path loss, and combating multipath fading This work provides a new energy-efficiency model for multi-IRS-assisted multi-cell non-orthogonal multiple access (NOMA) vehicular to infrastructure communication networks. The objective is the joint optimization of the total power budget at the roadside unit (RSU), NOMA power allocation for the user equipment, and designing phase shifts for IRS in each cell to maximize the achievable energy efficiency of the system. Due to non-convexity, the original non-convex problem is first decoupled and transformed using block coordinate descent and successive convex approximation methods. Then, an efficient solution is achieved using Gradient-based and interior-point methods. We also consider two benchmark schemes: (1) NOMA power optimization at RSU with random phase shift design at IRS and (2) orthogonal multiple access power allocation with optimal phase shift design at IRS. Numerical results show the superiority of the proposed solution compared to the benchmark schemes. The proposed solution outperforms the benchmarks, demonstrating a 59.57% and 151.21% improvement over the NOMA and orthogonal schemes, respectively, at pct=2 dBm. Additionally, it shows up to a 10.43% better performance than OMA at 10 IRS elements.

Modular Assembly of Metamaterials Using Light Gradients.

This is a report on a pilot study that tests the feasibility of assembling photonic metamaterials (PMs) using light gradient forces. Following a strategy that works like modular construction, light gradient forces, produced by a tightly focused, 1D standing wave optical trap, time-multiplexed across a 2D lattice are used to assemble voxels consisting of prefabricated, monodispersed nanoparticles (NPs) with radii ranging from 30 to 500nm into 3D structures on a hydrogel scaffold. Hundreds of NPs can be manipulated concurrently into a complex heterogeneous voxel this way, and then the process can be repeated by stitching together voxels to form a metamaterial of any size, shape, and constituency although imperfectly. Imperfections introduce random phase shifts and amplitude variations that can have an adverse effect on the band structure. Regardless, PMs are created this way using two different dielectric NPs, polystyrene and rutile, and then the near-infrared performance for each is analyzed with angle-, wavelength-, and polarization-dependent reflection spectroscopy. The cross-polarized spectra show evidence of a resonance peak. Interestingly, whereas the line shape from the polystyrene array is symmetric, the rutile array is not, which may be indicative of Fano resonance. So, even with the structural defects, reflection spectroscopy reveals a resonance.

Dynamics of large oscillator populations with random interactions.

We explore large populations of phase oscillators interacting via random coupling functions. Two types of coupling terms, the Kuramoto-Daido coupling and the Winfree coupling, are considered. Under the assumption of statistical independence of the phases and the couplings, we derive reduced averaged equations with effective non-random coupling terms. As a particular example, we study interactions defined via the coupling functions that have the same shape but possess random coupling strengths and random phase shifts. While randomness in coupling strengths just renormalizes the interaction, a distribution of the phase shifts in coupling reshapes the coupling function.

Dynamics of Oscillator Populations Globally Coupled with Distributed Phase Shifts.

We consider a population of globally coupled oscillators in which phase shifts in the coupling are random. We show that in the maximally disordered case, where the pairwise shifts are independent identically distributed random variables, the dynamics of a large population reduces to one without randomness in the shifts but with an effective coupling function, which is a convolution of the original coupling function with the distribution of the phase shifts. This result is valid for noisy oscillators and/or in the presence of a distribution of natural frequencies. We argue also, using the property of global asymptotic stability, that this reduction is valid in a partially disordered case, where random phase shifts are attributed to the forced units only. However, the reduction to an effective coupling in the partially disordered noise-free situation may fail if the coupling function is complex enough to ensure the multistability of locked states.

Dependence of the Values of Inter-Component Phase Relations of the Harmonic Components of Vibration on the Displacement of Misaligned Shafts

The analytical dependence of the phases and values of intercomponent phase relations of the harmonic components of vibration displacement of misaligned shafts on their displacement has been presented in the article. Harmonic vibrations of the shafts were modeled using a Lagrangian connecting vibration displacement and forces acting in the system. For ease of derivation, the Lagrangian is rewritten in complex form. The resulting algebraic equations connect the complex amplitudes of vibration components with the amplitudes of periodic forces at the same frequencies and the parameters of the mechanical system (stiffness, damping). The amplitudes of periodic forces are related to the magnitude of the shafts angular and parallel misalignment according to the accepted model. Calculation of intercomponent phase relations values is used to get rid of the random initial phase shift caused by the choice of the timing reference. The magnitude of the effect produced by the misalignment of the shafts on the amplitudes and values of the intercomponent phase relations of the signal components is estimated. The obtained resultcan be used to construct devices for estimation shaft displacements and devices for assessing the condition of equipment based on the analysis of vibration signals.ls.

