pwc-archive/papers-with-abstracts huggingface dataset:
Joint Channel Estimation and Data Recovery for Millimeter Massive MIMO: Using Pilot to Capture Principal Components
Authors: Shusen Cai, Li Chen, Yunfei Chen, Huarui Yin, Weidong Wang
Date: 2024-01-03 00:00:00

Channel state information (CSI) is important to reap the full benefits of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. The traditional channel estimation methods using pilot frames (PF) lead to excessive overhead. To reduce the demand for PF, data frames (DF) can be adopted for joint channel estimation and data recovery. However, the computational complexity of the DF-based methods is prohibitively high. To reduce the computational complexity, we propose a joint channel estimation and data recovery (JCD) method assisted by a small number of PF for mmWave massive MIMO systems. The proposed method has two stages. In Stage 1, differing from the traditional PF-based methods, the proposed PF-assisted method is utilized to capture the angle of arrival (AoA) of principal components (PC) of channels. In Stage 2, JCD is designed for parallel implementation based on the multi-user decoupling strategy. The theoretical analysis demonstrates that the PF-assisted JCD method can achieve equivalent performance to the Bayesian-optimal DF-based method, while greatly reducing the computational complexity. Simulation results are also presented to validate the analytical results.
An alternative approach for the convolution in time-domain: the taches-algorithms
Authors: Laurent Millot, Gérard Pelé
Date: 2024-01-03 00:00:00

We present an alternative temporal approach for convolution, providing a new algorithm, called the taches-algorithm. Based on interferences between the successive delayed and amplified output signals associated respectively with the impulses constituting the input signal, the taches-algorithm can give access immediately to the new output sample and have a low latency response even without using vector-based optimisation of the calculation. With the taches-algorithm it seems easy to change (even in real-time) the impulse response while running the calculation, simply by updating the impulse response to use it for next samples, a task rather difficult to achieve using FFT convolution. Real-time audio demonstrations using notably Pure Data and simple explanations of the taches-algorithm will be given.Paper 7412 presented at the 125th Convention of the Audio Engineering Society, Amsterdam, 2008
Regression Based Anomaly Detection in Electric Vehicle State of Charge Fluctuations Through Analysis of EVCI Data
Authors: Mitikiri Sagar Babu, Yash Tiwari, Vedantham Lakshmi Srinivas, Mayukha Pal
Date: 2024-01-03 00:00:00
Tasks: Anomaly Detection

With the increase in the number of electric vehicles (EV), there is a need for the development of the EV charging infrastructure (EVCI) to facilitate fast charging, thereby mitigating the EV congestion at charging stations. The role of the public charging station depot is to charge the vehicle, prioritizing the achievement of the desired state of charge (SoC) value for the EV battery or charging till the departure of the EV, whichever occurs first. The integration of cyber and physical components within EVCI defines it as a cyber physical power system (CPPS), increasing its vulnerability to diverse cyber attacks. When an EV interfaces with the EVCI, mutual exchange of data takes place via various communication protocols like the Open Charge Point Protocol (OCPP), and IEC 61850. Unauthorized access to this data by intruders leads to cyber attacks, potentially resulting in consequences like energy theft, and revenue loss. These scenarios may cause the EVCI to incur higher charges than the actual energy consumed or the EV owners to remit payments that do not correspond adequately to the amount of energy they have consumed. This article proposes an EVCI architecture connected to the utility grid and uses the EVCI data to identify the anomalies or outliers present in the EV transmitted data, particularly focusing on SoC irregularities.
On the Mutuality between Localization and Channel Modeling in sub-THz
Authors: Eray Guven, Gunes Karabulut Kurt
Date: 2024-01-03 00:00:00
Tasks: Integrated sensing and communication, ISAC

