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Found 39 papers, 0 papers with code
On Safeguarding Privacy and Security in the Framework of Federated Learning
Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) paradigm has emerged, namely federated learning (FL).
Networking and Internet Architecture
Vehicle Tracking in Wireless Sensor Networks via Deep Reinforcement Learning
Vehicle tracking has become one of the key applications of wireless sensor networks (WSNs) in the fields of rescue, surveillance, traffic monitoring, etc.
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
Secure Multigroup Multicast Communication Systems via Intelligent Reflecting Surface
This paper considers a secure multigroup multicast multiple-input single-output (MISO) communication system aided by an intelligent reflecting surface (IRS).
UAV Deployment Optimization for Secure Precise Wireless Transmission
This paper develops an unmanned aerial vehicle (UAV) deployment scheme in the context of the directional modulation-based secure precise wireless transmissions (SPWTs), where the optimal UAV position for the SPWT is derived to maximum the secrecy rate (SR) without injecting any artificial noise (AN) signaling.
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.
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.
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.
Regional Robust Secure Precise Wireless Transmission Design for Multi-user UAV Broadcasting System
Proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location.
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).
UAV-Enabled Confidential Data Collection in Wireless Networks
This work, for the first time, considers confidential data collection in the context of unmanned aerial vehicle (UAV) wireless networks, where the scheduled ground sensor node (SN) intends to transmit confidential information to the UAV without being intercepted by other unscheduled ground SNs.
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.
Collaborative Intelligent Reflecting Surface Networks with Multi-Agent Reinforcement Learning
Intelligent reflecting surface (IRS) is envisioned to be widely applied in future wireless networks.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
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.
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.
Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array
In the proposed Max-RP-QI, a quadratic interpolation scheme is adopted to interpolate the three DOA values corresponding to the largest three receive powers of Max-RP.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Deep-learning-aided Low-complexity DOA Estimators for Ultra-Massive MIMO Overlapped Receive Array
Massive multiple input multiple output(MIMO)-based fully-digital receive antenna arrays bring huge amount of complexity to both traditional direction of arrival(DOA) estimation algorithms and neural network training, which is difficult to satisfy high-precision and low-latency applications in future wireless communications.
Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning
Proactive edge association is capable of improving wireless connectivity at the cost of increased handover (HO) frequency and energy consumption, while relying on a large amount of private information sharing required for decision making.
Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV network
It is not able to estimate angle noise but has lower computational complexity.
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy
Specifically, we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client's local training, thereby mitigating the performance degradation induced by DP and and reducing the number of transmission parameters over wireless channels.
Design of Two-Level Incentive Mechanisms for Hierarchical Federated Learning
In this paper, we design two-level incentive mechanisms for the HFL with a two-tiered computing structure to encourage the participation of entities in each tier in the HFL training.
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.
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.
Achieving Covert Communication With A Probabilistic Jamming Strategy
In addition, we prove that the minimum jamming power should be the same as Alice's covert transmit power, depending on the covertness and average jamming power constraints.
A New Heterogeneous Hybrid Massive MIMO Receiver with An Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning
To address this problem, a new heterogeneous sub-connected hybrid analog and digital (HAD) MIMO structure is proposed with an intrinsic ability of removing phase ambiguity and a corresponding new framework is developed to implement a rapid high-precision DOA estimation using only single time-slot.
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.
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.
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.
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.
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.
