pwc-archive/papers-with-abstracts huggingface dataset:
Real-Valued 2-D Direction of Arrival Estimation via Sparse Representation
Authors: Zavareh Bozorgasl, Mohammad Javad Dehghani
Date: 2024-04-09 00:00:00
Tasks: Direction of Arrival Estimation

Despite many advantages of direction-of-arrivals (DOAs) in sparse representation domain, they have high computational complexity. This paper presents a new method for real-valued 2-D DOAs estimation of sources in a uniform circular array configuration. This method uses a transformation based on phase mode excitation in uniform circular arrays which called real beamspace L1-SVD (RB-L1SVD). This unitary transformation converts complex manifold matrix to real one, so that the computational complexity is decreased with respect to complex valued computations,its computation, at least, is one,fourth of the complex-valued case; moreover, some benefits from using this transformation are robustness to array imperfections, a better noise suppression because of exploiting an additional real structure, and etc. Numerical results demonstrate the better performance of the proposed approach over previous techniques such as C-L1SVD, RB-ESPRIT, and RB-MUSIC, especially in low signal-to-noise ratios.
Near/Far-Field Channel Estimation For Terahertz Systems With ELAAs: A Block-Sparse-Aware Approach
Authors: Hongwei Wang, Jun Fang, Huiping Duan, Hongbin Li
Date: 2024-04-08 00:00:00
Tasks: valid

Millimeter wave/Terahertz (mmWave/THz) communication with extremely large-scale antenna arrays (ELAAs) offers a promising solution to meet the escalating demand for high data rates in next-generation communications. A large array aperture, along with the ever increasing carrier frequency within the mmWave/THz bands, leads to a large Rayleigh distance. As a result, the traditional plane-wave assumption may not hold valid for mmWave/THz systems featuring ELAAs. In this paper, we consider the problem of hybrid near/far-field channel estimation by taking spherical wave propagation into account. By analyzing the coherence properties of any two near-field steering vectors, we prove that the hybrid near/far-field channel admits a block-sparse representation on a specially designed orthogonal dictionary. Specifically, the percentage of nonzero elements of such a block-sparse representation decreases in the order of $1/\sqrt{N}$, which tends to zero as the number of antennas, $N$, grows. Such a block-sparse representation allows to convert channel estimation into a block-sparse signal recovery problem. Simulation results are provided to verify our theoretical results and illustrate the performance of the proposed channel estimation approach in comparison with existing state-of-the-art methods.
Observations on Large-Scale Attenuation Effects in a 26 GHz Urban Micro-Cell Environment
Authors: Alejandro Ramírez-Arroyo, Troels B. Sørensen, Peter Beltoft, Henrik Christiansen, Juan F. Valenzuela-Valdés, Preben Mogensen
Date: 2024-04-08 00:00:00

This letter presents a measurement campaign carried out in an FR2 urban outdoor environment in a live experimental network deployment. The radio propagation analysis from a physical perspective at 26 GHz is essential for the correct deployment and dimensioning of future communication networks. This study performs a walk test emulating realistic conditions under which a pedestrian may be affected, summarizing and evaluating some of the typical effects encountered in a communications scenario such as penetration losses in a building, losses due to vegetation or the human body, or diffraction/scattering propagation around corners in street canyon-like environments. The operational conditions of the 5G network, the urban micro-cell scenario, and the use of omnidirectional antennas on the UE side validate the channel conditions from a perspective closer to a realistic scenario for a pedestrian within a FR2 live network.
Seamlessly merging radar ranging/imaging, wireless communications, and spectrum sensing, for 6G empowered by microwave photonics
Authors: Taixia Shi, Yang Chen, Jianping Yao
Date: 2024-04-08 00:00:00