The use of sub-Terahertz (sub-THz) band is gaining considerable attention in 6G networks. In this study, we introduce hardware and propagation integrated 3D Propagation Model to describe sub-THz channels and discuss its advantages over both deterministic and stochastic 6G channel models. The unexplored mutuality of localization and communication is presented and its potential in integrated sensing and communication (ISAC) applications is highlighted. Afterward, a real-time sub-THz localization experiment is conducted to show the impact of the mispositioned and misaligned narrow beams on service quality. In continuation, we highlight the most current challenges and developments in THz localization and explore the potential of sub-THz frequencies to efficiently utilize the ultra-wideband spectrum. In the end, the open issues that need to be overcome to provide high spatial resolution and millidegree-level angle of arrival estimation in ISAC applications have been explored.
CRB Minimization for RIS-aided mmWave Integrated Sensing and Communications
Authors: Wanting Lyu, Songjie Yang, Yue Xiu, Ya Li, Hongjun He, Chau Yuen, Zhongpei Zhang
Date: 2024-01-02 00:00:00
Tasks: ISAC

In this paper, reconfigurable intelligent surface (RIS) is employed in a millimeter wave (mmWave) integrated sensing and communications (ISAC) system. To alleviate the multi-hop attenuation, the semi-self sensing RIS approach is adopted, wherein sensors are configured at the RIS to receive the radar echo signal. Focusing on the estimation accuracy, the Cramer-Rao bound (CRB) for estimating the direction-of-the-angles is derived as the metric for sensing performance. A joint optimization problem on hybrid beamforming and RIS phaseshifts is proposed to minimize the CRB, while maintaining satisfactory communication performance evaluated by the achievable data rate. The CRB minimization problem is first transformed as a more tractable form based on Fisher information matrix (FIM). To solve the complex non-convex problem, a double layer loop algorithm is proposed based on penalty concave-convex procedure (penalty-CCCP) and block coordinate descent (BCD) method with two sub-problems. Successive convex approximation (SCA) algorithm and second order cone (SOC) constraints are employed to tackle the non-convexity in the hybrid beamforming optimization. To optimize the unit modulus constrained analog beamforming and phase shifts, manifold optimization (MO) is adopted. Finally, the numerical results verify the effectiveness of the proposed CRB minimization algorithm, and show the performance improvement compared with other baselines. Additionally, the proposed hybrid beamforming algorithm can achieve approximately 96% of the sensing performance exhibited by the full digital approach within only a limited number of radio frequency (RF) chains.
Deceptive Jamming in WLAN Sensing
Authors: Hasan Can Yildirim, Musa Furkan Keskin, Henk Wymeersch, François Horlin
Date: 2024-01-02 00:00:00

Joint Communication and Sensing (JCAS) is taking its first shape in WLAN sensing under IEEE 802.11bf, where standardized WLAN signals and protocols are exploited to enable radar-like sensing. However, an overlooked problem in JCAS, and specifically in WLAN Sensing, is the sensitivity of the system to a deceptive jammer, which introduces phantom targets to mislead the victim radar receiver. Standardized waveforms and sensing parameters make the system vulnerable to physical layer attacks. Moreover, orthogonal frequency-division multiplexing (OFDM) makes deceptive jamming even easier as it allows digitally generated artificial range/Doppler maps. This paper studies deceptive jamming in JCAS, with a special focus on WLAN Sensing. The provided mathematical models give insights into how to design jamming signals and their impact on the sensing system. Numerical analyses illustrate various distortions caused by deceptive jamming, while the experimental results validate the need for meticulous JCAS design to protect the system against physical layer attacks in the form of deceptive jamming.
Using DCFT for Multi-Target Detection in Distributed Radar Systems with Several Transmitters
Authors: Gokularam Muthukrishnan, S. Sruti, K. Giridhar
Date: 2024-01-01 00:00:00

In distributed radar systems, when several transmitters radiate simultaneously, the reflected signals need to be distinguished at the receivers to detect various targets. If the transmit signals are in different frequency bands, they require a large overall bandwidth. Instead, a set of pseudo-orthogonal waveforms derived from the Zadoff-Chu (ZC) sequences could be accommodated in the same band, enabling the efficient use of available bandwidth for better range resolution. In such a design, special care must be given to the 'near-far' problem, where a reflection could possibly become difficult to detect due to the presence of stronger reflections. In this work, a scheme to detect multiple targets in such distributed radar systems is proposed. It performs successive cancellations (SC) starting from the strong, detectable reflections in the domain of the Discrete Chirp-Fourier Transform (DCFT) after compensating for Doppler shifts, enabling the subsequent detections of weaker targets which are not trivially detectable. Numerical simulations corroborate the efficacy and usefulness of the proposed method in detecting weak target reflections.
Ruhr Hand Motion Catalog of Human Center-Out Transport Trajectories in 3D Task-Space Captured by a Redundant Measurement System
Authors: Tim Sziburis, Susanne Blex, Tobias Glasmachers, Ioannis Iossifidis
Date: 2023-12-31 00:00:00

