Search Results for author: Feng Shu

Found 44 papers, 0 papers with code

Machine learning-based Near-field Emitter Localization via Grouped Hybrid Analog and Digital Massive MIMO Receive Array

no code implementations14 Jun 2024 YiFan Li, Feng Shu, Jiatong Bai, Cunhua Pan, Yongpeng Wu, Yaoliang Song, Jiangzhou Wang

In order to meet the future demand for green communication while maintaining high performance, the grouped hybrid analog and digital (HAD) structure is proposed for NF DOA estimation, which divides the large-scale receive array into small-scale groups and each group contains several subarrays.

Clustering Position

Joint Power Allocation and Beamforming Design for Active IRS-Aided Directional Modulation Secure Systems

no code implementations13 Jun 2024 Yifan Zhao, Xiaoyu Wang, Kaibo Zhou, Xuehui Wang, Yan Wang, Wei Gao, Ruiqi Liu, Feng Shu

To meet the requirements of the network performance, a power allocation (PA) strategy is proposed and adopted in the system.

Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning

no code implementations9 Jun 2024 Qiankun Cheng, Jiatong Bai, Baihua Shi, Wei Gao, Feng Shu

We aim to maximize the signal-to-noise ratio of user by jointly designing power allocation (PA) factor, active IRS phase shift matrix, and beamforming vector of BS, subject to a total power constraint.

Co-learning-aided Multi-modal-deep-learning Framework of Passive DOA Estimators for a Heterogeneous Hybrid Massive MIMO Receiver

no code implementations27 Apr 2024 Jiatong Bai, Feng Shu, Qinghe Zheng, Bo Xu, Baihua Shi, YiWen Chen, Weibin Zhang, Xianpeng Wang

To satisfy the three properties, a novel heterogeneous hybrid MIMO receiver structure of integrating FD and heterogeneous HAD ($\rm{H}^2$AD-FD) is proposed and corresponding multi-modal (MD)-learning framework is developed.

Multi-stream Transmission for Directional Modulation Network via Distributed Multi-UAV-aided Multi-active-IRS

no code implementations26 Mar 2024 Ke Yang, Rongen Dong, Wei Gao, Feng Shu, Weiping Shi, Yan Wang, Xuehui Wang, Jiangzhou Wang

In this paper, single large-scale IRS is divided to multiple small IRSs and a novel multi-IRS-aided multi-stream DM network is proposed to achieve a point-to-point multi-stream transmission by creating $K$ ($\geq3$) DoFs, where multiple small IRSs are placed distributively via multiple unmanned aerial vehicles (UAVs).

Large-Scale RIS Enabled Air-Ground Channels: Near-Field Modeling and Analysis

no code implementations19 Mar 2024 Hao Jiang, Wangqi Shi, Zaichen Zhang, Cunhua Pan, Qingqing Wu, Feng Shu, Ruiqi Liu, Jiangzhou Wang

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.

An ADMM-Based Geometric Configuration Optimization in RSSD-Based Source Localization By UAVs with Spread Angle Constraint

no code implementations24 Nov 2023 Xin Cheng, Weiqiang Zhu, Feng Shu, Jiangzhou Wang

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

no code implementations15 Nov 2023 YiFan Li, Feng Shu, Jun Zou, Wei Gao, Yaoliang Song, Jiangzhou Wang

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.

Two Enhanced-rate Power Allocation Strategies for Active IRS-assisted Wireless Network

no code implementations15 Oct 2023 Qiankun Cheng, Rongen Dong, Wenlong Cai, Ruiqi Liu, Feng Shu, Jiangzhou Wang

Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed.

A New Heterogeneous Hybrid Massive MIMO Receiver with An Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning

no code implementations16 Aug 2023 Feng Shu, Baihua Shi, YiWen Chen, Jiatong Bai, YiFan Li, Tingting Liu, Zhu Han, Xiaohu You

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.


Achieving Covert Communication With A Probabilistic Jamming Strategy

no code implementations8 Aug 2023 Xun Chen, Fujun Gao, Min Qiu, Jia Zhang, Feng Shu, Shihao Yan

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.

Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network

no code implementations31 May 2023 Yan Wang, Feng Shu, Zhihong Zhuang, Rongen Dong, Qi Zhang, Di wu, Liang Yang, Jiangzhou Wang

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

no code implementations5 May 2023 Na Yan, Kezhi Wang, Cunhua Pan, Kok Keong Chai, Feng Shu, Jiangzhou Wang

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.

Federated Learning Scheduling

Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy

no code implementations9 Apr 2023 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Feng Shu, Haitao Zhao, Wen Chen, Hongbo Zhu

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.

Federated Learning Scheduling +1

Design of Two-Level Incentive Mechanisms for Hierarchical Federated Learning

no code implementations9 Apr 2023 Shunfeng Chu, Jun Li, Kang Wei, Yuwen Qian, Kunlun Wang, Feng Shu, Wen Chen

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.

Federated Learning Vocal Bursts Valence Prediction

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

no code implementations26 Jan 2023 Yan Lin, Jinming Bao, Yijin Zhang, Jun Li, Feng Shu, Lajos Hanzo

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.

Decision Making Multi-agent Reinforcement Learning +1

Deep-learning-aided Low-complexity DOA Estimators for Ultra-Massive MIMO Overlapped Receive Array

no code implementations15 Jan 2023 YiWen Chen, Xichao Zhan, Feng Shu

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.

Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks

no code implementations7 Jan 2023 Xuehui Wang, Feng Shu, Mengxing Huang, Fuhui Zhou, Riqing Chen, Cunhua Pan, Yongpeng Wu, Jiangzhou Wang

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

no code implementations16 Dec 2022 Yeqing Lin, Feng Shu, Rongen Dong, Riqing Chen, Siling Feng, Weiping Shi, Jing Liu, Jiangzhou Wang

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

no code implementations5 Dec 2022 Feng Shu, Jing Liu, Yeqing Lin, Yang Liu, Zhilin Chen, Xuehui Wang, Rongen Dong, Jiangzhou Wang

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.

Vocal Bursts Intensity Prediction

Enhanced Secure Wireless Transmission Using IRS-aided Directional Modulation

no code implementations29 Sep 2022 Yeqing Lin, Rongen Dong, Peng Zhang, Feng Shu, Jiangzhou Wang

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

no code implementations11 Sep 2022 YiFan Li, Baihua Shi, Feng Shu, Yaoliang Song, Jiangzhou Wang

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.

RIS-Aided Localization Algorithm and Analysis: Tackling Non-Gaussian Angle Estimation Errors

no code implementations16 Aug 2022 Tuo Wu, Hong Ren, Cunhua Pan, Yijin Pan, Sheng Hong, Maged Elkashlan, Feng Shu, Jiangzhou Wang

Reconfigurable intelligent surface (RIS)-aided localization systems are increasingly recognized for enhancing accuracy in internet of things (IoT) networks.

Optimal Measurement of Drone Swarm in RSS-based Passive Localization with Region Constraints

no code implementations2 Aug 2022 Xin Cheng, Feng Shu, YiFan Li, Zhihong Zhuang, Di wu, Jiangzhou Wang

In this paper, optimal geometrical configurations of UAVs in received signal strength (RSS)-based localization under region constraints are investigated.

Providing Location Information at Edge Networks: A Federated Learning-Based Approach

no code implementations17 May 2022 Xin Cheng, Tingting Liu, Feng Shu, Chuan Ma, Jun Li, Jiangzhou Wang

Recently, the development of mobile edge computing has enabled exhilarating edge artificial intelligence (AI) with fast response and low communication cost.

Edge-computing Federated Learning +1

Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array

no code implementations27 Apr 2022 Xichao Zhan, YiWen Chen, Feng Shu, Xin Cheng, Yuanyuan Wu, Qi Zhang, Yifang Li, Peng Zhang

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.

Two Low-complexity DOA Estimators for Massive/Ultra-massive MIMO Receive Array

no code implementations20 Apr 2022 YiWen Chen, Xichao Zhan, Feng Shu, Qijuan Jie, Xin Cheng, Zhihong Zhuang, Jiangzhou Wang

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

no code implementations29 Mar 2022 Xin Cheng, Chuan Ma, Jun Li, Haiwei Song, Feng Shu, Jiangzhou Wang

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.

Federated Learning

Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array

no code implementations2 Mar 2022 YiFan Li, Feng Shu, Jinsong Hu, Shihao Yan, Haiwei Song, Weiqiang Zhu, Da Tian, Yaoliang Song, Jiangzhou Wang

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.


High-performance Passive Eigen-model-based Detectors of Single Emitter Using Massive MIMO Receivers

no code implementations3 Aug 2021 Qijuan Jie, Xichao Zhan, Feng Shu, Yaohui Ding, Baihua Shi, YiFan Li, Jiangzhou Wang

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

no code implementations1 Apr 2021 Xin Cheng, Weiping Shi, Wenlong Cai, Weiqiang Zhu, Tong Shen, Feng Shu, Jiangzhou Wang

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.

UAV Deployment Optimization for Secure Precise Wireless Transmission

no code implementations31 Mar 2021 Tong Shen, Guiyang Xia, Jingjing Ye, Lichuan Gu, Xiaobo Zhou, Feng Shu

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.


Multi-RIS Aided 3D Secure Precise Wireless Transmission

no code implementations23 Nov 2020 Tong Shen, Wenlong Cai, Yan Lin, Shuo Zhang, Jinyong Lin, Feng Shu, Jiangzhou Wang

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

no code implementations3 Nov 2020 YiFan Li, Feng Shu, Baihua Shi, Xin Cheng, Yaoliang Song, Jiangzhou Wang

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

no code implementations1 Nov 2020 Baihua Shi, Nuo Chen, Xicheng Zhu, Yuwen Qian, Yijin Zhang, Feng Shu, Jiangzhou Wang

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

no code implementations17 Aug 2020 Weiping Shi, Jiayu Li, Guiyang Xia, Yuntian Wang, Xiaobo Zhou, Yonghui Zhang, Feng Shu

This paper considers a secure multigroup multicast multiple-input single-output (MISO) communication system aided by an intelligent reflecting surface (IRS).

Vehicle Tracking in Wireless Sensor Networks via Deep Reinforcement Learning

no code implementations22 Feb 2020 Jun Li, Zhichao Xing, Weibin Zhang, Yan Lin, Feng Shu

Vehicle tracking has become one of the key applications of wireless sensor networks (WSNs) in the fields of rescue, surveillance, traffic monitoring, etc.

reinforcement-learning Reinforcement Learning (RL)

UAV-Enabled Confidential Data Collection in Wireless Networks

no code implementations3 Jan 2020 Xiaobo Zhou, Shihao Yan, Min Li, Jun Li, Feng Shu

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.

On Safeguarding Privacy and Security in the Framework of Federated Learning

no code implementations14 Sep 2019 Chuan Ma, Jun Li, Ming Ding, Howard Hao Yang, Feng Shu, Tony Q. S. Quek, H. Vincent Poor

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

Regional Robust Secure Precise Wireless Transmission Design for Multi-user UAV Broadcasting System

no code implementations9 Apr 2019 Tong Shen, Tingting Liu, Yan Lin, Yongpeng Wu, Feng Shu, Zhu Han

Proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location.

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