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Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road networks

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China Communications 2022年第4期19卷 274-290页

作者： Tongyu Zhao Yaqiong Liu Guochu Shou Xinwei Yao School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and ConvergenceBeijing 100876China School of Computer Science and Technology Zhejiang University of TechnologyChina

In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual scene,which results in high latency and energy consumption. Therefore, it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption. In this article, we aim at finding a tradeoff between latency and energy consumption. We formalize the computation offloading problem base on mobile edge computing(MEC)into a constrained multiobjective optimization problem(CMOP) and utilize NSGA-II to solve it. The simulation results demonstrate that NSGA-II can find the Pareto set, which reduces the latency and energy consumption effectively. In addition, a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the actual situation.

关键词： proximity detection mobile edge computing road networks constrained multiobjective optimization

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A multipath-assisted localization algorithm under 5G-based opensource testbed 9

A multipath-assisted localization algorithm under 5G-based o...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Lu, Yuye Zheng, Wei Chu, Xinghe Lu, Zhaoming Hu, Ruoqian Li, Meiling Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)9798350317251

Indoor localization services are playing an important role in a variety of emerging industries. Traditional positioning methods suffer from insufficient accuracy or high deployment costs in indoor environments, and with the rapid development of cellular mobile communication systems, positioning under cellular networks has been more widely used due to its low cost and easy deployment. In the indoor environment, the number of available base stations is limited, and positioning by direct radius information provided by only one base station suffers from insufficient accuracy. In this paper, we designed a method for indoor localization based on cellular networks, which considering the localization information carried by the multi-path, to verify the performance of this algorithm in practical scene. We implement this algorithm in a 5G-based testbed based on software-defined radio (SDR) technologies. The results show that our algorithm can meet the requirements of indoor cases defined in 3GPP 38.855. © 2023 IEEE.

关键词： Testbeds

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User Selection and Resource Allocation for Satellite-Based Multi-task Federated Learning system 4th

User Selection and Resource Allocation for Satellite-Based M...

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4th International Conference on Artificial Intelligence in China, AIC 2022

作者： Zhang, Mingyu Wu, Xiaoyong Zhang, Zhilong Liu, Danpu Yin, Fangfang Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China Shanghai Radio Equipment Research Institute Shanghai201109 China State Key Laboratory of Media Convergence and Communication School of Information and Communication Communication University of China Beijing100024 China

ISBN: (纸本)9789819912551

In view of the development of low-orbit satellite constellation and the increasing demand for computing ability and privacy protection of space-based applications, a satellite-based multi-task federated learning system is designed. Specifically, with consideration of both the fluctuations of satellite-to-ground communication links and local training impacts on global models, a user selection strategy is established. On this basis, the functional relationship between task convergence speed and wireless communication factors is analyzed, and the KM optimal matching algorithm is adopted to dynamically allocate communication resources. Simulation results show that our proposed scheme outperforms baseline methods in both total weighted error rate and accuracy, and achieves the fastest convergence rate at the same time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Satellites

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Joint Source-Channel Coding for Efficient Image Transmission: An Information Bottleneck Based Scheme

Joint Source-Channel Coding for Efficient Image Transmission...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Sun, Lunan Guo, Caili Yang, Yang Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9781665459754

Joint source-channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing research mainly focuses on minimizing the distortion between the transmitted and received information while neglecting the required data rate. Therefore, the transmitted data rate may be far more than the minimal required threshold according to the rate-distortion (RD) theory even though the transmitted information can be well recovered. In this paper, we propose an Information Bottleneck (IB) based JSCC (IB-JSCC), which aims at reducing the required data rate as much as possible while increasing the reconstruction quality. In particular, we establish a new IB objective for unsupervised image transmission JSCC system, which simultaneously minimizes the distortion and the required data rate. We derive a mathematically tractable lower bound on the proposed objective and use the bound as the loss function of IB-JSCC. Experimental results show that IB-JSCC can significantly reduce the required amount of the transmitted data and improve the reconstruction quality and downstream artificial-intelligent tasks accuracy. © 2022 IEEE.