Integration of radar, wireless communications, and spectrum sensing is being investigated for 6G with an increased spectral efficiency. Microwave photonics (MWP), a technique that combines microwave engineering and photonic technology to take advantage of the wide bandwidth offered by photonics for microwave signal generation and processing is considered an effective solution for the implementation of the integration. In this paper, an MWP-assisted joint radar, wireless communications, and spectrum sensing (JRCSS) system that enables precise perception of the surrounding physical and electromagnetic environments while maintaining high-speed data communication is proposed and demonstrated. Communication signals and frequency-sweep signals are merged in the optical domain to achieve high-speed radar ranging and imaging, high-data-rate wireless communications, and wideband spectrum sensing. In an experimental demonstration, a JRCSS system supporting radar ranging with a measurement error within $\pm$ 4 cm, two-dimensional imaging with a resolution of 25 $\times$ 24.7 mm, wireless communications with a data rate of 2 Gbaud, and spectrum sensing with a frequency measurement error within $\pm$ 10 MHz in a 6-GHz bandwidth, is demonstrated.
Phase Noise Detection via Expectation Propagation and Related Algorithms
Authors: Elisa Conti, Armando Vannucci, Amina Piemontese, Giulio Colavolpe
Date: 2024-04-08 00:00:00

In the context of signal detection in the presence of an unknown time-varying channel parameter, receivers based on the Expectation Propagation (EP) framework appear to be very promising. EP is a message-passing algorithm based on factor graphs with an inherent ability to combine prior knowledge of system variables with channel observations. This suggests that an effective estimation of random channel parameters can be achieved even with a very limited number of pilot symbols, thus increasing the payload efficiency. However, achieving satisfactory performance often requires ad-hoc adjustments in the way the probability distributions of latent variables - both data and channel parameters - are combined and projected. Here, we apply EP to a classical problem of coded transmission on a strong Wiener phase noise channel, employing soft-input soft-output decoding. We identify its limitations and propose new strategies which reach the performance benchmark while maintaining low complexity, with a primary focus on challenging scenarios where the state-of-the-art algorithms fail.
Sensing-Resistance-Oriented Beamforming for Privacy Protection from ISAC Devices
Authors: Teng Ma, Yue Xiao, Xia Lei, Ming Xiao
Date: 2024-04-08 00:00:00
Tasks: Integrated sensing and communication, ISAC, Privacy Preserving

With the evolution of integrated sensing and communication (ISAC) technology, a growing number of devices go beyond conventional communication functions with sensing abilities. Therefore, future networks are divinable to encounter new privacy concerns on sensing, such as the exposure of position information to unintended receivers. In contrast to traditional privacy preserving schemes aiming to prevent eavesdropping, this contribution conceives a novel beamforming design toward sensing resistance (SR). Specifically, we expect to guarantee the communication quality while masking the real direction of the SR transmitter during the communication. To evaluate the SR performance, a metric termed angular-domain peak-to-average ratio (ADPAR) is first defined and analyzed. Then, we resort to the null-space technique to conceal the real direction, hence to convert the optimization problem to a more tractable form. Moreover, semidefinite relaxation along with index optimization is further utilized to obtain the optimal beamformer. Finally, simulation results demonstrate the feasibility of the proposed SR-oriented beamforming design toward privacy protection from ISAC receivers.
Graph-based Untrained Neural Network Detector for OTFS Systems
Authors: Hao Chang, Branka Vucetic, Wibowo Hardjawana
Date: 2024-04-08 00:00:00
Tasks: Decoder

Inter-carrier interference (ICI) caused by mobile reflectors significantly degrades the conventional orthogonal frequency division multiplexing (OFDM) performance in high-mobility environments. The orthogonal time frequency space (OTFS) modulation system effectively represents ICI in the delay-Doppler domain, thus significantly outperforming OFDM. Existing iterative and neural network (NN) based OTFS detectors suffer from high complex matrix operations and performance degradation in untrained environments, where the real wireless channel does not match the one used in the training, which often happens in real wireless networks. In this paper, we propose to embed the prior knowledge of interference extracted from the estimated channel state information (CSI) as a directed graph into a decoder untrained neural network (DUNN), namely graph-based DUNN (GDUNN). We then combine it with Bayesian parallel interference cancellation (BPIC) for OTFS symbol detection, resulting in GDUNN-BPIC. Simulation results show that the proposed GDUNN-BPIC outperforms state-of-the-art OTFS detectors under imperfect CSI.
A 0.65-pJ/bit 3.6-TB/s/mm I/O Interface with XTalk Minimizing Affine Signaling for Next-Generation HBM with High Interconnect Density
Authors: Hyunjun Park, Jiwon Shin, Hanseok Kim, Jihee Kim, Haengbeom Shin, TaeHoon Kim, Jung-Hun Park, Woo-Seok Choi
Date: 2024-04-08 00:00:00

