Search Results for author:
Found 39 papers, 3 papers with code
Frame Structure and Protocol Design for Sensing-Assisted NR-V2X Communications
In this study, we propose novel frame structures that incorporate ISAC signals for three crucial stages in the NR-V2X system: initial access, connected mode, and beam failure and recovery.
Novel KLD-based Resource Allocation for Integrated Sensing and Communication
In this paper, we introduce a novel resource allocation approach for integrated sensing-communication (ISAC) using the Kullback-Leibler divergence (KLD) metric.
Securing the Sensing Functionality in ISAC Networks: An Artificial Noise Design
Integrated sensing and communications (ISAC) systems employ dual-functional signals to simultaneously accomplish radar sensing and wireless communication tasks.
Intelligent Surface Empowered Integrated Sensing and Communication: From Coexistence to Reciprocity
Integrated sensing and communication (ISAC) has attracted growing interests for sixth-generation (6G) and beyond wireless networks.
Robust NOMA-assisted OTFS-ISAC Network Design with 3D Motion Prediction Topology
This paper proposes a novel non-orthogonal multiple access (NOMA)-assisted orthogonal time-frequency space (OTFS)-integrated sensing and communication (ISAC) network, which uses unmanned aerial vehicles (UAVs) as air base stations to support multiple users.
Towards Structural Sparse Precoding: Dynamic Time, Frequency, Space, and Power Multistage Resource Programming
This requires multistage optimization for full resource domain dynamic programming.
Robust Joint Active-Passive Beamforming Design for IRS-Assisted ISAC Systems
A low complexity and efficient joint optimization of transmit beamforming at the BS and reflective beamforming at the IRS is proposed.
Energy-Efficient Beamforming Design for Integrated Sensing and Communications Systems
In this paper, we investigate the design of energy-efficient beamforming for an ISAC system, where the transmitted waveform is optimized for joint multi-user communication and target estimation simultaneously.
Faster-Than-Nyquist Symbol-Level Precoding for Wideband Integrated Sensing and Communications
In this paper, we present an innovative symbol-level precoding (SLP) approach for a wideband multi-user multi-input multi-output (MU-MIMO) downlink Integrated Sensing and Communications (ISAC) system employing faster-than-Nyquist (FTN) signaling.
Towards ISAC-Empowered Vehicular Networks: Framework, Advances, and Opportunities
Connected and autonomous vehicle (CAV) networks face several challenges, such as low throughput, high latency, and poor localization accuracy.
ISAC-Enabled V2I Networks Based on 5G NR: How Much Can the Overhead Be Reduced?
The emergence of the fifth-generation (5G) New Radio (NR) brings additional possibilities to vehicle-to-everything (V2X) network with improved quality of services.
Robust Symbol Level Precoding for Overlay Cognitive Radio Networks
This paper focuses on designing robust symbol-level precoding (SLP) in an overlay cognitive radio (CR) network, where the primary and secondary networks transmit signals concurrently.
RIS-assisted Integrated Sensing and Communications: A Subspace Rotation Approach
We first show that the sensing and communication (S&C) performance can be jointly improved due to the capability of the RISs to control the ISAC channel.
Sensing-Assisted Eavesdropper Estimation: An ISAC Breakthrough in Physical Layer Security
Using the resulting information about potential Eves, we formulate secrecy rate expressions, that are a function of the Eves' estimation accuracy.
Seventy Years of Radar and Communications: The Road from Separation to Integration
Radar and communications (R&C) as key utilities of electromagnetic (EM) waves have fundamentally shaped human society and triggered the modern information age.
Energy-Efficient Trajectory Design of a Multi-IRS Assisted Portable Access Point
In this work, we propose a framework for energy-efficient trajectory design of an unmanned aerial vehicle (UAV)-based portable access point (PAP) deployed to serve a set of ground nodes (GNs).
ISAC from the Sky: UAV Trajectory Design for Joint Communication and Target Localization
In this paper, we consider an airborne integrated sensing and communications (ISAC) system where a UAV, which acts both as a communication BS and a mono-static radar, flies over a given area to transmit downlink signal to a ground communication user.
Vehicular Connectivity on Complex Trajectories: Roadway-Geometry Aware ISAC Beam-tracking
In this paper, we propose sensing-assisted beamforming designs for vehicles on arbitrarily shaped roads by relying on integrated sensing and communication (ISAC) signalling. Specifically, we aim to address the limitations of conventional ISAC beam-tracking schemes that do not apply to complex road geometries.
An Experimental Proof of Concept for Integrated Sensing and Communications Waveform Design
This experimental work focuses on a dual-functional radar sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both radar sensing and communication functions.