Fourier-transform-only method for random phase shifting interferometry

An accurate and computationally simple phase shifting interferometry (PSI) method is developed to reconstruct phase maps without a priori knowledge of the phase shift. Previous methods developed for random PSI either do not address general sources of error or require complex iterative processes and increased computational time. Here we demonstrate a novel method that is able to extract the phase using only Fourier transform (FT). With spatial FT analysis, randomly phase-shifted data is reordered to allow performing temporal FT on the intensity, which is a function of the phase shift. Since the entire process, including order analysis and phase calculation, is based only on Fourier analysis, it is rapid, easy to implement, and addresses general sources of error. The method exhibits high performance in experiments containing random phase shifts. Moreover, simulations incorporating common experimental error sources such as random intensity noise, intensity harmonics, and phase shift errors demonstrate that the proposed method performs as good as or better than the state-of-the-art phase reconstruction techniques in terms of accuracy and time.

High accuracy, compact 3D face imaging method based on translational and online-switchable phase-shifting fringe projection.

In this paper, a compact, cost-effective, and fast translational online-switchable phase-shifting fringe (TOPF) projector is designed and fabricated for high accuracy three-dimensional (3D) face imaging. Compared with the conventional mechanical projectors, the main difference is that it utilizes a translational approach instead of a rotational one to achieve a better balance in terms of size, speed, accuracy, and cost. To mitigate the inconsistency of the motor's step size and ensure the stability of phase-shifting, an optical encoder-based feedback control mechanism is employed. Additionally, to address the random phase shift errors induced by mechanical motion, a fast, generalized phase-shifting algorithm with unknown phase shifts (uPSAs) that can calculate arbitrary phase shifts is proposed. Finally, a 3D imaging system consisting of the TOPF projector and two cameras is constructed for experimental validation. The feasibility, effectiveness, and precision of our proposed method are substantiated through the reconstruction of a static facial model and a dynamic real face.

CSI-F: A Human Motion Recognition Method Based on Channel-State-Information Signal Feature Fusion.

The recognition of human activity is crucial as the Internet of Things (IoT) progresses toward future smart homes. Wi-Fi-based motion-recognition stands out due to its non-contact nature and widespread applicability. However, the channel state information (CSI) related to human movement in indoor environments changes with the direction of movement, which poses challenges for existing Wi-Fi movement-recognition methods. These challenges include limited directions of movement that can be detected, short detection distances, and inaccurate feature extraction, all of which significantly constrain the wide-scale application of Wi-Fi action-recognition. To address this issue, we propose a direction-independent CSI fusion and sharing model named CSI-F, one which combines Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). Specifically, we have introduced a series of signal-processing techniques that utilize antenna diversity to eliminate random phase shifts, thereby removing noise influences unrelated to motion information. Later, by amplifying the Doppler frequency shift effect through cyclic actions and generating a spectrogram, we further enhance the impact of actions on CSI. To demonstrate the effectiveness of this method, we conducted experiments on datasets collected in natural environments. We confirmed that the superposition of periodic actions on CSI can improve the accuracy of the process. CSI-F can achieve higher recognition accuracy compared with other methods and a monitoring coverage of up to 6 m.