Neurological conditions are a major source of movement disorders. Motion modelling and variability analysis have the potential to identify pathology but require profound data. We introduce a systematic dataset of 3D center-out task-space trajectories of human hand transport movements in a natural setting. The transport tasks of this study consist of grasping a cylindric object from a unified start position and transporting it to one of nine target locations in unconstrained operational space. The measurement procedure is automatized to record ten trials per target location. With that, the dataset consists of 90 movement trajectories for each hand of 31 participants without known movement disorders. The participants are aged between 21 and 78 years, covering a wide range. Data are recorded redundantly by both an optical tracking system and an IMU sensor. As opposed to the stationary capturing system, the IMU can be considered as a portable, low-cost and energy-efficient alternative to be implemented on embedded systems.
Exploring the Synergy: A Review of Dual-Functional Radar Communication Systems
Authors: Ali Hanif, Sajid Ahmed, Tareq Y. Al-Naffouri, Mohamed-Slim Alouin
Date: 2023-12-31 00:00:00

This review paper examines the concept and advancements in the evolving landscape of Dual-functional Radar Communication (DFRC) systems. Traditionally, radar and communication systems have functioned independently, but current research is actively investigating the integration of these functionalities into a unified platform. This paper discusses the motivations behind the development of DFRC systems, the challenges involved, and the potential benefits they offer. A discussion on the performance bounds for DFRC systems is also presented. The paper encompasses a comprehensive analysis of various techniques, architectures, and technologies used in the design and optimization of DFRC systems, along with their performance and trade-offs. Additionally, we explore potential application scenarios for these joint communication and sensing systems, offering a comprehensive perspective on the multifaceted landscape of DFRC technology.
RIS-Enabled Integrated Sensing and Communication for 6G Systems
Authors: Dexin Wang, Ahmad Bazzi, Marwa Chafii
Date: 2023-12-31 00:00:00
Tasks: Integrated sensing and communication

The following paper proposes a new target localization system design using an architecture based on reconfigurable intelligent surfaces (RISs) and passive radars (PRs) for integrated sensing and communications systems. The preamble of the communication signal is exploited in order to perform target sensing tasks, which involve detection and localization. The RIS in this case can aid the PR in sensing targets that are otherwise not seen by the PR itself, due to the many obstacles encountered within the propagation channel. Therefore, this work proposes a localization algorithm tailored for the integrated sensing and communications RIS-aided architecture, which is capable of uniquely positioning targets within the scene. The algorithm is capable of detecting the number of targets along with estimating the position of targets via angles and times of arrival. Our simulation results demonstrate the performance of the localization method in terms of different localization and detection metrics and for increasing RIS sizes.
Internet of Harvester Nano Things: A Future Prospects
Authors: Bitop Maitra, Emine Bardakci, Oktay Cetinkaya, Ozgur B. Akan
Date: 2023-12-30 00:00:00
Tasks: Electrical Engineering

