pwc-archive/papers-with-abstracts huggingface dataset:
Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data
Authors: Huidong Xie, Weijie Gan, Reimund Bayerlein, Bo Zhou, Ming-Kai Chen, Michal Kulon, Annemarie Boustani, Kuan-Yin Ko, Der-Shiun Wang, Benjamin A. Spencer, Wei Ji, Xiongchao Chen, Qiong Liu, Xueqi Guo, Menghua Xia, Yinchi Zhou, Hui Liu, Liang Guo, Hongyu An, Ulugbek S. Kamilov, Hanzhong Wang, Biao Li, Axel Rominger, Kuangyu Shi, Ge Wang, Ramsey D. Badawi, Chi Liu
Date: 2024-05-02 00:00:00
Tasks: Denoising, Image Denoising, Lesion Segmentation

Reducing scan times, radiation dose, and enhancing image quality for lower-performance scanners, are critical in low-dose PET imaging. Deep learning techniques have been investigated for PET image denoising. However, existing models have often resulted in compromised image quality when achieving low-count/low-dose PET and have limited generalizability to different image noise-levels, acquisition protocols, and patient populations. Recently, diffusion models have emerged as the new state-of-the-art generative model to generate high-quality samples and have demonstrated strong potential for medical imaging tasks. However, for low-dose PET imaging, existing diffusion models failed to generate consistent 3D reconstructions, unable to generalize across varying noise-levels, often produced visually-appealing but distorted image details, and produced images with biased tracer uptake. Here, we develop DDPET-3D, a dose-aware diffusion model for 3D low-dose PET imaging to address these challenges. Collected from 4 medical centers globally with different scanners and clinical protocols, we evaluated the proposed model using a total of 9,783 18F-FDG studies with low-dose levels ranging from 1% to 50%. With a cross-center, cross-scanner validation, the proposed DDPET-3D demonstrated its potential to generalize to different low-dose levels, different scanners, and different clinical protocols. As confirmed with reader studies performed by board-certified nuclear medicine physicians, experienced readers judged the images to be similar or superior to the full-dose images and previous DL baselines based on qualitative visual impression. Lesion-level quantitative accuracy was evaluated using a Monte Carlo simulation study and a lesion segmentation network. The presented results show the potential to achieve low-dose PET while maintaining image quality. Real low-dose scans was also included for evaluation.
UAV-Enabled Wireless Networks with Movable-Antenna Array: Flexible Beamforming and Trajectory Design
Authors: Wenchao Liu, Xuhui Zhang, Huijun Xing, Jinke Ren, Yanyan Shen, Shuguang Cui
Date: 2024-05-31 00:00:00
Tasks: Position

Recently, movable antenna (MA) array becomes a promising technology for improving the communication quality in wireless communication systems. In this letter, an unmanned aerial vehicle (UAV) enabled multi-user multi-input-single-output system enhanced by the MA array is investigated. To enhance the throughput capacity, we aim to maximize the achievable data rate by jointly optimizing the transmit beamforming, the UAV trajectory, and the positions of the MA array antennas. The formulated data rate maximization problem is a highly coupled non-convex problem, for which an alternating optimization based algorithm is proposed to get a sub-optimal solution. Numerical results have demonstrated the performance gain of the proposed method compared with conventional method with fixed-position antenna array.
IoT on the Road to Sustainability: Vehicle or Bandit?
Authors: Jona Cappelle, Liesbet Van der Perre, Emma Fitzgerald, Simon Ravyts, Weronika Gajda, Valentijn De Smedt, Bert Cox, Gilles Callebaut
Date: 2024-05-31 00:00:00