Wavefront Reconstruction Using Two-Frame Random Interferometry Based on Swin-Unet

Due to its high precision, phase-shifting interferometry (PSI) is a commonly used optical component detection method in interferometers. However, traditional PSI, which is susceptible to environmental factors, is costly, with piezoelectric ceramic transducer (PZT) being a major contributor to the high cost of interferometers. In contrast, two-frame random interferometry does not require precise multiple phase shifts, which only needs one random phase shift, reducing control costs and time requirements, as well as mitigating the impact of environmental factors (mechanical vibrations and air turbulence) when acquiring multiple interferograms. A novel method for wavefront reconstruction using two-frame random interferometry based on Swin-Unet is proposed. Besides, improvements have been made on the basis of the established algorithm to develop a new wavefront reconstruction method named Phase U-Net plus (PUN+). According to training the Swin-Unet and PUN+ with a large amount of simulated data generated by physical models, both of the methods accurately compute the wrapped phase from two frames of interferograms with an unknown phase step (except for multiples of π). The superior performance of both methods is effectively showcased by reconstructing phases from both simulated and real interferograms, in comprehensive comparisons with several classical algorithms. The proposed Swin-Unet outperforms PUN+ in reconstructing the wrapped phase and unwrapped phase.

The effects of range and echo-phase on range resolution in bottlenose dolphins (Tursiops truncatus) performing a successive comparison taska).

Echolocating bats and dolphins use biosonar to determine target range, but differences in range discrimination thresholds have been reported for the two species. Whether these differences represent a true difference in their sensory system capability is unknown. Here, the dolphin's range discrimination threshold as a function of absolute range and echo-phase was investigated. Using phantom echoes, the dolphins were trained to echo-inspect two simulated targets and indicate the closer target by pressing a paddle. One target was presented at a time, requiring the dolphin to hold the initial range in memory as they compared it to the second target. Range was simulated by manipulating echo-delay while the received echo levels, relative to the dolphins' clicks, were held constant. Range discrimination thresholds were determined at seven different ranges from 1.75 to 20 m. In contrast to bats, range discrimination thresholds increased from 4 to 75 cm, across the entire ranges tested. To investigate the acoustic features used more directly, discrimination thresholds were determined when the echo was given a random phase shift (±180°). Results for the constant-phase versus the random-phase echo were quantitatively similar, suggesting that dolphins used the envelope of the echo waveform to determine the difference in range.

Disco Intelligent Reflecting Surfaces: Active Channel Aging for Fully-Passive Jamming Attack

Due to the open communications environment in wireless channels, wireless networks are vulnerable to jamming attacks. However, existing approaches for jamming rely on knowledge of the legitimate users’ (LUs’) channels, extra jamming power, or both. To raise concerns about the potential threats posed by illegitimate intelligent reflecting surfaces (IRSs), we propose an alternative method to launch jamming attacks on LUs without either LU channel state information (CSI) or jamming power. The proposed approach employs an adversarial IRS with random phase shifts, referred to as a “disco” IRS (DIRS), that acts like a “disco ball” to actively age the LUs’ channels. Such active channel aging (ACA) interference can be used to launch jamming attacks on multi-user multiple-input single-output (MU-MISO) systems. The proposed DIRS-based fully-passive jammer (FPJ) can jam LUs with no additional jamming power or knowledge of the LU CSI, and it can not be mitigated by classical anti-jamming approaches. A theoretical analysis of the proposed DIRS-based FPJ that provides an evaluation of the DIRS-based jamming attacks is derived. Based on this detailed theoretical analysis, some unique properties of the proposed DIRS-based FPJ can be obtained. Furthermore, a design example of the proposed DIRS-based FPJ based on one-bit quantization of the IRS phases is demonstrated to be sufficient for implementing the jamming attack. In addition, numerical results are provided to show the effectiveness of the derived theoretical analysis and the jamming impact of the proposed DIRS-based FPJ.

Pulse Characteristics of Actively Q‐ Switched Random Fiber Laser Based on Random Phase Shift Grating and Their Evolution

Pulse Characteristics of Actively Q‐ Switched Random Fiber Laser Based on Random Phase Shift Grating and Their Evolution

Design and Performance Analysis of Massive MIMO Modeling with Reflected Intelligent Surface to Enhance the Capacity of 6G Networks