The advancements in nanotechnology, material science, and electrical engineering have shrunk the sizes of electronic devices down to the micro/nanoscale. This brings the opportunity of developing the Internet of Nano Things (IoNT), an extension of the Internet of Things (IoT). With nanodevices, numerous new possibilities emerge in the biomedical, military fields, and industrial products. However, a continuous energy supply is mandatory for these devices to work. At the micro/nanoscale, batteries cannot supply this demand due to size limitations and the limited energy contained in the batteries. Internet of Harvester Nano Things (IoHNT), a concept of Energy Harvesting (EH) integrated with wireless power transmission (WPT) techniques, converts the existing different energy sources into electrical energy and transmits to IoNT nodes. As IoHNTs are not directly attached to IoNTs, it gives flexibility in size. However, we define the size of IoHNTs as up to 10 cm. In this review, we comprehensively investigate the available energy sources and EH principles to wirelessly power IoNTs. We discuss the IoHNT principles, material selections, and state-of-the-art applications of each energy source for different sectoral applications. The different technologies of WPT and how communication is influenced by the incorporation of IoHNTs to power IoNTs are discussed with the future research directions. IoHNTs represent a shift in the nanodevice power supply, leading us towards a future where wireless technology is widespread. Hence, it will motivate researchers to envision and contribute to advancing the following power revolution in IoNT, providing unmatched simplicity and efficiency.
Acceleration Estimation of Signal Propagation Path Length Changes for Wireless Sensing
Authors: Jiacheng Wang, Hongyang Du, Dusit Niyato, Mu Zhou, Jiawen Kang, H. Vincent Poor
Date: 2023-12-30 00:00:00
Tasks: Activity Recognition, parameter estimation

As indoor applications grow in diversity, wireless sensing, vital in areas like localization and activity recognition, is attracting renewed interest. Indoor wireless sensing relies on signal processing, particularly channel state information (CSI) based signal parameter estimation. Nonetheless, regarding reflected signals induced by dynamic human targets, no satisfactory algorithm yet exists for estimating the acceleration of dynamic path length change (DPLC), which is crucial for various sensing tasks in this context. Hence, this paper proposes DP-AcE, a CSI-based DPLC acceleration estimation algorithm. We first model the relationship between the phase difference of adjacent CSI measurements and the DPLC's acceleration. Unlike existing works assuming constant velocity, DP-AcE considers both velocity and acceleration, yielding a more accurate and objective representation. Using this relationship, an algorithm combining scaling with Fourier transform is proposed to realize acceleration estimation. We evaluate DP-AcE via the acceleration estimation and acceleration-based fall detection with the collected CSI. Experimental results reveal that, using distance as the metric, DP-AcE achieves a median acceleration estimation percentage error of 4.38%. Furthermore, in multi-target scenarios, the fall detection achieves an average true positive rate of 89.56% and a false positive rate of 11.78%, demonstrating its importance in enhancing indoor wireless sensing capabilities.
Lossless digraph signal processing via polar decomposition
Authors: Feng Ji
Date: 2023-12-30 00:00:00

In this paper, we present a signal processing framework for directed graphs. Unlike undirected graphs, a graph shift operator such as the adjacency matrix associated with a directed graph usually does not admit an orthogonal eigenbasis. This makes it challenging to define the Fourier transform. Our methodology leverages the polar decomposition to define two distinct eigendecompositions, each associated with different matrices derived from this decomposition. We propose to extend the frequency domain and introduce a Fourier transform that jointly encodes the spectral response of a signal for the two eigenbases from the polar decomposition. This allows us to define convolution following a standard routine. Our approach has two features: it is lossless as the shift operator can be fully recovered from factors of the polar decomposition. Moreover, it subsumes the traditional graph signal processing if the graph is directed. We present numerical results to show how the framework can be applied.
Generative AI-driven Semantic Communication Networks: Architecture, Technologies and Applications
Authors: Chengsi Liang, Hongyang Du, Yao Sun, Dusit Niyato, Jiawen Kang, Dezong Zhao, Muhammad Ali Imran
Date: 2023-12-30 00:00:00
Tasks: Autonomous Driving, Knowledge Base Construction, Management, Semantic Communication

