Search Results for author: Yansha Deng

Found 23 papers, 3 papers with code

Energy-Efficient Cellular-Connected UAV Swarm Control Optimization

no code implementations18 Mar 2023 Yang Su, Hui Zhou, Yansha Deng, Mischa Dohler

To maximize the number of UAVs that receive the message successfully within the latency and energy constraints, we formulate the problem as a Constrained Markov Decision Process to find the optimal policy.

Graph Attention

Federated and Meta learning over Non-Wireless and Wireless Networks: A Tutorial

no code implementations24 Oct 2022 Xiaonan Liu, Yansha Deng, Arumugam Nallanathan, Mehdi Bennis

Typically, FL focuses on learning a global model for a given task and all devices and hence cannot adapt the model to devices with different data distributions.

Decision Making Federated Learning +2

Task-Oriented and Semantics-Aware 6G Networks

no code implementations17 Oct 2022 Hui Zhou, Xiaonan Liu, Yansha Deng, Nikolaos Pappas, Arumugam Nallanathan

In this article, we propose a generic task-oriented and semantics-aware (TOSA) communication framework for various tasks with diverse data types, which incorporates both semantic level information and effectiveness level performance metrics.

Time-triggered Federated Learning over Wireless Networks

no code implementations26 Apr 2022 Xiaokang Zhou, Yansha Deng, Huiyun Xia, Shaochuan Wu, Mehdi Bennis

The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner.

Federated Learning Privacy Preserving

Optimization of Grant-Free NOMA with Multiple Configured-Grants for mURLLC

no code implementations17 Nov 2021 Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis

To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs.

Scalable Multi-agent Reinforcement Learning Algorithm for Wireless Networks

1 code implementation1 Aug 2021 Fenghe Hu, Yansha Deng, A. Hamid Aghvami

This introduces the scalability challenges, while multi-agent reinforcement shows the opportunity to cope this challenges and extend the intelligent algorithm to cooperative large-scale network.

Decision Making Multi-agent Reinforcement Learning +2

Learning-based Prediction, Rendering and Transmission for Interactive Virtual Reality in RIS-Assisted Terahertz Networks

no code implementations27 Jul 2021 Xiaonan Liu, Yansha Deng, Chong Han, Marco Di Renzo

This high data rate over short transmission distances may be achieved via abundant bandwidth in the terahertz (THz) band.


Machine Learning for Massive Industrial Internet of Things

no code implementations10 Mar 2021 Hui Zhou, Changyang She, Yansha Deng, Mischa Dohler, Arumugam Nallanathan

With the deployment of massive IIoT devices, it is difficult for the wireless network to support the ubiquitous connections with diverse quality-of-service (QoS) requirements.

BIG-bench Machine Learning

QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep Reinforcement Learning

no code implementations21 Feb 2021 Liyana Adilla binti Burhanuddin, Xiaonan Liu, Yansha Deng, Ursula Challita, Andras Zahemszky

In this paper, we co-design the video resolution, the movement, and the power control of UAV-BS and UAV-UEs to maximize the Quality of Experience (QoE) of real-time video streaming.

Analyzing Novel Grant-Based and Grant-Free Access Schemes for Small Data Transmission

no code implementations20 Feb 2021 Hui Zhou, Yansha Deng, Luca Feltrin, Andreas Höglund

Motivated by this, 3GPP has proposed 4/2-step SDT RA schemes based on the existing grant-based (4-step) and grant-free (2-step) RA schemes, with the aim to enable data transmission during RA procedures in Radio Resource Control (RRC) Inactive state.

Real-time Video Streaming and Control of Cellular-Connected UAV System: Prototype and Performance Evaluation

no code implementations26 Jan 2021 Hui Zhou, Fenghe Hu, Michal Juras, Asish B Mehta, Yansha Deng

Unmanned aerial vehicles (UAVs) play an increasingly important role in military, public, and civilian applications, where providing connectivity to UAVs is crucial for its real-time control, video streaming, and data collection.