Reflected Intelligent Surface (RIS) can establish a virtual line-of-sight link to enhance system performance while consuming less power in non-line-of-sight. RIS technique is utilized to minimize the spreading of electromagnetic signals by modifying the surface's electric and magnetic field characteristics. RIS can be adopted with the existing environment to effectively increase efficiency by modifying the radio channel characteristics. The signals are steered to the receiver using an RIS thus improving the link quality. The radio channel is viewed in traditional wireless systems as an uncontrollable entity that typically tampers with transmitted signals. This paper suggests an alternate theoretical model after examining the prevalent models and potential issues. Security of the wireless communication physical layer can be improved with an RIS by just changing the phase of the reflective unit. In this work, the massive Multiple Input Multiple Outputs (MIMO)-based iterative modeling technique is used to build the transmitter, channel, and receiver section. This will simultaneously optimize the RIS passive beamforming pre-coding matrix and thus avoid multi-user interference. At the base station cyclic programming is adopted, it iteratively calculates the active and passive beam-forming RIS matrices. The simulation results demonstrate that the combined pre-coding technique used in this work improves the weighted sum rate, efficiency, and coverage ratio. The results show that MIMO with continuous phase shift RIS achieves a higher Weighted Sum Ratio (WSR) and minimum Channel State Information (CSI) error in comparison with the random phase shift RIS. The performance metrics sum rate, signal-to-interference plus noise ratio (SINR), energy efficiency, and transmit power are analyzed and compared.

SE Analysis and GEE Optimization of Hardware-Impaired Multi-Cell Massive MIMO Systems With Rician Fading and Phase Shifts

We consider a practical hardware-impaired multi-cell massive multi-input multi-output (mMIMO) system with spatially-correlated Rician fading channels, whose line-of-sight component experiences a random phase shift. The multi-cell mMIMO system employs two-layer large-scale fading decoding (LSFD) to mitigate the interference due to pilot contamination. We consider a dynamic analog-to-digital converter (ADC) architecture at the base stations (BS), which enables us to independently vary the resolution of ADC connected to its each antenna, and thus properly choose them to achieve a high spectral efficiency (SE). Both BS and user equipments (UEs) are also equipped with low cost radio frequency chains, which introduce additional hardware impairments. We first derive a closed-form SE expression for this system, and then optimize the UEs uplink data power and LSFD vectors to maximize the global energy efficiency metric. The proposed optimization, which is practically implementable due to its closed-form updates, is derived by combining the quadratic and Dinkelbach transforms, and generalized Rayleigh quotient. We investigate the ADC resolution and hardware impairments values for which LSFD is highly effective, and the values for which its effectiveness reduces.

Joint optimization scheme for the reconfigurable intelligent surface-assisted untrusted relay networks

To further improve the secrecy rate, a joint optimization scheme for the reconfigurable intelligent surface (RIS) phase shift and the power allocation is proposed in the untrusted relay (UR) networks assisted by the RIS. The eavesdropping on the UR is interfered by a source-based jamming strategy. Under the constraints of unit modulus and total power, the RIS phase shift, the power allocation between the confidential signal and the jamming signal, and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate. The complex multivariable coupling problem is decomposed into three sub-problems, and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation. Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme, the random phase shift scheme, and the no-RIS scheme.

Spectral and temporal cues used by echolocating bottlenose dolphins to discriminate changes in inter-highlight intervals

Echolocating dolphins use spectral cues to discriminate complex echoes from targets with multiple reflective surfaces; however, the specific cues involved are not clear. This study investigated the role of spectral interference patterns on the dolphin’s ability to discriminate two-highlight echoes. In task one of the study, two dolphins were trained to echolocate, listen to returning electronic (“phantom”) echoes with two identical highlights, and produce a conditioned acoustic response if the inter-highlight interval (IHI) increased. The amount that the IHI increased varied across trials. Task two replicated task one but applied a random phase shift to all highlights. This varied the specific locations of notches along the frequency axis in the complex echo spectrum but preserved the notch spacing (equal to the inverse of the IHI). For IHIs less than 250 μs, discrimination thresholds increased with IHI and were larger with random phase shifts. For IHIs greater than 250 μs, thresholds plateaued and were similar for both tasks. Results agree with those from a previous study with passively listening dolphins. Namely, echolocating dolphins can use the spacing of notches in spectral interference patterns to detect IHI changes within the ∼250-μs temporal window, but temporal cues are used at longer IHIs. [Work supported by ONR]