This paper presents an I/O interface with Xtalk Minimizing Affine Signaling (XMAS), which is designed to support high-speed data transmission in die-to-die communication over silicon interposers or similar high-density interconnects susceptible to crosstalk. The operating principles of XMAS are elucidated through rigorous analyses, and its advantages over existing signaling are validated through numerical experiments. XMAS not only demonstrates exceptional crosstalk removing capabilities but also exhibits robustness against noise, especially simultaneous switching noise. Fabricated in a 28-nm CMOS process, the prototype XMAS transceiver achieves an edge density of 3.6TB/s/mm and an energy efficiency of 0.65pJ/b. Compared to the single-ended signaling, the crosstalk-induced peak-to-peak jitter of the received eye with XMAS is reduced by 75% at 10GS/s/pin data rate, and the horizontal eye opening extends to 0.2UI at a bit error rate < 10$^{-12}$.
The Use of MEMS Accelerometers for Remote Activity and Living Parameters Monitoring
Authors: Natalia Osiadala, Marcin Kolakowski
Date: 2024-04-07 00:00:00

In the paper a ballistocardiographic sensor for remote monitoring of activity and vital parameters is presented. The sensor is mainly intended for use in monitoring systems supporting care of older people. It allows to detect occupancy of a piece of furniture, to which it is attached and to estimate basic vital parameters (heart and respiration rates) of the monitored person. The presented device includes three inertial sensors: two accelerometers of different parameters and prices and one reference BCG module. The device sends the measurement results to the external server over WiFi. The vital parameters are estimated based on the Continuous Wavelet Transform of the registered acceleration signals. User's presence is detected by tracking changes in acceleration measured in axes parallel to the ground.
Wi-Fi-based Personnel Identity Recognition: Addressing Dataset Imbalance with C-DDPMs
Authors: Jichen Bian, Chong Tan, Peiyao Tang, Min Zheng
Date: 2024-04-07 00:00:00
Tasks: Denoising

Wireless sensing technologies become increasingly prevalent due to the ubiquitous nature of wireless signals and their inherent privacy-friendly characteristics. Device-free personnel identity recognition, a prevalent application in wireless sensing, is susceptibly challenged by imbalanced channel state information (CSI) datasets. This letter proposes a novel method for CSI dataset augmentation that employs Conditional Denoising Diffusion Probabilistic Models (C-DDPMs) to generate additional samples that address class imbalance issues. The augmentation markedly improves classification accuracies on our homemade dataset, elevating all classes to above 94%.
Pushing the Limit of Range Resolution Beyond Bandwidth Constraint with Triangle FMCW
Authors: Yanbo Zhang
Date: 2024-04-06 00:00:00

This paper proposes a novel signal processing technique that doubles the range resolution of FMCW~(Frequency Modulated Continuous Wave) sensing without increasing the required bandwidth. The proposed design overcomes the resolution limit imposed by bandwidth by exploiting the phase consistency observed in the special frequency variation of the beat signal derived from triangle FMCW. Through this approach, the resolution is doubled while maintaining high spectrum SNR. A system model for signal processing is presented, and the energy distribution of the derived beat spectrum is analyzed. The effectiveness of the proposed technique is validated through model-based simulations.
Data-Driven Online Resource Allocation for User Experience Improvement in Mobile Edge Clouds
Authors: Liqun Fu, Jingwen Tong, Tongtong Lin, Jun Zhang
Date: 2024-04-06 00:00:00

