Related papers: Fourth-Order Hierarchical Array: A Novel Scheme fo…
In this paper, we propose a distributed cluster formation (CF) and resource allocation (RA) framework for non-ideal non-orthogonal multiple access (NOMA) schemes in heterogeneous networks. The imperfection of the underlying NOMA scheme is…
A novel frequency diverse array (FDA)-assisted secure transmission framework is proposed, which leverages additional frequency offsets to enhance physical layer security. Specifically, an FDA-assisted wiretap channel is considered, where…
This paper investigates the problem of noncoherent direction-of-arrival (DOA) estimation using different sparse subarrays. In particular, we present a Multiple Measurements Vector (MMV) model for noncoherent DOA estimation based on a…
The problem of joint direction-of-arrival estimation and distorted sensor detection has received a lot of attention in recent decades. Most state-of-the-art work formulated such a problem via low-rank and row-sparse decomposition, where the…
Localizing near-field sources considering practical arrays is important in wireless communications. Array-based apertures exhibit mutual coupling between the array elements, which can significantly degrade the performance of the…
The problem of multi-objective design of sparse MIMO arrays for better multitarget detection capabilities is considered. A novel approach for efficient utilization of the antenna design resources; namely, the number of available array…
Integrated sensing and communication (ISAC) has emerged as a promising paradigm for next-generation (6G) wireless networks, unifying radar sensing and communication on a shared hardware platform. This paper proposes a dynamic array…
Dual-function radar communications (DFRC) systems have recently been proposed to enable the coexistence of radar and wireless communications, which in turn alleviates the increased spectrum congestion crisis. In this paper, we consider the…
This paper proposes and demonstrates a PHY-layer design of a real-time prototype that supports Ultra-Reliable Communication (URC) in wireless infrastructure networks. The design makes use of Orthogonal Frequency Division Multiple Access…
The signal processing community currently witnesses the emergence of sensor array processing and Direction-of-Arrival (DoA) estimation in various modern applications, such as automotive radar, mobile user and millimeter wave indoor…
Coded caching scheme originally proposed by Maddah-Ali and Niesen (MN) achieves an optimal transmission rate $R$ under uncoded placement but requires a subpacketization level $F$ which increases exponentially with the number of users $K$…
This paper studies the effects of directional antenna element complex gain patterns and nonidealities in direction of arrival (DoA) estimation. We compare sparse arrays and classical uniform linear arrays, harnessing EM simulation tools to…
Recently, several array radar structures combined with sub-Nyquist techniques and corresponding algorithms have been extensively studied. Carrier frequency and direction-of-arrival (DOA) estimations of multiple narrow-band signals received…
Multibeam analog arrays have been proposed for millimeter-wave joint communication and sensing (JCAS). We study multibeam planar arrays for JCAS, providing time division duplex communication and full-duplex sensing with steerable beams. In…
The combination of frequency diverse array (FDA) radar technology with the multiple input multiple output (MIMO) radar architecture and waveform diversity techniques potentially promises a high integration gain with respect to conventional…
Interference Alignment (IA) is a transmission scheme which achieves 1/2 Degrees-of-Freedom (DoF) per transmit-antenna per user. The constraints imposed on the scheme are based on the linear receiver since conventional IA assumes Gaussian…
Optimal sensor placement (OSP) is critical for efficient, accurate monitoring, control, and inference in complex physical systems. We propose a machine-learning-based feature attribution (FA) framework to identify OSP for target…
Factor analysis provides a canonical framework for imposing lower-dimensional structure such as sparse covariance in high-dimensional data. High-dimensional data on the same set of variables are often collected under different conditions,…
Federated Learning (FL) is a distributed machine learning framework that inherently allows edge devices to maintain their local training data, thus providing some level of privacy. However, FL's model updates still pose a risk of privacy…
Future wireless networks, deploying thousands of antenna elements, may operate in the radiative near-field (NF), enabling spatial multiplexing across both angle and range domains. Sparse arrays have the potential to achieve comparable…