Discrete Shifts Research Articles

Energy Efficiency Maximization in RIS-Assisted SWIPT Networks With RSMA: A PPO-Based Approach

This paper investigates reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) networks with rate splitting multiple access (RSMA). An energy efficiency (EE) maximization problem is formulated subject to the power budget at the transmitter and the quality of service (QoS) requirements of both information communication and energy harvesting, where the beamforming vectors, the power splitting (PS) ratios, the common message rates, and the discrete phase shifts are jointly optimized. To tackle the non-convex problem with both discrete and continuous variables, a deep reinforcement learning-based approach is proposed with the proximal policy optimization (PPO) framework. Different from traditional optimization approaches which optimizes the beamforming vectors and phase shifts separately and alternatively, our proposed PPO-based approach optimizes all the variables in unison. Besides, to perform beamforming design in action space, the beamforming vectors for the common stream and the private stream are respectively designed based on the maximum-ratio transmission and the zero forcing to enhance both energy and information transmission. To evaluate the performance of the PPO-based approach, a successive convex approximation (SCA) and Dinkelbach’s method based solution scheme (named SCA-D scheme) is also presented. Simulation results show that the system EE obtained by the proposed PPO-based approach is close to that obtained by the SCA-D scheme while outperforming various benchmarks. The RSMA contributes to the EE of the system greatly compared with traditional scheme. As for the case of time-varying channels, the proposed PPO-based approach is with much smaller running time by only sacrificing a slight EE performance compared with the SCA-D scheme.

A Novel Maximum Distance Separable Coded OFDM-RIS for 6G Wireless Communications

The vision of the sixth generation mobile communication (6G) calls for extremely reliable data transmission over complex and diverse wireless channels. By combining the maximum distance separable (MDS) codes with the classic orthogonal frequency division multiplexing (OFDM), we present a new paradigm with the assistance of the reconfigurable intelligent surfaces (RIS). In our design, the RIS with limited phase shifts are adopted and the pairwise error probability (PEP) of the proposed system is first derived. Then, in order to further minimize the bit error rate (BER), we provide a novel method based on phase alignment to obtain the optimal solution for the discrete phase shifts. Our simulation results show that the proposed scheme provides considerable BER performance improvements compared to conventional OFDM systems. Moreover, the proposed discrete phase optimization algorithm is capable of achieving performance similar to that of the system with continuous phase shifts.

19 F-Labeled Probes for Recognition-Enabled Chromatographic 19 F NMR.

The NMR technique is among the most powerful analytical methods for molecular structural elucidation, process monitoring, and mechanistic investigations; however, the direct analysis of complex real-world samples is often hampered by crowded NMR spectra that are difficult to interpret. The combination of fluorine chemistry and supramolecular interactions leads to a unique detection method named recognition-enabled chromatographic (REC) 19 F NMR, where interactions between analytes and 19 F-labeled probes are transduced into chromatogram-like 19 F NMR signals of discrete chemical shifts. In this account, we summarize our endeavor to develop novel 19 F-labeled probes tailored for separation-free multicomponent analysis. The strategies to achieve chiral discrimination, sensitivity enhancement, and automated analyte identification will be covered. The account will also provide a detailed discussion of the underlying principles for the design of molecular probes for REC 19 F NMR where appropriate.

Speeding up: Discrete mediolateral perturbations increased self-paced walking speed in young and older adults

BackgroundIn uncertain environments and with increasing age humans often walk slower while taking shorter, quicker, and wider steps, reflective of a cautious gait. Understanding when humans opt to use a cautious gait and the differences in gait strategies used as people age could be examined with perturbations on a self-paced treadmill that allows participants to adjust their walking speed. Adding varying degrees of unpredictability, an inherent element of real-world walking could also improve understanding of when specific gait strategies are used. Research questionWe investigated how healthy young and older adults adjust their gait strategies when responding to perturbations of varying unpredictability. We hypothesized that more unpredictable perturbations would produce more cautious gait strategies and be more pronounced in older adults than young adults. MethodsTen young and ten older adults walked on a self-paced treadmill with discrete mediolateral treadmill shift perturbations. We changed the shift magnitude and/or the timing of the perturbations during the gait cycle to vary perturbation unpredictability. We analyzed walking speed and step kinematics from treadmill and motion capture data. ResultsSurprisingly, participants walked faster not slower for the conditions with perturbations. Even more surprising older adults walked faster overall than young adults. As expected, participants took faster and wider steps for the most unpredictable perturbation but also took longer steps which was not expected. Step kinematic variability and average step width also increased as perturbation unpredictability increased suggesting that the more unpredictable conditions demanded greater balance control. Additionally, older adults had greater step kinematic variability, highlighted further using detrended step length variability, compared to young adults SignificanceOverall, these findings provide new insights about gait strategies and suggest that perturbations such as discrete mediolateral treadmill shifts can potentially be designed to encourage participants to walk faster if it is beneficial.

