Related papers: Complex CNN CSI Enhancer for Integrated Sensing an…
Integrated Sensing And Communication (ISAC) has been recognized as a promising technology in the 6G communication. A realistic channel model is a prerequisite for designing ISAC systems. Most existing channel models independently generate…
Future wireless networks are poised to transform into integrated sensing and communication (ISAC) networks, unlocking groundbreaking services such as digital twinning. To harness the full potential of ISAC networks, it is essential to…
A near-field integrated sensing and communications (ISAC) framework is proposed, which introduces an additional distance dimension for both sensing and communications compared to the conventional far-field system. In particular, the…
Selection of hyperparameters in deep neural networks is a challenging problem due to the wide search space and emergence of various layers with specific hyperparameters. There exists an absence of consideration for the neural architecture…
As one of the key usage scenarios for the sixth generation (6G) wireless networks, integrated sensing and communication (ISAC) provides an efficient framework to achieve simultaneous wireless sensing and communication. However, traditional…
The implementation of integrated sensing and communication (ISAC) highly depends on the effective beamforming design exploiting accurate instantaneous channel state information (ICSI). However, channel tracking in ISAC requires large amount…
Integrated sensing and communication (ISAC) emerges as a promising technology for B5G/6G, particularly in the millimeter-wave (mmWave) band. However, the widely utilized hybrid architecture in mmWave systems compromises multiplexing gain…
Sixth generation (6G) wireless technology is anticipated to introduce Integrated Sensing and Communication (ISAC) as a transformative paradigm. ISAC unifies wireless communication and RADAR or other forms of sensing to optimize spectral and…
Integrated sensing and communication (ISAC) is envisioned be to one of the paradigms upon which next-generation mobile networks will be built, extending localization and tracking capabilities, as well as giving birth to environment-aware…
Motivated by the issue of inaccurate channel state information (CSI) at the base station (BS), which is commonly due to feedback/processing delays and compression problems, in this paper, we introduce a scalable idea of adopting artificial…
To achieve higher throughput in next-generation Wi-Fi systems, a station (STA) needs to efficiently compress channel state information (CSI) and feed it back to an access point (AP). In this paper, we propose a novel deep learning…
Integrated super-resolution sensing and communication (ISSAC) has emerged as a promising technology to achieve extremely high precision sensing for those key parameters, such as the angles of the sensing targets. In this paper, we propose…
Modulation recognition is a challenging task while performing spectrum sensing in a cognitive radio setup. Recently, the use of deep convolutional neural networks (CNNs) has shown to achieve state-of-the-art accuracy for modulation…
Deep learning approaches have been widely used in Automatic Speech Recognition (ASR) and they have achieved a significant accuracy improvement. Especially, Convolutional Neural Networks (CNNs) have been revisited in ASR recently. However,…
Segmented pinching antenna assisted integrated sensing and communication (ISAC) systems enable flexible spatial resource utilization by allowing different waveguide segments to be dynamically configured for transmission and reception.…
Sparse channel estimation problem is one of challenge technical issues in stable broadband wireless communications. Based on square error criterion (SEC), adaptive sparse channel estimation (ASCE) methods, e.g., zero-attracting least mean…
We propose a novel coded integrated passive sensing and communication (CIPSAC) system with orthogonal frequency division multiplexing (OFDM), where a multi-antenna base station (BS) passively senses the parameters of the targets and decodes…
To advance integrated sensing and communications (ISAC) in sixth-generation (6G) extremely large-scale multiple-input multiple-output (XL-MIMO) networks, a low-complexity compressed sensing (CS)-based dictionary design is proposed for…
Recent research in deep learning (DL) has investigated the use of the Fast Fourier Transform (FFT) to accelerate the computations involved in Convolutional Neural Networks (CNNs) by replacing spatial convolution with element-wise…
Integrated sensing and communication (ISAC) is increasingly recognized as a pivotal technology for next-generation cellular networks, offering mutual benefits in both sensing and communication capabilities. This advancement necessitates a…