The Internet of Things (IoT) can support the evolution towards a digital and green future. However, the introduction of the technology clearly has in itself a direct adverse ecological impact. This paper assesses this impact at both the IoT-node and at the network side. For the nodes, we show that the electronics production of devices comes with a carbon footprint that can be much higher than during operation phase. We highlight that the inclusion of IoT support in existing cellular networks comes with a significant ecological penalty, raising overall energy consumption by more than 15%. These results call for novel design approaches for the nodes and for early consideration of the support for IoT in future networks. Raising the 'Vehicle or bandit?' question on the nature of IoT in the broader sense of sustainability, we illustrate the need for multidisciplinary cooperation to steer applications in desirable directions.
Large-scale Outdoor Cell-free mMIMO Channel Measurement in an Urban Scenario at 3.5 GHz
Authors: Yuning Zhang, Thomas Choi, Zihang Cheng, Issei Kanno, Masaaki Ito, Jorge Gomez-Ponce, Hussein Hammoud, BoWei Wu, Ashwani Pradhan, Kelvin Arana, Pramod Krishna, Tianyi Yang, Tyler Chen, Ishita Vasishtha, Haoyu Xie, Linyu Sun, Andreas F. Molisch
Date: 2024-05-31 00:00:00

The design of cell-free massive MIMO (CF-mMIMO) systems requires accurate, measurement-based channel models. This paper provides the first results from the by far most extensive outdoor measurement campaign for CF-mMIMO channels in an urban environment. We measured impulse responses between over 20,000 potential access point (AP) locations and 80 user equipments (UEs) at 3.5 GHz with 350 MHz bandwidth (BW). Measurements use a "virtual array" approach at the AP and a hybrid switched/virtual approach at the UE. This paper describes the sounder design, measurement environment, data processing, and sample results, particularly the evolution of the power-delay profiles (PDPs) as a function of the AP locations, and its relation to the propagation environment.
Multi-Beam Integrated Sensing and Communication: State-of-the-Art, Challenges and Opportunities
Authors: Yinxiao Zhuo, Tianqi Mao, Haojin Li, Chen Sun, Zhaocheng Wang, Zhu Han, Sheng Chen
Date: 2024-05-31 00:00:00
Tasks: Integrated sensing and communication, ISAC, Motion Detection

Integrated sensing and communication (ISAC) has been envisioned as a critical enabling technology for the next-generation wireless communication, which can realize location/motion detection of surroundings with communication devices. This additional sensing capability leads to a substantial network quality gain and expansion of the service scenarios. As the system evolves to millimeter wave (mmWave) and above, ISAC can realize simultaneous communications and sensing of the ultra-high throughput level and radar resolution with compact design, which relies on directional beamforming against the path loss. With the multi-beam technology, the dual functions of ISAC can be seamlessly incorporated at the beamspace level by unleashing the potential of joint beamforming. To this end, this article investigates the key technologies for multi-beam ISAC system. We begin with an overview of the current state-of-the-art solutions in multi-beam ISAC. Subsequently, a detailed analysis of the advantages associated with the multi-beam ISAC is provided. Additionally, the key technologies for transmitter, channel and receiver of the multi-beam ISAC are introduced. Finally, we explore the challenges and opportunities presented by multi-beam ISAC, offering valuable insights into this emerging field.
A Multiband T-Shaped Antenna Array for 6G Mobile Communication
Authors: Sunday Achimugu, Abraham Usman Usman, Suleiman Zubair, Michael David, Abdulkadir Olayinka Abdulbaki, Hassan Musa Abdullahi
Date: 2024-05-30 00:00:00

The paradigm shift in the use cases of wireless communication necessitates the need to move toward higher data rates, large bandwidths, and intelligent reconfiguration in 6G. This paper presents a novel double T-shaped antenna array that operates between 4GHz to 16GHz for 6G mobile communication. The antenna consists of a rectangular microstrip with a fractal Tshaped slot, cut at the rear of the microstrip to provide an air gap for an improved radiation pattern.
Distributed MIMO Precoding with Routing Constraints in Segmented Fronthaul
Authors: Jale Sadreddini, Omer Haliloglu, Andres Reial
Date: 2024-05-30 00:00:00