Generative artificial intelligence (GAI) has emerged as a rapidly burgeoning field demonstrating significant potential in creating diverse contents intelligently and automatically. To support such artificial intelligence-generated content (AIGC) services, future communication systems should fulfill much more stringent requirements (including data rate, throughput, latency, etc.) with limited yet precious spectrum resources. To tackle this challenge, semantic communication (SemCom), dramatically reducing resource consumption via extracting and transmitting semantics, has been deemed as a revolutionary communication scheme. The advanced GAI algorithms facilitate SemCom on sophisticated intelligence for model training, knowledge base construction and channel adaption. Furthermore, GAI algorithms also play an important role in the management of SemCom networks. In this survey, we first overview the basics of GAI and SemCom as well as the synergies of the two technologies. Especially, the GAI-driven SemCom framework is presented, where many GAI models for information creation, SemCom-enabled information transmission and information effectiveness for AIGC are discussed separately. We then delve into the GAI-driven SemCom network management involving with novel management layers, knowledge management, and resource allocation. Finally, we envision several promising use cases, i.e., autonomous driving, smart city, and the Metaverse for a more comprehensive exploration.
Joint User Scheduling, Power Allocation, and Rate Control for MC-RSMA in URLLC Services
Authors: Xiaoyu Ou, Shuping Dang, Zhihan Ren, Angela Doufexi
Date: 2023-12-29 00:00:00
Tasks: Management, Scheduling

This paper investigates the resource management problem in multi-carrier rate-splitting multiple access (MC-RSMA) systems with imperfect channel state information (CSI) and successive interference cancellation (SIC) for ultra-reliable and low-latency communications (URLLC) applications. To explore the trade-off between the decoding error probability and achievable rate, effective throughput (ET) is adopted as the utility function in this study. Then, a mixed-integer non-convex problem is formulated, where power allocation, rate control, and user grouping are jointly taken into consideration. To tackle this problem, we approximate the achievable ET using a lower bound and then develop a decomposition method to decouple optimization variables. Specifically, for a given user grouping scheme, an iteration-based concave-convex programming (CCCP) method and an iteration-free lower-bound approximation (LBA) method are proposed for power allocation and rate control. Next, a greedy search-based scheme and a heuristic grouping scheme are developed for the user-grouping problem. The simulation results verify the effectiveness of the CCCP and LBA methods in power allocation and rate control and the greedy search-based and heuristic grouping methods in user grouping. Besides, the superiority of RSMA for URLLC services is demonstrated when compared to spatial division multiple access.
Integer-Based Pattern Synthesis for Asymmetric Multi-Reflection RIS
Authors: Wei Wang, Angela Doufexi, Mark A Beach
Date: 2023-12-28 00:00:00

This study delves into the radiation pattern synthesis of reconfigurable intelligent surfaces (RIS) / reflection metasurfaces. Through superimposing multiple single-reflection profiles, which comprise the amplitude and/or phase settings of all constituent elements, a single incident wave can be effectively reflected in multiple asymmetric directions. However, some mismatch and interference between adjacent reflection beams may be caused by this superposition as well. Additionally, it is constrained by the inherent limitation that achieving linear and continuous amplitude adjustments and phase shifts in real-world designs is challenging. Consequently, the reconfigurable amplitude and phase must be approximated to discrete values, necessitating the arrangement of reflection profile before and after optimization based on integer. Therefore, in this paper, we adapt the traditional particle swarm optimization (PSO) algorithm to discretized integer-based PSO by proposing the concepts of 'discard rate' and 'knowledge.' With the enhancement of the integer-based programming, the multiple asymmetric reflection pattern can be synthesized with suppressed sidelobe levels within limited iterations and time cost.
Controlling the occurrence sequence of reaction modules through biochemical relaxation oscillators
Authors: Xiaopeng Shi, Chuanhou Gao, Denis Dochain
Date: 2024-01-04 00:00:00

Embedding sequential computations in biochemical environments is challenging because the computations are carried out by chemical reactions, which are inherently disordered. In this paper we apply modular design to specific calculations through chemical reactions and provide a design scheme of biochemical oscillator models in order to generate periodical species for the order regulation of these reaction modules. We take the case of arbitrary multi-module regulation into consideration, analyze the main errors in the regulation process under \textit{mass-action kinetics} and demonstrate our design scheme under existing synthetic biochemical oscillator models.
Almost Perfect Shadow Prices
Authors: Eberhard Mayerhofer
Date: 2024-01-01 00:00:00

Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a na\"ive shadow price Ansatz for maximizing long term returns given average volatility yields a strategy that is, for small bid-ask-spreads, asymptotically optimal at third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices.