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Found 49 papers, 4 papers with code
Ubiquitous Integrated Sensing and Communications for Massive MIMO LEO Satellite Systems
The next sixth generation (6G) networks are envisioned to integrate sensing and communications in a single system, thus greatly improving spectrum utilization and reducing hardware costs.
Enhancing Indoor and Outdoor THz Communications with Beyond Diagonal-IRS: Optimization and Performance Analysis
This work investigates the application of Beyond Diagonal Intelligent Reflective Surface (BD-IRS) to enhance THz downlink communication systems, operating in a hybrid: reflective and transmissive mode, to simultaneously provide services to indoor and outdoor users.
Joint Computation and Communication Resource Optimization for Beyond Diagonal UAV-IRS Empowered MEC Networks
We propose a joint optimization strategy to reduce system's worst-case latency and UAV hovering time by optimizing BD-IRS-UAV deployment and resource allocation.
Deep Reinforcement Learning for Backscatter Communications: Augmenting Intelligence in Future Internet of Things
Backscatter communication (BC) technology offers sustainable solutions for next-generation Internet-of-Things (IoT) networks, where devices can transmit data by reflecting and adjusting incident radio frequency signals.
Reconfigurable Intelligent Surfaces for 6G Non-Terrestrial Networks: Assisting Connectivity from the Sky
This paper studies the potential of RIS-integrated NTNs to revolutionize the next-generation connectivity.
Reconfigurable Intelligent Surfaces Enhanced NOMA D2D Communications Underlaying UAV Networks
The objective is to maximize the sum rate of NOMA D2D communications by simultaneously optimizing the power budget of D2D transmitter, NOMA power allocation coefficients of D2D receivers and passive beamforming of RIS while guaranteeing the quality of services of UAV user.
Harnessing the Power of Swarm Satellite Networks with Wideband Distributed Beamforming
The space communications industry is challenged to develop a technology that can deliver broadband services to user terminals equipped with miniature antennas, such as handheld devices.
RIS-Assisted Energy-Efficient LEO Satellite Communications with NOMA
Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming.
Joint Optimization of 3D Placement and Radio Resource Allocation for per-UAV Sum Rate Maximization
The main aim of this work is to derive an efficient technique for the allocation of radio resources, $3$D placement of UAVs, and user association matrices.
Multi-Objective Optimization for 3D Placement and Resource Allocation in OFDMA-based Multi-UAV Networks
The main aim of this work is to derive the optimal allocation of radio resources, 3D placement of UAVs, and user association matrices.
Energy-Efficient RIS-Enabled NOMA Communication for 6G LEO Satellite Networks
The proposed framework simultaneously optimizes the transmit power of ground terminals at LEO satellite and passive beamforming at RIS while ensuring the quality of services.
Opportunities for Intelligent Reflecting Surfaces in 6G-Empowered V2X Communications
This paper first describes the introduction of 6G-empowered V2X communications and IRS technology.
Hybrid Beamforming in mmWave Dual-Function Radar-Communication Systems: Models, Technologies, and Challenges
As a promising technology in beyond-5G (B5G) and 6G, dual-function radar-communication (DFRC) aims to ensure both radar sensing and communication on a single integrated platform with unified signaling schemes.
Rate Splitting Multiple Access for Cognitive Radio GEO-LEO Co-Existing Satellite Networks
We also propose two suboptimal schemes with fixed power allocation and random subcarrier beam assignment as the benchmark.
Joint Beam Hopping and Carrier Aggregation in High Throughput Multi-Beam Satellite Systems
Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and to significantly improve the spectral efficiency.
Integration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors
Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks.
Opportunities for Physical Layer Security in UAV Communication Enhanced with Intelligent Reflective Surfaces
Unmanned Aerial Vehicles (UAVs) are an important component of next-generation wireless networks that can assist in high data rate communications and provide enhanced coverage. Their high mobility and aerial nature offer deployment flexibility and low-cost infrastructure support to existing cellular networks and provide many applications that rely on mobile wireless communications.
Double-Phase-Shifter based Hybrid Beamforming for mmWave DFRC in the Presence of Extended Target and Clutters
In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains.
Integration of Backscatter Communication with Multi-cell NOMA: A Spectral Efficiency Optimization under Imperfect SIC
This paper proposes a new optimization approach to enhance the spectral efficiency of nonorthogonal multiple access (NOMA)-BC network.
Optimal Sensor Placement for Source Localization: A Unified ADMM Approach
Source localization plays a key role in many applications including radar, wireless and underwater communications.
Resource Allocation in Heterogeneously-Distributed Joint Radar-Communications under Asynchronous Bayesian Tracking Framework
Optimal allocation of shared resources is key to deliver the promise of jointly operating radar and communications systems.
Heterogeneously-Distributed Joint Radar Communications: Bayesian Resource Allocation
In this paper, we focus on a heterogeneous radar and communication network (HRCN), which consists of various generic radars for multiple target tracking (MTT) and wireless communications for multiple users.
Frequency-packed Faster-than-Nyquist Signaling via Symbol-level Precoding for Multi-user MISO Redundant Transmissions
This work addresses the issue of interference generated by co-channel users in downlink multi-antenna multicarrier systems with frequency-packed faster-than-Nyquist (FTN) signaling.
Broadband Non-Geostationary Satellite Communication Systems: Research Challenges and Key Opportunities
Besides conventional geostationary (GSO) satellite broadband communication services, non-geostationary (NGSO) satellites are envisioned to support various new communication use cases from countless industries.
On the Performance of One-Bit DoA Estimation via Sparse Linear Arrays
Specifically, we first investigate the identifiability conditions for the DoA estimation problem from one-bit SLA data and establish an equivalency with the case when DoAs are estimated from infinite-bit unquantized measurements.