Distributed Multiple-Input and Multiple-Output (D-MIMO) is envisioned to play a significant role in future wireless communication systems as an effective means to improve coverage and capacity. In this paper, we have studied the impact of a practical two-level data routing scheme on radio performance in a downlink D-MIMO scenario with segmented fronthaul. At the first level, a Distributed Unit (DU) is connected to the Aggregating Radio Units (ARUs) that behave as cluster heads for the selected serving RU groups. At the second level, the selected ARUs connect with the additional serving RUs. At each route discovery level, RUs and/or ARUs share information with each other. The aim of the proposed framework is to efficiently select serving RUs and ARUs so that the practical data routing impact for each User Equipment (UE) connection is minimal. The resulting post-routing Signal-to-Interference plus Noise Ratio (SINR) among all UEs is analyzed after the routing constraints have been applied. The results show that limited fronthaul segment capacity causes connection failures with the serving RUs of individual UEs, especially when long routing path lengths are required. Depending on whether the failures occur at the first or the second routing level, a UE may be dropped or its SINR may be reduced. To minimize the DU-ARU connection failures, the segment capacity of the segments closest to the DU is set as double as the remaining segments. When the number of active co-scheduled UEs is kept low enough, practical segment capacities suffice to achieve a zero UE dropping rate. Besides, the proper choice of maximum path length setting should take into account segment capacity and its utilization due to the relation between the two.
A Perspective on the Impact of Group Delay Dispersion in Future Terahertz Wireless Systems
Authors: Karl Strecker, Sabit Ekin, John F. O'Hara
Date: 2024-05-30 00:00:00

This article discusses the challenges and opportunities of managing group delay dispersion (GDD) and its relation to the performance standards of future sixth-generation (6G) wireless communication systems utilizing terahertz frequency waves. The unique susceptibilities of 6G systems to GDD are described, along with a quantitative description of the sources of GDD, including multipath, rough surface scattering, intelligent reflecting surfaces, and propagation through the atmosphere. An experimental case-study is presented that confirms previous models quantifying the impact of atmospheric GDD. Several GDD manipulation strategies are presented illustrating their hindered effectiveness in the 6G context. Conversely, some benefits of leveraging GDD to enhance 6G systems, such as improved security and simplified hardware, are also discussed. Finally, a perspective on using photonic GDD control devices is provided, revealing quantitative benefits that may unburden existing equalization schemes. The article argues that GDD will uniquely and significantly impact some 6G systems, but that its careful consideration along with new mitigation strategies, including photonic devices, will help optimize system performance. The conclusion provides a perspective to guide future research in this area.
An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback
Authors: Xinran Sun, Zhengming Zhang, Luxi Yang
Date: 2024-05-30 00:00:00
Tasks: Quantization

The efficacy of massive multiple-input multiple-output (MIMO) techniques heavily relies on the accuracy of channel state information (CSI) in frequency division duplexing (FDD) systems. Many works focus on CSI compression and quantization methods to enhance CSI reconstruction accuracy with lower feedback overhead. In this letter, we propose CsiConformer, a novel CSI feedback network that combines convolutional operations and self-attention mechanisms to improve CSI feedback accuracy. Additionally, a new quantization module is developed to improve encoding efficiency. Experiment results show that CsiConformer outperforms previous state-of-the-art networks, achieving an average accuracy improvement of 17.67\% with lower computational overhead.
Integrated Sensing and Communications Framework for 6G Networks
Authors: Hongliang Luo, Tengyu Zhang, Chuanbin Zhao, Yucong Wang, Bo Lin, Yuhua Jiang, Dongqi Luo, Feifei Gao
Date: 2024-05-30 00:00:00
Tasks: ISAC, Material Recognition

In this paper, we propose a novel integrated sensing and communications (ISAC) framework for the sixth generation (6G) mobile networks, in which we decompose the real physical world into static environment, dynamic targets, and various object materials. The ubiquitous static environment occupies the vast majority of the physical world, for which we design static environment reconstruction (SER) scheme to obtain the layout and point cloud information of static buildings. The dynamic targets floating in static environments create the spatiotemporal transition of the physical world, for which we design comprehensive dynamic target sensing (DTS) scheme to detect, estimate, track, image and recognize the dynamic targets in real-time. The object materials enrich the electromagnetic laws of the physical world, for which we develop object material recognition (OMR) scheme to estimate the electromagnetic coefficient of the objects. Besides, to integrate these sensing functions into existing communications systems, we discuss the interference issues and corresponding solutions for ISAC cellular networks. Furthermore, we develop an ISAC hardware prototype platform that can reconstruct the environmental maps and sense the dynamic targets while maintaining communications services. With all these designs, the proposed ISAC framework can support multifarious emerging applications, such as digital twins, low altitude economy, internet of vehicles, marine management, deformation monitoring, etc.
Novel Synchronization Scheme for Cooperative ISAC Systems
Authors: Qihao Peng, Hong Ren, Zhendong Peng, Cunhua Pan, Maged Elkashlan, Dongming Wang, Jiangzhou Wang, Xiaohu You
Date: 2024-05-29 00:00:00
Tasks: ISAC