Learning based signal detection for MIMO systems with unknown noise statistics

1 code implementation21 Jan 2021 Ke He, Le He, Lisheng Fan, Yansha Deng, George K. Karagiannidis, Arumugam Nallanathan

Existing detection methods have mainly focused on specific noise models, which are not robust enough with unknown noise statistics.

Learning-based Prediction and Uplink Retransmission for Wireless Virtual Reality (VR) Network

no code implementations16 Dec 2020 Xiaonan Liu, Xinyu Li, Yansha Deng

While for the online learning algorithm, based on the VR user's actual viewpoint delivered through uplink transmission, we compare it with the predicted viewpoint and update the parameters of the online learning algorithm to further improve the prediction accuracy.

RACH in Self-Powered NB-IoT Networks: Energy Availability and Performance Evaluation

no code implementations23 Nov 2020 Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, Jinhong Yuan, Ranjan K. Mallik

In this work, we analyze RACH success probability in a self-powered NB-IoT network taking into account the repeated preamble transmissions and collisions, where each IoT device with data is active when its battery energy is sufficient to support the transmission.

A Vision of XR-aided Teleoperation System Towards 5G/B5G

no code implementations18 Nov 2020 Fenghe Hu, Yansha Deng, Hui Zhou, Tae Hun Jung, Chan-Byoung Chae, A. Hamid Aghvami

Extended Reality (XR)-aided teleoperation has shown its potential in improving operating efficiency in mission-critical, rich-information and complex scenarios.

Correlation-aware Cooperative Multigroup Broadcast 360° Video Delivery Network: A Hierarchical Deep Reinforcement Learning Approach

1 code implementation21 Oct 2020 Fenghe Hu, Yansha Deng, A. Hamid Aghvami

Our proposed learning architectures is effective and scalable for a high-dimensional cooperative association problem with increasing APs and VR users.

Association Reinforcement Learning (RL) +1

Analysis of Random Access in NB-IoT Networks with Three Coverage Enhancement Groups: A Stochastic Geometry Approach

no code implementations14 Sep 2020 Yan Liu, Yansha Deng, Nan Jiang, Maged Elkashlan, Arumugam Nallanathan

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks.

Low-Complexity Robust Beamforming Design for IRS-Aided MISO Systems with Imperfect Channels

no code implementations24 Aug 2020 Yasaman Omid, Seyyed MohammadMahdi Shahabi, Cunhua Pan, Yansha Deng, Arumugam Nallanathan

In this paper, large-scale intelligent reflecting sur-face (IRS)-assisted multiple-input single-output (MISO) system is considered in the presence of channel uncertainty.

Learning-based Prediction, Rendering and Association Optimization for MEC-enabled Wireless Virtual Reality (VR) Network

no code implementations17 May 2020 Xiaonan Liu, Yansha Deng

Wireless-connected Virtual Reality (VR) provides immersive experience for VR users from any-where at anytime.


Analyzing Grant-Free Access for URLLC Service

no code implementations18 Feb 2020 Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis

Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances.

Cellular-Connected Wireless Virtual Reality: Requirements, Challenges, and Solutions

no code implementations13 Jan 2020 Fenghe Hu, Yansha Deng, Walid Saad, Mehdi Bennis, A. Hamid Aghvami

Cellular-connected wireless connectivity provides new opportunities for virtual reality(VR) to offer seamless user experience from anywhere at anytime.

Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing

no code implementations17 Oct 2019 Tong Bai, Cunhua Pan, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, Lajos Hanzo

In this paper, the beneficial role of IRSs is investigated in MEC systems, where single-antenna devices may opt for off-loading a fraction of their computational tasks to the edge computing node via a multi-antenna access point with the aid of an IRS.


Green Deep Reinforcement Learning for Radio Resource Management: Architecture, Algorithm Compression and Challenge

no code implementations11 Oct 2019 Zhiyong Du, Yansha Deng, Weisi Guo, Arumugam Nallanathan, Qihui Wu

To scale learning across geographic areas, a spatial transfer learning scheme is proposed to further promote the learning efficiency of distributed DRL entities by exploiting the traffic demand correlations.

Decision Making Management +3

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