Wireless Powered Intelligent Reflecting Surface for Improving Broadcasting Channels

Intelligent reflecting surface (IRS) is a promising technology for the 6G networks and attracts much attention. However, existing research seldom considers its energy demand. In this paper, we study an IRS assisted multiple-input single-output downlink broadcasting system where there exist one access point (AP), multiple users and a wireless powered IRS. We focus on the broadcasting data transmission which includes two phases. In the first phase, the AP transmits broadcasting data to users and energy signals for IRS energy harvesting (EH). In the second phase, the AP broadcasts messages with the assistance of the IRS. We aim at maximizing the transmission throughput by designing the phase duration scheduling, the transmit beamforming at the AP in each phase, the energy signal covariance matrix and the IRS reflect beamforming with discrete phase shifts. We first propose a semidefinite relaxation (SDR) based transmission design by also employing one-dimensional line search and further proposing a randomization process. Then, a low complexity transmission design has been further developed. Simulation results demonstrate that the SDR based design can almost achieve the optimal and the low complexity design can perform close to the SDR based design with much lower complexity.

Deep Learning-Based Two-Timescale CSI Feedback for Beamforming Design in RIS-Assisted Communications

This letter proposes a deep learning-based two-timescale channel state information feedback framework called RIS-CsiNet for beamforming (BF) design and discrete phase shift design in reconfigurable intelligent surface (RIS)-assisted frequency-division duplexing systems, where the direct link between the base station (BS) and the user equipment (UE) is blocked. Given that the BS-RIS channel is quasi-static and the RIS-UE channel rapidly changes, the feedback is divided into two types: large-timescale and small-timescale feedback. At the beginning of the large-timescale feedback, the neural network (NN)-based encoder at the UE compresses and feedbacks the BS-RIS channel to the BS. On the basis of the received BS-RIS channel information, an NN-based hypernetwork adopted at the BS generates the weights of the NNs that directly produce the BF vector and RIS phase shifts according to the received feedback information of the RIS-UE channel. In the small-timescale feedback, only the RIS-UE channel is fed back by the encoder. The BF vector and phase shifts are produced by the NNs generated in the large timescale. Simulation results show that RIS-CsiNet considerably outperforms conventional algorithms in terms of achievable rate and complexity.

Hardware-Impaired RIS-Assisted mmWave Hybrid Systems: Beamforming Design and Performance Analysis

Reconfigurable intelligent surface (RIS) has been envisioned as an innovative technology to assist millimeter wave (mmWave) communications. Thanks to both advantages of low hardware cost and low power consumption, the hybrid transceiver structure also becomes an integral component of mmWave systems. However, due to practical limitations of hardware components, the RIS-assisted mmWave communications usually suffer unavoidable hardware impairments (HWIs). In this paper, we aim to minimize the (sum) MSE and maximize the average rate of the hardware-impaired RIS-assisted point-to-point mmWave MIMO system, respectively, by jointly optimizing the hybrid transceiver and RIS reflection coefficients under the realistic discrete phase shift constraints. We firstly consider the single-antenna user case and propose efficient alternating optimization (AO) algorithms to solve the two intractable problems. A binary-oriented exact penalty (BEP) method is developed for the involved discrete optimization, which is able to strike a good trade-off between performance and complexity. Moreover, we analyze the optimality of AO algorithms under the cascaded line-of-sight (LoS) channel condition, and reveal both the MSE floor effect and average rate saturation effect in the high-SNR regime. The above studies are then extended to the general multi-antenna user case, where a low-complexity two-phase scheme with the aim of creating the favorable RIS-cascaded channel in the first phase and enhancing system performance in the second phase is proposed. This two-phase scheme is also demonstrated to attain the optimal performance in the LoS scenario. Numerical results validate our theoretical analysis and illustrate superior performance of the proposed algorithms over various benchmark schemes.