Carrier frequency and timing synchronization play the fundamental roles in cooperative integrating communication and sensing (ISAC). To mitigate the effects of synchronization error, this paper develops a novel synchronization scheme in cell-free massive multiple-input multiple-output (mMIMO) systems. First, we characterize the impacts of pilot contamination on synchronization performance, i.e., Cramer-Rao bound (CRB). Furthermore, a maximum likelihood algorithm is presented to estimate the CFO and TO among the pairing APs. Then, to minimize the sum of CRBs, we devise a synchronization strategy based on a pilot-sharing scheme by jointly optimizing the cluster classification, synchronization overhead, and pilot-sharing scheme, while simultaneously considering the overhead and each AP's synchronization requirements. To solve this NP-hard problem, we simplify it into two sub-problems, namely cluster classification problem and the pilot sharing problem. To strike a balance between synchronization performance and overhead, we first classify the clusters by using the K-means algorithm, and propose a criteria to find a good set of master APs. Then, the pilot-sharing scheme is obtained by using the swap-matching operations. Simulation results validate the accuracy of our derivations and demonstrate the effectiveness of the proposed scheme over the benchmark schemes.
Position Error Bound for Cooperative Sensing in MIMO-OFDM Networks
Authors: Lorenzo Pucci, Andrea Giorgetti
Date: 2024-05-30 00:00:00
Tasks: Position

Only the chairs can edit This paper investigates the fundamental limits of target position estimation accuracy of joint sensing and communication (JSC) networks comprising several monostatic base stations (BSs) that cooperate to localize targets. Specifically, each BS adopts a multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) scheme with a multi-beam radiation pattern to partition power between communication and sensing tasks. Building on prior works, we derive a general framework to evaluate the positioning accuracy of a target in networks with an arbitrary number of cooperating BSs and arbitrary geometrical configurations using Fisher information. Numerical results demonstrate the benefits of cooperation between BSs in improving target localization accuracy and provide insights into the relationships between various system parameters, which may aid in designing JSC networks.
Generalized BER Performance Analysis for SIC-based Uplink NOMA Systems
Authors: Mahmoud AlaaEldin, Emad Alsusa, Mohammad Al-jarrah, Karim G. Seddik
Date: 2024-05-30 00:00:00
Tasks: Form

Non-orthogonal multiple access (NOMA) is widely recognized for its spectral and energy efficiency, which allows more users to share the network resources more effectively. This paper provides a generalized bit error rate (BER) performance analysis of successive interference cancellation (SIC)-based uplink NOMA systems under Rayleigh fading channels, taking into account error propagation resulting from SIC imperfections. Exact closed-form BER expressions are initially derived for scenarios with 2 and 3 users using quadrature phase shift keying (QPSK) modulation. These expressions are then generalized to encompass any arbitrary rectangular/square M-ary quadrature amplitude modulation (M-QAM) order, number of NOMA users, and number of BS antennas. Additionally, by utilizing the derived closed-form BER expressions, a simple and practically feasible power allocation (PA) technique is devised to minimize the sum bit error rate of the users and optimize the SIC-based NOMA detection at the base-station (BS). The derived closed-form expressions are corroborated through Monte Carlo simulations. It is demonstrated that these expressions can be effective for optimal uplink PA to ensure optimized SIC detection that mitigates error floors. It is also shown that significant performance improvements are achieved regardless of the users' decoding order, making uplink SIC-based NOMA a viable approach.
Motor Imagery Task Alters Dynamics of Human Body Posture
Authors: Fatemeh Delavari, Seyyed Mohammad Reza Hashemi Golpayegani, Mohammad Ali Ahmadi-Pajouh
Date: 2024-05-29 00:00:00
Tasks: Motor Imagery