As the cloud is pushed to the edge of the network, resource allocation for user experience improvement in mobile edge clouds (MEC) is increasingly important and faces multiple challenges. This paper studies quality of experience (QoE)-oriented resource allocation in MEC while considering user diversity, limited resources, and the complex relationship between allocated resources and user experience. We introduce a closed-loop online resource allocation (CORA) framework to tackle this problem. It learns the objective function of resource allocation from the historical dataset and updates the learned model using the online testing results. Due to the learned objective model is typically non-convex and challenging to solve in real-time, we leverage the Lyapunov optimization to decouple the long-term average constraint and apply the prime-dual method to solve this decoupled resource allocation problem. Thereafter, we put forth a data-driven optimal online queue resource allocation (OOQRA) algorithm and a data-driven robust OQRA (ROQRA) algorithm for homogenous and heterogeneous user cases, respectively. Moreover, we provide a rigorous convergence analysis for the OOQRA algorithm. We conduct extensive experiments to evaluate the proposed algorithms using the synthesis and YouTube datasets. Numerical results validate the theoretical analysis and demonstrate that the user complaint rate is reduced by up to 100% and 18% in the synthesis and YouTube datasets, respectively.
A Novel Terabit Grid-of-Beam Optical Wireless Multi-User Access Network with Beam Clustering
Authors: Hossein Kazemi, Elham Sarbazi, Michael Crisp, Taisir E. H. El-Gorashi, Jaafar M. H. Elmirghani, Richard V. Penty, Ian H. White, Majid Safari, Harald Haas
Date: 2024-04-05 00:00:00
Tasks: Clustering, Fairness

In this paper, we put forward a proof of concept for sixth generation (6G) Terabit infrared (IR) laser-based indoor optical wireless networks. We propose a novel double-tier access point (AP) architecture based on an array of arrays of vertical cavity surface emitting lasers (VCSELs) to provide a seamless grid-of-beam coverage with multi-Gb/s per beam. We present systematic design and thorough analytical modeling of the AP architecture, which are then applied to downlink system modeling using non-imaging angle diversity receivers (ADRs). We propose static beam clustering with coordinated multi-beam joint transmission (CoMB-JT) for network interference management and devise various clustering strategies to address inter-beam interference (IBI) and inter-cluster interference (ICI). Non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) schemes are also adopted to handle intra-cluster interference, and the resulting signal-to-interference-plus-noise ratio (SINR) and achievable data rate are derived. The network performance is studied in terms of spatial distributions and statistics of the downlink SINR and data rate through extensive computer simulations. The results demonstrate that data rates up to 15 Gb/s are achieved within the coverage area and a properly devised clustering strikes a balance between the sum rate and fairness depending on the number of users.
Logic-dependent emergence of multistability, hysteresis, and biphasic dynamics in a minimal positive feedback network with an autoloop
Authors: Akriti Srivastava, Mubasher Rashid
Date: 2024-04-08 00:00:00

Cellular decision-making (CDM) is a dynamic phenomenon often controlled by regulatory networks defining interactions between genes and transcription factor proteins. Traditional studies have focussed on molecular switches such as positive feedback circuits that exhibit at most bistability. However, higher-order dynamics such as tristability is also prominent in many biological processes. It is thus imperative to identify a minimal circuit that can alone explain mono, bi, and tristable dynamics. In this work, we consider a two-component positive feedback network with an autoloop and explore these regimes of stability for different degrees of multimerization and the choice of Boolean logic functions. We report that this network can exhibit numerous dynamical scenarios such as bi-and tristability, hysteresis, and biphasic kinetics, explaining the possibilities of abrupt cell state transitions and the smooth state swap without a step-like switch. Specifically, while with monomeric regulation and competitive OR logic, the circuit exhibits mono-and bistability and biphasic dynamics, with non-competitive AND and OR logics only monostability can be achieved. To obtain bistability in the latter cases, we show that the autoloop must have (at least) dimeric regulation. In pursuit of higher-order stability, we show that tristability occurs with higher degrees of multimerization and with non-competitive OR logic only. Our results, backed by rigorous analytical calculations and numerical examples, thus explain the association between multistability, multimerization, and logic in this minimal circuit. Since this circuit underlies various biological processes, including epithelial-mesenchymal transition which often drives carcinoma metastasis, these results can thus offer crucial inputs to control cell state transition by manipulating multimerization and the logic of regulation in cells.
In silico bioactivity prediction of proteins interacting with graphene-based nanomaterials guides rational design of biosensor
Authors: Jing Ye, Minzhi Fan, XiaoYu Zhang, Shasha Lu, Mengyao Chai, Yunshan Zhang, Xiaoyu Zhao, Shuang Li, Diming Zhang
Date: 2024-04-08 00:00:00
Tasks: Molecular Docking