Applications of Differential-Difference Algebra in Discrete Calculus

Discrete calculus deals with developing the concepts and techniques of differential and integralcalculus in a discrete setting, often using difference equations and discrete function spaces. This paperexplores how differential-difference algebra can provide an algebraic framework for advancing discretecalculus. Differential-difference algebra studies algebraic structures equipped with both differential anddifference operators. These hybrid algebraic systems unify continuous and discrete analogues ofderivatives and shifts. This allows the development of general theorems and properties that cover bothsettings. In particular, we construct differential-difference polynomial rings and fields over discretefunction spaces. We define discrete derivatives and shifts algebraically using these operators. We thenstudy integration, summation formulas, fundamental theorems, and discrete analogues of multivariatecalculus concepts from an algebraic perspective. A key benefit is being able to state unified theorems indifferential-difference algebra that simultaneously yield results for both the continuous and discretecases. This provides new tools and insights for discrete calculus using modern algebraic techniques.We also discuss applications of representing discrete calculus problems in differential-differencealgebras. This allows bringing to bear algebraic methods and software tools for their solution. Specificexamples are provided in areas such as numerical analysis of discrete dynamical systems definedthrough difference equations. The paper aims to demonstrate the capabilities of differential-differencealgebra as a unifying framework for further developing the foundations and applications of discretecalculus. Broader connections to algebraic modeling of discrete physical systems are also discussed.

Multi-IRS Assisted Wireless-Powered Mobile Edge Computing for Internet of Things

This paper proposes a multiple intelligent reflecting surfaces (IRSs) assisted wireless-powered mobile edge computing (MEC) system, where the IRSs are deployed to assist both the downlink wireless power transfer (WPT) from the multi-antenna hybrid access point (HAP) to the wireless devices (WDs) and the uplink computation offloading from the WDs to the MEC server. To further improve the system performance, the energy beamforming and multiple-user detection (MUD) technologies are exploited. We consider both partial and binary offloading schemes and formulate the sum computation rate (SCR) maximization problems for them, respectively. To tackle the non-convexity of each problem, we propose an efficient alternating optimization (AO) method. Specifically, the Lagrange duality method is used to optimize the energy beamforming vector and the MUD matrix at the HAP, and the CPU frequencies and transmit power of the WDs. Then, we optimize the discrete phase shifts via the successive convex appropriation (SCA) method, the rank-one equivalents, and rounding method. Finally, the optimal time scheduling can be obtained via the one-dimensional search method. In addition, we propose a greedy algorithm with low complexity to optimize the computing modes for the binary offloading scheme. Numerical results show that our proposed schemes outperform the benchmarks.

Joint User Scheduling and Phase Shift Design for RIS Assisted Multi-Cell MISO Systems

This letter investigates the joint user scheduling and phase shift design for reconfigurable intelligent surface (RIS) assisted multi-cell downlink systems. A closed-form ergodic sum spectral efficiency (SE) approximation is utilized as the optimization metric. Based on this approximation, we schedule the users, whose cascaded channels are mostly correlated with each other’s, to maximize each user’s effective signal. Moreover, the RIS phase shift is designed to be the mean of the scheduled users’ cascaded channel phases. With the proposed transmission design, we find the optimal RIS deployment to achieve the highest maximum throughput which depends only on the relative locations of the BSs and RIS. In addition, we consider a more practical discrete RIS phase shift design based on a discrete Fourier transform (DFT) codebook. Simulation results show that the proposed low-complexity scheduling algorithm performs well.

Cost-Efficient RIS-Assisted Transmitter Design With Discrete Phase Shifts for Wireless Communication

In this letter, in order to achieve higher spectral and energy efficiency, we propose a novel cost-efficient transmitter conceptual design based on reconfigurable intelligent surface (RIS) with discrete phase shifts. The key idea is to directly utilize the digital signal to adjust the discrete reflection coefficients of RIS, resulting that the phases of the reflected carrier signal being modulated without the need for complex digital signal processing (DSP) hardware and costly radio frequency (RF) chains. Furthermore, a joint digital modulation and beamforming method is developed to enable information transmission as well as enhance signal strength. Based on the proposed transmitter, we derive the closed-form expressions of the signal-to-noise ratio (SNR) and bit error rate (BER) of the received signal and analyze the impact of hardware constraints on communication performance. Extensive simulation results validate that the novel design of RIS-assisted transmitter provides a cost-effective and power-efficient solution for wireless communications.

