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Found 55 papers, 6 papers with code
Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing
In this scheme, vehicle s mobility, channel conditions with temporal variations, computational resources with temporal variations, different data amount, transmission channel status of vehicles as well as Byzantine attacks were taken into account. Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.
Pseudo MIMO (pMIMO): An Energy and Spectral Efficient MIMO-OFDM System
The proposed system architecture and the dedicated signal processing methods enable the scheme to transmit a bigger number of parallel data streams than the number of receiving RF chains, achieving a spectral efficiency performance close to that of a fully digital (FD) MIMO system with the same number of antenna elements, each equipped with an RF chain.
Employing High-Dimensional RIS Information for RIS-aided Localization Systems
Then, we propose a transfer learning based fingerprint (TFBF) algorithm that employs the reconstructed high-dimensional RIS information for MU localization.
Deep Learning-Based CSI Feedback for RIS-Aided Massive MIMO Systems with Time Correlation
We use long short-term memory to learn time correlation, which can help the neural network to improve the recovery quality of the compressed CSI.
Large-Scale RIS Enabled Air-Ground Channels: Near-Field Modeling and Analysis
Then, we develop a beam domain channel model based on the proposed sub-array partition framework for large-scale RIS-enabled UAV-to-vehicle communication systems, which can be used to efficiently capture the sparse features in RIS-enabled UAV-to-vehicle channels in both near-field and far-field ranges.
Blockchain-Enabled Variational Information Bottleneck for IoT Networks
In Internet of Things (IoT) networks, the amount of data sensed by user devices may be huge, resulting in the serious network congestion.
Target Localization and Performance Trade-Offs in Cooperative ISAC Systems: A Scheme Based on 5G NR OFDM Signals
Specifically, we propose a two-stage scheme for target localization, where communication signals are reused as sensing reference signals based on the system information shared at the central processing unit (CPU).
Energy-Efficient Clustered Cell-Free Networking with Access Point Selection
Ultra-densely deploying access points (APs) to support the increasing data traffic would significantly escalate the cell-edge problem resulting from traditional cellular networks.
Reconfigurable Intelligent Surface assisted Integrated Communication, Sensing, and Computation Systems
To address the formulated non-convex problem, we propose an algorithm based on the block coordinate descent (BCD) method to decouple the original problem into two subproblems, where the computational and beamforming settings are optimized alternately.
Beamforming Optimization for Active RIS-Aided Multiuser Communications With Hardware Impairments
Specifically, by exploiting the majorization-minimization approach, each subproblem is reformulated into a tractable surrogate problem, whose closed-form solutions are obtained by Lagrange dual decomposition approach and element-wise alternating sequential optimization method.
Spectral Efficiency Maximization for Active RIS-aided Cell-Free Massive MIMO Systems with Imperfect CSI
A cell-free network merged with active reconfigurable reflecting surfaces (RIS) is investigated in this paper.
URLLC-Awared Resource Allocation for Heterogeneous Vehicular Edge Computing
Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing.
An ADMM-Based Geometric Configuration Optimization in RSSD-Based Source Localization By UAVs with Spread Angle Constraint
Deploying multiple unmanned aerial vehicles (UAVs) to locate a signal-emitting source covers a wide range of military and civilian applications like rescue and target tracking.
A Novel Tree Model-based DNN to Achieve a High-Resolution DOA Estimation via Massive MIMO receive array
To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly increase the number of output classifications and also produce a huge high model complexity.
High-performance Power Allocation Strategies for Active IRS-aided Wireless Network
Due to its slow linear convergence from iterative GA, the proposed ESMPI-GA is high-complexity.
Two Enhanced-rate Power Allocation Strategies for Active IRS-assisted Wireless Network
Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed.
Dynamic Sub-array Based Modeling for Large-Scale RIS-assisted mmWave UAV Channels
Large-scale reconfigurable intelligent surface (RIS) can effectively enhance the performance of millimeter wave (mmWave) unmanned aerial vehicle (UAV) to ground communication link with obstructed line-of-sight (LoS) path by exploiting more reflecting units.
Energy Minimization for Active RIS-Aided UAV-Enabled SWIPT Systems
In this paper, we consider an active reconfigurable intelligent surface (RIS)-aided unmanned aerial vehicle(UAV)-enabled simultaneous wireless information and power transfer(SWIPT) system with multiple ground users.
Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network
Numerical simulation results show that a 3-bit discrete phase shifter is required to achieve a trivial performance loss for a large-scale active IRS.
Over-the-Air Federated Averaging with Limited Power and Privacy Budgets
We aim to improve the learning performance by jointly designing the device scheduling, alignment coefficient, and the number of aggregation rounds of federated averaging (FedAvg) subject to sum power and privacy constraints.
Deep Reinforcement Learning Based Power Allocation for Minimizing AoI and Energy Consumption in MIMO-NOMA IoT Systems
It is critical to determine the optimal policy including sample collection requirements and power allocation to minimize the AoI and energy consumption of MIMO-NOMA IoT system, where the transmission rate is not a constant in the SIC process and the noise is stochastic in the MIMO-NOMA channel.
Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks
Moreover, it is verified that the proposed HP-SDR-FP method perform better than WF-GPI-GRR method in terms of rate performance.
Enhanced-rate Iterative Beamformers for Active IRS-assisted Wireless Communications
In this paper, in order to boost the achievable rate of user in such a wireless network, three enhanced-rate iterative beamforming methods are proposed by designing the amplifying factors and the corresponding phases at active IRS.
Three High-rate Beamforming Methods for Active IRS-aided Wireless Network
To fully exploit the amplifying gain achieved by active IRS, two high-rate methods, maximum ratio reflecting (MRR) and selective ratio reflecting (SRR) are presented, which are motivated by maximum ratio combining and selective ratio combining.
Channel Tracking for RIS-aided mmWave Communications Under High Mobility Scenarios
The emerging reconfigurable intelligent surface (RIS) technology is promising for applications in the millimeter wave (mmWave) communication systems to effectively compensate for propagation loss or tackle the blockage issue.
Two-Timescale Transmission Design for RIS-Aided Cell-Free Massive MIMO Systems
Finally, the numerical results demonstrate the correctness of our derived expressions and the benefits of deploying large-size RISs into cell-free mMIMO systems.
Enhanced Secure Wireless Transmission Using IRS-aided Directional Modulation
To reduce the computational complexity, a new method of maximizing receive power with zero-forcing constraint (Max-RP-ZFC) of only reflecting CM and no AN is proposed.
Deep Learning Based DOA Estimation for Hybrid Massive MIMO Receive Array with Overlapped Subarrays
To improve the accuracy of direction-of-arrival (DOA) estimation, a deep learning (DL)-based method called CDAE-DNN is proposed for hybrid analog and digital (HAD) massive MIMO receive array with overlapped subarray (OSA) architecture in this paper.
Active Reconfigurable Intelligent Surface for Mobile Edge Computing
This paper investigates an active reconfigurable intelligent surface (RIS)-aided mobile edge computing (MEC) system.
Statistical CSI-based Beamforming for RIS-Aided Multiuser MISO Systems using Deep Reinforcement Learning
The paper presents a joint beamforming algorithm using statistical channel state information (S-CSI) for reconfigurable intelligent surfaces (RIS) for multiuser MISO wireless communications.
RIS-Aided Near-Field Localization and Channel Estimation for the Sub-Terahertz System
This makes localization and channel estimation in the near field of the RIS-aided subTHz system more challenging.
Joint Angle Estimation Error Analysis and 3D Positioning Algorithm Design for mmWave Positioning System
Then, we derive a complex expression for the variance based on the derived PDF.
RIS-Aided Localization Algorithm and Analysis: Tackling Non-Gaussian Angle Estimation Errors
Reconfigurable intelligent surface (RIS)-aided localization systems are increasingly recognized for enhancing accuracy in internet of things (IoT) networks.
Asynchronous Federated Learning for Edge-assisted Vehicular Networks
For the traditional federated learning (FL), vehicles train the data locally to obtain a local model and then upload the local model to the RSU to update the global model, thus the data privacy can be protected through sharing model parameters instead of data.
Optimal Measurement of Drone Swarm in RSS-based Passive Localization with Region Constraints
In this paper, optimal geometrical configurations of UAVs in received signal strength (RSS)-based localization under region constraints are investigated.
Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning
In addition, we consider the mobility of vehicles and propose a deep reinforcement learning algorithm to obtain the optimal cooperative caching location for the predicted popular contents in order to optimize the content transmission delay.