关键词： Electric distortion

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Image Semantic Communications: An Extended Rate-Distortion Theory Based Scheme

Image Semantic Communications: An Extended Rate-Distortion T...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Tong, Wanjie Liu, Fangfang Sun, Zhengfen Yang, Yang Guo, Caili Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9781665459754

Semantic communication is a promising paradigm for future artificial intelligence-empowered communications. In this paper, we propose a task-oriented semantic communications with semantic reconstruction (TOSC-SR) scheme for image semantic communications. Different from existing studies focusing on minimizing the pixel-level or feature-level distortion of images, TOSC-SR aims to preserve the semantic information of the image so as to ensure the performance of downstream artificial intelligence (AI) tasks. To this end, a new form of rate-distortion is first derived, which takes the semantic information related to AI tasks into consideration. We formulate TOSC-SR as an extended rate-distortion optimization problem. Then we propose a joint source and channel coding (JSCC) based semantic communication system, which are followed by multiple AI tasks. Experimental results show that the proposed approach outperforms the traditional JPEG, JPEG2000-based communication system and deep learning based multi-task communication system in terms of image reconstruction quality, AI task performance, and multi-task generalization ability. © 2022 IEEE.

关键词： Semantics

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Deep Learning-Based Mobile User Localization with Reconfigurable Intelligent Surface

Deep Learning-Based Mobile User Localization with Reconfigur...

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IEEE Conference on Wireless Communications and networking

作者： Chenpan He Zhenghe Zhu Yawen Chen Wei Zheng Zhaoming Lu Xiangming Wen Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Reconfigurable intelligent surface (RIS) is a promising technique for positioning systems. A large number of reference signals is needed for traditional base station (BS) with RIS localization system which occupy communication resources. To solve this problem, we directly use the DMRS (Demodulation Reference Signal), which does not consume additional communication resources to estimate the user equipment (UE) position. In this paper, we consider a RIS-assisted downlink localization system that takes account for the channel time variability caused by UE mobility. To estimate the UE position, DPSCN (Depthwise Separable Convolution) network consisting of three stages is adopted to capture the relationship between the received signal and the UE *** on the estimated position, the RIS phase is dynamically adjusted, to achieve accurate and continuous tracking of the UE. Extensive simulation results are also presented to demonstrate that the proposed DPSCN learning algorithm can estimate the UE position accurately and outperforms the traditional algorithms.

关键词： Location awareness Accuracy Convolution Simulation Heuristic algorithms Neural networks Reconfigurable intelligent surfaces Prediction algorithms Downlink Demodulation

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Demo: A Hybrid Semantic RAN Protocol Stack Design for 6G system and its Implementation

Demo: A Hybrid Semantic RAN Protocol Stack Design for 6G Sys...

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IEEE Conference on Wireless Communications and networking

作者： Luhan Wang Haiwen Niu Zhaoming Lu Xiangming Wen Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Recently, Semantic Communication (SC) has been recognized as a crucial new paradigm in 6G, significantly improving information transmission efficiency. However, the diverse range of service types in 6G networks, such as high-data-volume services like AR/VR/MR and low-data-volume applications requiring high accuracy, such as industrial control and data collection, presents significant challenges to fully replacing the fundamental technologies with SC. Therefore, we design a Hybrid Semantic Communication Ratio Access network (HSC-RAN) protocol stack demo for 6G systems to achieve compatibility and smooth transition between SC and non-SC. Specifically, we take the Physical Downlink Shared Channel (PDSCH) as an example, to efficiently integrate SC with Orthogonal Frequency Division Multiplexing (OFDM). Furthermore, we introduce a novel Downlink Control Information (DCI) format that jointly supports SC and non-SC, enabling real-time video transmission via SC and text transmission through non-SC. Experimental results demonstrate that our approach allows simultaneous transmission of semantic and non-semantic information while maintaining high-quality reconstruction at the receiver.