Pre-scaling and Codebook Design for Joint Radar and Communication Based on Index Modulation
This paper develops an efficient index modulation (IM) approach for the joint radar-communication (JRC) system based on a multi-carrier multiple-input multiple-output (MIMO) radar.
Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets
The first stage is exploited for ISAC transmission, where a wide beam is adopted for both communication and sensing.
Learning-Based Symbol Level Precoding: A Memory-Efficient Unsupervised Learning Approach
Symbol level precoding (SLP) has been proven to be an effective means of managing the interference in a multiuser downlink transmission and also enhancing the received signal power.
An Unsupervised Deep Unfolding Framework for robust Symbol Level Precoding
Symbol Level Precoding (SLP) has attracted significant research interest due to its ability to exploit interference for energy-efficient transmission.
A Memory-Efficient Learning Framework for SymbolLevel Precoding with Quantized NN Weights
Our results show that while SLP-DNet provides near-optimal performance, its quantized versions through SQ yield 3. 46x and 2. 64x model compression for binary-based and ternary-based SLP-SQDNets, respectively.
MIMO-OFDM Dual-Functional Radar-Communication Systems: Low-PAPR Waveform Design
In this paper, we explore a dual-functional radar-communication (DFRC) system for achieving integrated sensing and communications (ISAC).
Physical Layer Anonymous Precoding: The Path to Privacy-Preserving Communications
In contrast to traditional security and privacy designs that aim to prevent confidential information from being eavesdropped upon by adversaries, or learned by unauthorized parties, in this paper we consider designs that mask the users' identities during communication, hence resulting in anonymous communications.
Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond
As the standardization of 5G is being solidified, researchers are speculating what 6G will be.
Towards Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication and Security
At the same time, the sensing capability incorporated in the ISAC transmission offers unique opportunities to design secure ISAC techniques.
Secure Dual-Functional Radar-Communication Transmission: Exploiting Interference for Resilience Against Target Eavesdropping
We study security solutions for dual-functional radar communication (DFRC) systems, which detect the radar target and communicate with downlink cellular users in millimeter-wave (mmWave) wireless networks simultaneously.
Secure Dual-Functional Radar-Communication System via Exploiting Known Interference in the Presence of Clutter
This paper addresses the problem that designing the transmit waveform and receive beamformer aims to maximize the receive radar SINR for secure dual-functional radar-communication (DFRC) systems, where the undesired multi-user interference (MUI) is transformed to useful power.
An Unsupervised Learning-Based Approach for Symbol-Level-Precoding
This paper proposes an unsupervised learning-based precoding framework that trains deep neural networks (DNNs) with no target labels by unfolding an interior point method (IPM) proximal `log' barrier function.
Hardware Efficient Joint Radar-Communications with Hybrid Precoding and RF Chain Optimization
In this paper, we aim to achieve energy efficient design with minimum hardware requirement for hybrid precoding, which enables a large number of antennas with minimal number of RF chains, and sub-arrayed multiple-input multiple-output (MIMO) radar based joint radar-communication (JRC) systems.
Rate-Splitting Multiple Access for Joint Radar-Communications with Low-Resolution DACs
In this paper, we introduce the design of a multi-antenna Joint Radar-Communication (JRC) system with Rate Splitting Multiple Access (RSMA) and low resolution Digital-to-Analog Converter (DAC) units.
An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing
Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, sharing a majority of hardware and signal processing modules and, in a typical case, sharing a single transmitted signal.
Reconfigurable Intelligent Surface Aided Mobile Edge Computing: From Optimization-Based to Location-Only Learning-Based Solutions
In this paper, we explore optimization-based and data-driven solutions in a reconfigurable intelligent surface (RIS)-aided multi-user mobile edge computing (MEC) system, where the user equipment (UEs) can partially offload their computation tasks to the access point (AP).
Cramér-Rao Bound Optimization for Joint Radar-Communication Design
We employ the Cram\'er-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios.
Learning to Select for MIMO Radar based on Hybrid Analog-Digital Beamforming
In this paper, we propose an energy-efficient radar beampattern design framework for a Millimeter Wave (mmWave) massive multi-input multi-output (mMIMO) system, equipped with a hybrid analog-digital (HAD) beamforming structure.
Bayesian Predictive Beamforming for Vehicular Networks: A Low-overhead Joint Radar-Communication Approach
To accurately estimate the motion parameters of vehicles in real-time, we propose a novel message passing algorithm based on factor graph, which yields near optimal solution to the maximum a posteriori estimation.
Complexity-Scalable Neural Network Based MIMO Detection With Learnable Weight Scaling
This paper introduces a framework for systematic complexity scaling of deep neural network(DNN) based MIMO detectors.