An IRS Backscatter Enabled Integrated Sensing, Communication and Computation System
This paper proposes to leverage intelligent reflecting surface (IRS) backscatter to realize radio-frequency-chain-free uplink-transmissions (RFCF-UT).
Providing Location Information at Edge Networks: A Federated Learning-Based Approach
Recently, the development of mobile edge computing has enabled exhilarating edge artificial intelligence (AI) with fast response and low communication cost.
Two Low-complexity DOA Estimators for Massive/Ultra-massive MIMO Receive Array
Eigen-decomposition-based direction finding methods of using large-scale/ultra-large-scale fully-digital receive antenna arrays lead to a high or ultra-high complexity.
Federated Learning-Based Localization with Heterogeneous Fingerprint Database
Fingerprint-based localization plays an important role in indoor location-based services, where the position information is usually collected in distributed clients and gathered in a centralized server.
Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array
The simulation results show that the machine learning-based methods can achieve good results in signal classification, especially neural networks, which can always maintain the classification accuracy above 70\% with massive MIMO receive array.
RIS-Aided D2D Communications Relying on Statistical CSI with Imperfect Hardware
In this letter, we investigate a reconfigurable intelligent surfaces (RIS)-aided device to device (D2D) communication system over Rician fading channels with imperfect hardware including both hardware impairment at the transceivers and phase noise at the RISs.
High-performance Passive Eigen-model-based Detectors of Single Emitter Using Massive MIMO Receivers
The test statistic (TS) of the first method is defined as the ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV) while that of the second one is defined as the ratio of Max-EV to noise variance (R-MaxEV-NV).
Communication-efficient Coordinated RSS-based Distributed Passive Localization via Drone Cluster
Simulation results show that the proposed DMM performs better than the existing distributed Gauss-Newton method (DGN) in terms of root of mean square error (RMSE) under a limited low communication overhead constraint.
Self-Sustainable Reconfigurable Intelligent Surface Aided Simultaneous Terahertz Information and Power Transfer (STIPT)
This paper proposes a new simultaneous terahertz (THz) information and power transfer (STIPT) system, which is assisted by reconfigurable intelligent surface (RIS) for both the information data and power transmission.
Performance Comparison between Reconfigurable Intelligent Surface and Relays: Theoretical Methods and a Perspective from Operator
On the other hand, a relay node in a traditional relay network has to be active, which indicates that it will consume energy when it is relaying the signal or information between the source and destination nodes.
Information Theory Information Theory
Multi-RIS Aided 3D Secure Precise Wireless Transmission
Then, multiple RISs are utilized to achieve SPWT through the reflection path among transmitter, RISs and receivers in order to enhance the communication performance and energy efficiency simultaneously.
Reconfigurable Intelligent Surfaces for 6G Systems: Principles, Applications, and Research Directions
Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs), are regarded as one of the most promising and revolutionizing techniques for enhancing the spectrum and/or energy efficiency of wireless systems.
Time-dependent Performance Analysis of the 802.11p-based Platooning Communications Under Disturbance
However, one vehicle in platoons inevitably suffers from a disturbance resulting from the leader vehicle acceleration/deceleration, wind gust and uncertainties in a platoon control system, i. e., aerodynamics drag and rolling resistance moment etc.
Networking and Internet Architecture
Enhanced RSS-based UAV Localization via Trajectory and Multi-base Stations
First, fixing the nth BS, by exploiting multiple measurements along trajectory, the position of UAV is computed by ML rule.
Impact of Low-Resolution ADC on DOA Estimation Performance for Massive MIMO Receive Array
In this paper, we present a new scenario of direction of arrival (DOA) estimation using massive multiple-input multiple-output (MIMO) receive array with low-resolution analog-to-digital convertors (ADCs), which can strike a good balance between performance and circuit cost.
Information Theory Signal Processing Information Theory
Fast Network Community Detection with Profile-Pseudo Likelihood Methods
In this article, we propose a novel likelihood based approach that decouples row and column labels in the likelihood function, which enables a fast alternating maximization; the new method is computationally efficient, performs well for both small and large scale networks, and has provable convergence guarantee.
UAV-Assisted and Intelligent Reflecting Surfaces-Supported Terahertz Communications
In this paper, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications.
A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Moreover, optimal or near-optimal solutions of historical scenarios can be searched offline and stored in advance.
On Consideration of Content Preference and Sharing Willingness in D2D Assisted Offloading
Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem.
Networking and Internet Architecture
