Related papers: Faster-than-Nyquist Signaling for Next-Generation …
Positioning has recently received considerable attention as a key enabler in emerging applications such as extended reality, unmanned aerial vehicles and smart environments. These applications require both data communication and…
Classical artificial neural networks have witnessed widespread successes in machine-learning applications. Here, we propose fermion neural networks (FNNs) whose physical properties, such as local density of states or conditional…
Optical wireless communication (OWC) covering an ultra-wide range of unlicensed spectrum has emerged as an extent efficient solution to mitigate conventional RF spectrum scarcity ranging from communication distances from nm to several…
Cell-free (CF) architecture and full-duplex (FD) communication are leading candidates for next-generation wireless networks. The CF framework removes cell boundaries in traditional cell-based systems, thereby mitigating inter-cell…
Faster-than-Nyquist (FTN) signaling and superimposed pilot (SP) techniques are effective solutions for significantly enhancing the spectral efficiency (SE) in next-generation wireless communication systems. This paper proposes an innovative…
While 5G networks are being rolled out, the definition of the potential 5G-Advanced features and the identification of disruptive technologies for 6G systems are being addressed by the scientific and academic communities to tackle the…
The faster-than-Nyquist nonlinear frequency division multiplexing system was first proposed, which provided 12.5% and 25% increase in spectral efficiency for the compression factor of 0.89 and 0.8 respectively.
Fast-sampled models are essential for control design, e.g., to address intersample behavior. The aim of this paper is to develop a non-parametric identification technique for fast-sampled models of systems that have relevant dynamics and…
With deployment of 6G technology, it is envisioned that competitive edge of wireless networks will be sustained and next decade's communication requirements will be stratified. Also 6G will aim to aid development of a human society which is…
Integrated sensing and communication (ISAC) is expected to be natively supported by future 6G wireless radios, yet most mmWave sensing solutions still rely on dedicated radar hardware incompatible with cost and power constrained wireless…
Convolutional neural networks (CNNs) have a large number of variables and hence suffer from a complexity problem for their implementation. Different methods and techniques have developed to alleviate the problem of CNN's complexity, such as…
Implicit neural representations have emerged as a powerful paradigm to represent signals such as images and sounds. This approach aims to utilize neural networks to parameterize the implicit function of the signal. However, when…
As an efficient graph analytical tool, graph neural networks (GNNs) have special properties that are particularly fit for the characteristics and requirements of wireless communications, exhibiting good potential for the advancement of…
A target recognition framework relying on near-field integrated sensing and communication (ISAC) systems is proposed. By exploiting the distance-dependent spatial signatures provided by the near-field spherical wavefront, high-accuracy…
To support the development of internet-of-things applications, an enormous population of low-power devices are expected to be incorporated in wireless networks performing sensing and communication tasks. As a key technology for improving…
The architecture of a neural network and the selection of its activation function are both fundamental to its performance. Equally vital is ensuring these two elements are well-matched, as their alignment is key to achieving effective…
This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks (QNNs) in the Noisy Intermediate-Scale Quantum (NISQ) era. In this paper, we present an integrated…
Optical neural networks have long cast attention nowadays. Like other optical structured neural networks, fiber neural networks which utilize the mechanism of light transmission to compute can take great advantages in both computing…
A new frequency switching receiver structure is proposed for simultaneous wireless information and power transfer in multi-carrier communication systems. Each subcarrier is switched to either the energy harvesting unit or the information…
In some Internet of Things (IoT) applications, multi-path propagation is a main constraint of communication channel. Recently, the chaotic baseband wireless communication system (CBWCS) is promising to eliminate the inter-symbol…