Graphene based nanomaterials have attracted significant attention for their potentials in biomedical and biotechnology applications in recent years, owing to the outstanding physical and chemical properties. However, the interaction mechanism and impact on biological activity of macro and micro biomolecules still require more concerns and further research in order to enhance their applicability in biosensors, etc. Herein, an integrated method has been developed to predict the protein bioactivity performance when interacting with nanomaterials for protein based biosensor. Molecular dynamics simulation and molecular docking technique were consolidated to investigate several nanomaterials C60 fullerene, single walled carbon nanotube, pristine graphene and graphene oxide, and their effect when interacting with protein. The adsorption behavior, secondary structure changes and protein bioactivity changes were simulated, and the results of protein activity simulation were verified in combination with atomic force spectrum, circular dichroism spectrum fluorescence and electrochemical experiments. The best quantification alignment between bioactivity obtained by simulation and experiment measurements was further explored. The two proteins, RNase A and Exonuclease III, were regarded as analysis model for the proof of concept, and the prediction accuracy of protein bioactivty could reach up to 0.98.
Characterizing visual cortical magnification with topological smoothing and optimal transportation
Authors: Yujian Xiong, Yanshuai Tu, Zhong-Lin Lu, Yalin Wang
Date: 2024-04-09 00:00:00

Human vision has different concentration on visual fields. Cortical magnification factor (CMF) is a popular measurement on visual acuity and cortex concentration. In order to achieve thorough measurement of CMF across the whole visual field, we propose a method to measure planar CMF upon retinotopic maps generated by pRF decoding, with help of our proposed methods: optimal transportation and topological smoothing. The optimal transportation re-calculates vertex location in retinotopic mapping, and topological smoothing guarantees topological conditions in retinotopic maps, which allow us to calculate planar CMF with the proposed 1-ring patch method. The pipeline was applied to the HCP 7T dataset, giving new planar results on CMF measurement across all 181 subjects, which illustrate novel concentration behavior on visual fields and their individual difference.
Do the receptive fields in the primary visual cortex span a variability over the degree of elongation of the receptive fields?
Authors: Tony Lindeberg
Date: 2024-04-07 00:00:00

This paper presents results of combining (i) theoretical analysis regarding connections between the orientation selectivity and the elongation of receptive fields for the affine Gaussian derivative model with (ii) biological measurements of orientation selectivity in the primary visual cortex, to investigate if (iii) the receptive fields can be regarded as spanning a variability in the degree of elongation. From an in-depth theoretical analysis of idealized models for the receptive fields of simple and complex cells in the primary visual cortex, we have established that the directional selectivity becomes more narrow with increasing elongation of the receptive fields. By comparison with previously established biological results, concerning broad vs. sharp orientation tuning of visual neurons in the primary visual cortex, we demonstrate that those underlying theoretical predictions, in combination with these biological results, are consistent with a previously formulated biological hypothesis, stating that the biological receptive field shapes should span the degrees of freedom in affine image transformations, to support affine covariance over the population of receptive fields in the primary visual cortex. Based on this possible indirect support for the working hypothesis concerning affine covariance, we formulate a set of testable predictions that could be used to, with neurophysiological experiments, judge if the receptive fields in the primary visual cortex of higher mammals could be regarded as spanning a variability over the eccentricity or the elongation of the receptive fields, and, if so, then also characterize if such a variability would, in a structured way, be related to the pinwheel structure in the visual cortex.