Motor Imagery (MI) is gaining traction in both rehabilitation and sports settings, but its immediate influence on human postural control is not yet clearly understood. The focus of this study is to examine the effects of MI on the dynamics of the Center of Pressure (COP), a crucial metric for evaluating postural stability. In the experiment, thirty healthy young adults participated in four different scenarios: normal standing with both open and closed eyes, and kinesthetic motor imagery focused on mediolateral (ML) and anteroposterior (AP) sway movements. A mathematical model was developed to characterize the nonlinear dynamics of the COP and to assess the impact of MI on these dynamics. Our results show a statistically significant increase (p-value<0.05) in variables such as COP path length and Long-Range Correlation (LRC) during MI compared to the closed-eye and normal standing conditions. These observations align well with psycho-neuromuscular theory, which suggests that imagining a specific movement activates neural pathways, consequently affecting postural control. This study presents compelling evidence that motor imagery not only has a quantifiable impact on COP dynamics but also that changes in the Center of Pressure (COP) are directionally consistent with the imagined movements. This finding holds significant implications for the field of rehabilitation science, suggesting that motor imagery could be strategically utilized to induce targeted postural adjustments. Nonetheless, additional research is required to fully understand the complex mechanisms that underlie this relationship and to corroborate these results across a more diverse set of populations.
Optimising RF linear Amplifier for maximum efficiency and linearity
Authors: Srdan Milic, Igor Krois
Date: 2024-05-29 00:00:00

A method for increasing efficiency of radio frequency (RF) amplifier employing laterally diffused metal oxide semiconductor (LDMOS) transistors coupled to an RF exciter depending on the emission mode of modulated RF input signals generated by exciter, if exciter output signal is of a type where modulated RF signals do not have continuously varying envelope, biasing the LDMOS transistor in the RF amplifier with fixed quiescent drain current and fixed drain voltage supply to cause LDMOS transistors to operate in compression and if exciter output signal is of a type where modulated RF signals do have continuously varying envelope, biasing the LDMOS transistors in the RF amplifier for linear operation.
Integrated Communication and Imaging: Design, Analysis, and Performances of COSMIC Waveforms
Authors: Marco Manzoni, Francesco Linsalata, Maurizio Magarini, Stefano Tebaldini
Date: 2024-05-29 00:00:00

This paper presents COSMIC (Connectivity-Oriented Sensing Method for Imaging and Communication), an innovative waveform design framework that integrates environmental radio imaging with robust communication capabilities. COSMIC introduces an extended orthogonality condition achieved through algebraic precoding across transmitting antennas, differentiating it from conventional time, frequency, or space multiplexing techniques. By leveraging the constrained imaging field of view relative to the signal duration, COSMIC enables the simultaneous transport of information while preserving high sensing performance. Numerical evaluations reveal that COSMIC significantly outperforms state-of-the-art methods, doubling the imaging Signal-to-Noise Ratio and substantially reducing the Integrated Side Lobe Ratio, thus demonstrating its effectiveness in combining communication and imaging functionalities.
Multi-Channel Multi-Step Spectrum Prediction Using Transformer and Stacked Bi-LSTM
Authors: Guangliang Pan, Jie Li, Minglei Li
Date: 2024-05-29 00:00:00
Tasks: Decoder, Prediction

Spectrum prediction is considered as a key technology to assist spectrum decision. Despite the great efforts that have been put on the construction of spectrum prediction, achieving accurate spectrum prediction emphasizes the need for more advanced solutions. In this paper, we propose a new multichannel multi-step spectrum prediction method using Transformer and stacked bidirectional LSTM (Bi- LSTM), named TSB. Specifically, we use multi-head attention and stacked Bi-LSTM to build a new Transformer based on encoder-decoder architecture. The self-attention mechanism composed of multiple layers of multi-head attention can continuously attend to all positions of the multichannel spectrum sequences. The stacked Bi-LSTM can learn these focused coding features by multi-head attention layer by layer. The advantage of this fusion mode is that it can deeply capture the long-term dependence of multichannel spectrum data. We have conducted extensive experiments on a dataset generated by a real simulation platform. The results show that the proposed algorithm performs better than the baselines.