Slightly Off-Axis Digital Holography Using a Transmission Grating and GPU-Accelerated Parallel Phase Reconstruction

Slightly off-axis digital holography is proposed using transmission grating to obtain quantitative phase distribution. The experimental device is based on an improved 4f optical system in which a two-window input plane is used to form the object beam and reference beam. Then, the two beams are diffracted into multiple orders by the transmission grating placed at the Fourier plane. By applying a modified Michelson configuration, the interference patterns can be generated by the object and reference beams from different diffraction orders. After translating the grating, a random phase shift can be introduced to the hologram. To demonstrate the feasibility of our method, both thick and thin phase specimens are retrieved using two carrier phase-shifting holograms. Furthermore, we use the phase reconstruction algorithm based on the NVIDIA CUDA programming model to reduce the retrieval time. Meanwhile, we optimize the discrete cosine transform (DCT)-based least-squares unwrapping algorithm to unwrap the phase. By porting the entire phase reconstruction process to the graphics processing unit (GPU), the phase retrieval acceleration and execution efficiency significantly improve. To demonstrate the feasibility of our method, it is found that our method can measure the surface profiles of standard elements, such as a plano-convex cylinder lens and a microlens array, with a relative error of about 0.5%. For holograms with a different phase shift, the root-mean-square (RMS) value of the phase difference for the main imaging region is about 0.2 rad. By accelerating the phase reconstruction with GPU implementation, a speedup ratio of about 20× for the thick phase specimen and a speedup ratio of about 15× for the thin-phase specimen can be obtained for holograms with a pixel size of 1024 × 1024.

An Energy-Efficient Optimization Method for High-Speed Rail Communication Systems Assisted by Intelligent Reflecting Surfaces (IRS)

This paper proposes an intelligent reflecting surface (IRS)-assisted energy efficiency optimization algorithm to address the problem of energy efficiency (EE) degradation in high-speed rail communication systems caused by line-of-sight link blockages between base stations and trains. The joint optimization of base station beamforming and IRS phase shifts is formulated as a variable-coupled energy efficiency maximization problem, subject to the base station’s transmission power and the IRS unit’s modulus constraints. This is known to be an NP-hard problem, making it challenging to obtain the global optimal solution. To tackle the issue of optimization variable coupling, an alternating optimization is employed to decompose the original problem into two sub-problems: base station beamforming and IRS phase-shift optimization. The Dinkelbach method is utilized to convert the fractional objective function into a difference form; then, the successive convex approximation (SCA) algorithm is applied to transform non-convex constraints into convex ones, which are solved using CVX. The Riemann conjugate gradient (RCG) algorithm can effectively solve the difficult unit module constraint. Finally, an alternating iterative strategy is employed to converge to a suboptimal solution. Our simulation results demonstrate that the proposed algorithm significantly enhances system efficiency with low computational complexity. Specifically, when the number of IRS reflecting elements is 64, the system’s EE is improved by approximately 12.41%, 35.26%, and 37.96% compared to the semi-definite relaxation algorithm, the random phase shift approach, and no IRS scheme, respectively.

An improved WiFi sensing based indoor navigation with reconfigurable intelligent surfaces for 6G enabled IoT network and AI explainable use case

The expanding number of low cost sensors and smart devices drives the internet-of-things (IoT) ecosystem of the future. These sensing devices are connected to the internet for information exchange. The location and positioning of these nodes is very important information required in vast range of location based services like smart homes, smart healthcare, environmental monitoring, personal navigation and smart transportation. This paper presents an intelligent solution for node localization in a 6G enabled IoT network. An indoor communication network scenario is proposed in which reconfigurable intelligent surfaces (RISs) are installed to locate the sensor nodes operating in that network. The performance evaluation of the proposed scheme is carried out with optimum number of reflecting elements and optimum phase shifts. It is observed that optimized RISs with 100 reflecting elements improve the estimated localization error by 7.4% over non-optimum RISs. Also, the minimum gain of 6% in localization error is offered using equal phase shifts over random phase shifts. Further, the effect of channel conditions on the average estimation error in node locations is also elaborated. In the end, the explainable artificial intelligence (XAI) empowered indoor localization is discussed as a use case scenario and the performance comparison of the algorithms is evaluated.