On the Secrecy Capacity of MIMO Wiretap Channels: Convex Reformulation and Efficient Numerical Methods
In the first method we capitalize on the accelerated DC algorithm which requires solving a sequence of convex subproblems, for which we propose an efficient iterative algorithm where each iteration admits a closed-form solution.
Information Theory Signal Processing Information Theory
Secure Vehicular Communications through Reconfigurable Intelligent Surfaces
Reconfigurable intelligent surfaces (RIS) is considered as a revolutionary technique to improve the wireless system performance by reconfiguring the radio wave propagation environment artificially.
Reconfigurable Intelligent Surfaces in Challenging Environments: Underwater, Underground, Industrial and Disaster
Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering.
Joint Constellation Rotation and Symbol-level Precoding Optimization in the Downlink of Multiuser MISO Channels
This paper tackles the problem of the simultaneous interference among the multiple users in the downlink of a wireless multiantenna system.
Multi-Antenna Data-Driven Eavesdropping Attacks and Symbol-Level Precoding Countermeasures
In this work, we consider secure communications in wireless multi-user (MU) multiple-input single-output (MISO) systems with channel coding in the presence of a multi-antenna eavesdropper (Eve).
Widely-distributed Radar Imaging Based on Consensus ADMM
In this paper, a novel $l_1$-regularized, consensus alternating direction method of multipliers (CADMM) based algorithm is proposed to mitigate artifacts by exploiting a widely-distributed radar system's spatial diversity.
Reconfigurable Intelligent Surfaces for Smart Cities: Research Challenges and Opportunities
The concept of Smart Cities has been introduced as a way to benefit from the digitization of various ecosystems at a city level.
Short-Packet Communications for MIMO NOMA Systems over Nakagami-m Fading: BLER and Minimum Blocklength Analysis
The achieved results show that MIMO NOMA can serve multiple users simultaneously using a smaller blocklength compared with MIMO OMA, thus demonstrating the benefits of MIMO NOMA for SPC in minimizing the transmission latency.
Downlink Transmit Design for Massive MIMO LEO Satellite Communications
We show that, in this case, the design of precoding vectors can be simplified into that of scalar variables, for which an effective algorithm is developed.
Localization with One-Bit Passive Radars in Narrowband Internet-of-Things using Multivariate Polynomial Optimization
To support the low-capacity links to the fusion center (FC), the range estimates obtained at individual sensors are then converted to one-bit data.
A Novel Heap-based Pilot Assignment for Full Duplex Cell-Free Massive MIMO with Zero-Forcing
This paper investigates the combined benefits of full-duplex (FD) and cell-free massive multiple-input multipleoutput (CF-mMIMO), where a large number of distributed access points (APs) having FD capability simultaneously serve numerous uplink and downlink user equipments (UEs) on the same time-frequency resources.
Joint Forecasting and Interpolation of Graph Signals Using Deep Learning
We tackle the problem of forecasting network-signal snapshots using past signal measurements acquired by a subset of network nodes.
Task-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
Motivated by these recent developments, in this paper, we perform an indirect design of the communications in a multi-agent system (MAS) in which agents cooperate to maximize the averaged sum of discounted one-stage rewards of a collaborative task.
Joint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems
This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels.
Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatial-Temporal Graph Convolutional Network for Action Recognition
This paper extends the Spatial-Temporal Graph Convolutional Network (ST-GCN) for skeleton-based action recognition by introducing two novel modules, namely, the Graph Vertex Feature Encoder (GVFE) and the Dilated Hierarchical Temporal Convolutional Network (DH-TCN).
Ranked #14 on
Action Recognition
on NTU RGB+D 120
A Family of Deep Learning Architectures for Channel Estimation and Hybrid Beamforming in Multi-Carrier mm-Wave Massive MIMO
Hybrid analog and digital beamforming transceivers are instrumental in addressing the challenge of expensive hardware and high training overheads in the next generation millimeter-wave (mm-Wave) massive MIMO (multiple-input multiple-output) systems.
Bi-objective Framework for Sensor Fusion in RGB-D Multi-View Systems: Applications in Calibration
In this work, we propose a sensor fusion framework based on a weighted bi-objective optimization for refinement of extrinsic calibration tailored for RGB-D multi-view systems.
Inexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization
Interestingly, when the approximation subproblem is solved by a descent algorithm, convergence of a subsequence to a stationary point is still guaranteed even if the approximation subproblem is solved inexactly by terminating the descent algorithm after a finite number of iterations.
Localized Trajectories for 2D and 3D Action Recognition
The Dense Trajectories concept is one of the most successful approaches in action recognition, suitable for scenarios involving a significant amount of motion.
Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations
The proposed framework has several attractive features, namely, i) flexibility, as different choices of the approximate function lead to different type of algorithms; ii) fast convergence, as the problem structure can be better exploited by a proper choice of the approximate function and the stepsize is calculated by the line search; iii) low complexity, as the approximate function is convex and the line search scheme is carried out over a differentiable function; iv) guaranteed convergence to a stationary point.
Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks
The cognitive part of this sequential probing process is the selection of the power levels of the Secondary Users (SUs) which aims to learn the PU interference constraint with a minimum number of probing attempts while setting a limit on the number of harmful probing-induced interference events or equivalently of NACK packet observations over a time window.
Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure
A high signal power is achieved by transmitting the same data signal from all antennas, but with different amplitudes and phases, such that the signal components add coherently at the user.
Information Theory Information Theory
Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments
The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas.
Information Theory Information Theory
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user---the two extremes in data stream allocation.
Information Theory Information Theory