RIS-Assisted Scheduling for High-Speed Railway Secure Communications

With the rapid development of high-speed railway systems and railway wireless communication, the application of ultra-wideband millimeter wave band is an inevitable trend. However, the millimeter wave channel has large propagation loss and is easy to be blocked. Moreover, there are many problems such as eavesdropping between the base station (BS) and the train. As an emerging technology, reconfigurable intelligent surface (RIS) can achieve the effect of passive beamforming by controlling the propagation of the incident electromagnetic wave in the desired direction. We propose a RIS-assisted scheduling scheme for scheduling interrupt flows and improving quality of service (QoS). In the propsed scheme, an RIS is deployed between the BS and multiple mobile relays (MRs). By jointly optimizing the beamforming vector and the discrete phase shift of the RIS, the constructive interference between direct link signals and reflected link signals can be achieved, and the channel capacity of eavesdroppers is guaranteed to be within a controllable range. Finally, the purpose of maximizing the number of successfully scheduled flows and satisfying their QoS requirements can be practically realized. Extensive simulations demonstrate that the proposed scheme has superior performance regarding the number of completed flows and the system secrecy capacity over four baseline schemes in literature.

Joint information transmission design for intelligent reflecting surface aided system with discrete phase shifts

Joint information transmission design for intelligent reflecting surface aided system with discrete phase shifts

Inverse design of broadband acoustic metasurfaces for reflective wavefront modulation through the topology optimization method

The design of broadband acoustic metasurfaces is an important research challenge. Topology optimization with a genetic algorithm (TOGA) is used in this paper to design a set of reflection acoustic metasurfaces with discrete phase shift characteristics. This method allows the design of selective single-frequency and broadband metasurfaces. First, nine metasurface units are designed with a total phase gradient of 2π at 3500 Hz. Simulations and experiments verify the anomalous reflection phenomenon of the metasurface in the reflected sound field and achieve wave focusing and self-bending functions by adjusting the position distribution of the units. Compared with single-frequency optimization studies, broadband acoustic metasurface units are designed with a linear phase dispersion in the range of 2000–5000 Hz, which achieves anomalous reflection with the same reflection angle and acoustic focusing phenomenon under broadband incident sound conditions. The ability of the algorithm to modulate the acoustic phase dispersion and the potential mechanism of generating different phase differences are further investigated. This method provides more accurate phase controllability for broadband acoustic metasurface optimization design and provides some ideas for the design of broadband structures in related fields.

Spatiotemporal Acoustic Communication by a Single Sensor via Rotational Doppler Effect.

A longstanding pursuit in information communication is to increase transmission capacity and accuracy, with multiplexing technology playing as a promising solution. To overcome the challenges of limited spatial information density and systematic complexity in acoustic communication, here real-time spatiotemporal communication is proposed and experimentally demonstrated by a single sensor based on the rotational Doppler effect. The information carried in multiplexed orbital-angular-momentum (OAM) channels is transformed into the physical quantities of the temporal harmonic waveform and simultaneously detected by a single sensor. This single-sensor configuration is independent of the channel number and encoding scheme. The parallel transmission of complicated images is demonstrated by multiplexing eight OAM channels and achieving an extremely-low bit error rate (BER)exceeding 0.02%, owing to the intrinsic discrete frequency shift of the rotational Doppler effect. The immunity to inner-mode crosstalk and robustness to noise of the simple and low-cost communication paradigm offers promising potential to promote relevant fields.

Impact of the Refractive Index on the Achievable Rate of Liquid Crystal-Based Digital-RIS Indoor VLC Systems

In wireless networks, reconfigurable intelligent surfaces (RISs) have recently been proven to have a significant impact. The RIS has been incorporated into wireless communication systems to improve security, increase coverage, reduce interference, and improve transmission quality. Digital RIS (DRISs) have also proven to provide better reflection management. However, the impact of the DRIS intrinsic parameters on the system's achievable rate, has not yet been investigated. Due to their availability and easily reconfigurable properties, liquid crystals (LCs) appear as suitable materials for use in DRIS, specifically in optical communication systems. This paper analyzes the effect of the LC's refractive index on the achievable rate of LC-based DRIS indoor visible light communication systems. Based on a set of discrete phase shifts, required refractive indices have been evaluated. The reflected power and achievable rates are determined with respect to incoming light wavelengths at 510 nm, 550 nm, and 670 nm. According to the obtained numerical results, there is no linear relationship between refractive indices, corresponding transition coefficients, phase shifts, light power, and achievable rate.