关键词： 6G mobile communication Wireless communication Protocols OFDM Receivers Streaming media Downlink Semantic communication Real-time systems Next generation networking

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A Neural-Based OTFS Channel Estimator

A Neural-Based OTFS Channel Estimator

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IEEE Conference on Wireless Communications and networking

作者： Zhenghe Zhu Yawen Chen Zhaoming Lu Xiangming Wen Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

orthogonal time frequency space (OTFS) systems are considered as the reliable solution for addressing the challenges of high mobility in sixth generation (6G) scenarios. By modulating data across both the delay and Doppler dimensions, OTFS efficiently handles the double spread problems caused by high mobility. Accurate and efficient channel estimation is essential for ensuring reliable data reception in OTFS systems. In this paper, we propose a convolutional neural network (CNN) based channel estimator within the standard OTFS transceiver framework to estimate the transmitted channel from the received OTFS signal. Simulation results demonstrate that our neural channel estimator achieves superior channel reconstruction and outperforms existing neural-based methods. Moreover, we analyze its performance with higher-order modulation and show that it effectively supports such modulation under good channel conditions, improving spectral efficiency and throughput.

关键词： 6G mobile communication Time-frequency analysis Spectral efficiency Simulation Channel estimation Modulation Transceivers Reliability Convolutional neural networks Standards

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Joint Optimization of VNF Reusing and Routing in Satellite networks

Joint Optimization of VNF Reusing and Routing in Satellite N...

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IEEE Conference on Wireless Communications and networking

作者： Weixin Yan Zhilong Zhang Danpu Liu Tao Luo Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Low-earth orbit (LEO) satellite networks has attracted a lot of attention, since it is able to provide high-quality services worldwide. With the assistance of NFV technology, the flexibility and the quality of service (QoS) of LEO satellite networks can be further improved. However, most existing researches have not considered virtual network functions (VNFs) reusing during the process of service function chain (SFC) placement in NFV-enabled satellite networks. In this paper, we investigate the problem of SFC placement, and propose a joint VNF reusing and routing algorithm. By considering both of the initialization delay and sharing of VNFs, the service deployment delay can be effectively reduced, and the network profit can be largely improved. In our setting, simulation results show that our proposed algorithm outperforms baseline algorithms in profit, with an improvement of at least 23 %.

关键词： Satellites Service function chaining Simulation Low earth orbit satellites Quality of service Routing Orbits Delays Resource management Optimization

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Semi-SemNet: A Evolved Servitization network architecture from 5G to Semantic Communication

Semi-SemNet: A Evolved Servitization Network Architecture fr...

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IEEE Conference on Wireless Communications and networking

作者： Haiwen Niu Luhan Wang Zhaoming Lu Xiangming Wen Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Recently, a new communication paradigm, semantic communication, has garnered significant attention due to its superior information transmission efficiency compared to conventional communication. However, current research on semantic communication primarily focuses on the design of end-to-end communication systems from the perspective of goal orientation or information reconstruction, without considering integration with the evolving technological landscape of the 5th generation mobile communication (5G) networks. To address this gap, in this paper, we propose an evolved servitization network architecture, called Semi-SemNet, which provides goal-level semantic service capability for the proposed converged goal-oriented semantic communication. To enable dynamic semantic-aware load balancing, the contexts of network functions (NFs) are decoupled from themselves and managed by a common NF, rendering each NF stateless. Additionally, we present an overview of enhanced NFs and system procedures for semantic communications. To meet different target nodes, such as application servers and user equipment (UE), we introduce a semantic translation mechanism to eliminate performance degradation when there are multiple independent wireless links between the source node and the target node. Finally, we use fire video remote monitoring as a case study. Experimental results show that Semi-SemNet achieves an average 26.67% PSNR and 27.21% MS-SSIM performance improvement in information reconstruction, and saves 40.51% bandwidth resources in goal execution. Moreover, with the stateless mechanism and semantic-aware load balancing decisions, it can reduce semantic data transmission delay by an average of 60.59% compared to the benchmark methods. The all code and original data of this paper are publicly available at https://***/hwniu/sbi_semantic_***.

关键词： Wireless communication Translation 5G mobile communication network architecture Semantic communication Load management Rendering (computer graphics) Noise measurement Servers Remote monitoring

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