One-Carbon Metabolism, a Nutrient Dependent Mediator of Angiogenesis and Alveolar Formation in the Developing Lung

Background/Objective: Lung maturation has discrete dynamic shifts in metabolic derivatives that give rise to stage specific metabolite signatures. Components of one-carbon metabolism (OCM) are significantly increased in the late saccular and alveolar stage while hyperoxia disrupts OCM metabolism during these lung developmental stages. We hypothesize that disrupted OCM metabolites in the immature lung disrupts vessel dependent alveolar formation thus contributing to alveolar dysplasia. Our studies explore the impact that restoration of OCM has on angiogenesis and alveolar formation.Methods: Isolated human neonatal circulating Endothelial Colony Forming Cells (ECFCs) were examined for proliferation (WST-1), migration (scratch assay), and angiogenesis (matrigel) in response to supplementation of OCM derivatives, essential amino acid methionine and nicotinamide. OCM enzyme levels were assessed via Western blotting, NNMT, NAMPT, DNMT. Lastly, alveolar formation in a hyperoxia murine model of prematurity (HMMP) with dietary supplement of methionine vs control was assessed, MLI, H&E, and vessel formation (endomucin).Results: Methionine and nicotinamide increased ECFC proliferation (p<0.05) and OCM enzymes. Nicotinamide increased ECFC angiogenesis (p<0.05). ECFC migration was not impacted by methionine or nicotinamide supplementation (p NS). Methionine dietary supplementation in a HMMP model improved distal alveolar formation.Conclusion and Clinical Implications: Lung maturation is dependent on shifting metabolic needs during development. Replenishment of disrupted key OCM metabolites in HMMP promotes vessel and alveolar formation. Future studies are necessary to explore the role of precision nutritive supplementation in alveolar development of premature infants.

Evaluating the (F)utility of Mandatory Minimum Sentencing Laws in Pennsylvania

In the current criminal justice policy sphere mandatory minimum sentencing serves two important purposes 1) they are used as a punitive response to immediate crime concerns and 2) their removal is viewed as a tool to conserve resources, decarcerate, and promote fairness in sentencing. Though much research explores how the passage of these laws relates to crime, the literature has not focused on the public safety implications of removing mandatory minimum sentences. Using a comparative interrupted time-series approach, the present work investigates whether a Pennsylvania Supreme Court decision that invalidated several mandatory minimum sentencing provisions impacted the state’s crime rate. We find little to no evidence of a discrete shift in overall or type-disaggregated crime rates, or changes in the slope of any crime trend when the state reduced their use of mandatory minimums. These findings tentatively suggest that many mandatory minimums can be repealed without risking public safety.

RIS-Assisted UAV for Fresh Data Collection in 3D Urban Environments: A Deep Reinforcement Learning Approach

Dispatching flexible unmanned aerial vehicles (UAVs) to collect data from distributed Internet-of-Things devices (IoTDs) is expected to be a promising technology to support time-critical applications. However, in urban environments, the communication links between the UAV and IoTDs are prone to be frequently blocked by buildings, which severely impairs the freshness of information collected by the UAV. Thus, how to overcome urban building blockages and ensure fresh data collection is quite important but neglected in existing works. In this paper, for keeping the information fresh, we propose to utilize the reconfigurable intelligent surface (RIS) to assist the UAV in mitigating signal propagation impairments caused by building blockages. The formulated optimization problem is minimizing the age of information (AoI) of all IoTDs by jointly optimizing the UAV trajectory, IoTD scheduling and discrete phase shifts of the RIS. It is a mixed-integer non-convex problem as well as lacking the complete channel state information (CSI), thus using conventional optimization methods is intractable. To address this issue, we present an effective and robust deep reinforcement learning (DRL)-based scheme called “SAC-AO-RIS,” where a soft actor-critic (SAC) algorithm with recent-prioritized experience replay is designed for learning highly stable policies of UAV trajectory and IoTD scheduling, and an alternating optimization (AO) algorithm is leveraged for solving RIS phase shifts. Finally, simulation results demonstrate the effectiveness and superiority of our proposed scheme compared with other baseline approaches.

Performance Analysis for RIS-Aided Secure Massive MIMO Systems With Statistical CSI

This letter studies a reconfigurable intelligent surface (RIS)-aided secure massive multiple-input multiple-output (MIMO) communication system. We derive the approximate expression of the sum achievable security data rate (ASDR) with statistical channel state information (CSI). To further improve the system performance, a genetic algorithm (GA) is proposed to optimize the RIS’s phase shifts, where both the continuous and discrete phase shifts are considered. Finally, simulation results confirm the correctness of our derived expressions, and demonstrate the effectiveness of using RIS in improving the security performance.