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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Jian Zhao Tao Wang Haonan Tong Xinxin He Changchuan Yin Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications P. R. China

This paper studies a deadline-aware hybrid retransmission scheme for an Industrial Internet of Things (IIoT) system over the 5th generation and Time-Sensitive networking (5G-TSN) system. In the considered model, multiple devices must transmit time-sensitive data flows to an edge server for real-time computing and industrial control. These scenarios require the 5G-TSN technique to realize deterministic transmission, which must complete the data transmission before the specified deadline while maintaining ultra-high reliability. Since the uncertainty of the wireless channel in 5G-TSN affects the transmission reliability, hybrid automatic repeat request (HARQ) technology is introduced to improve the transmission success probability. However, two existing mainstream HARQ negative acknowledgment-based (NACK-based) and blind schemes lead to a huge delay penalty and drain spectrum resources, respectively. These drawbacks make it challenging to meet multiple devices’ diverse quality of service (QoS) requirements. To address this issue, a deadline-aware hybrid HARQ scheme that combines NACK and blind retransmission schemes is proposed to maximize the number of successfully transmitted deterministic data flows over the 5G-TSN. Specifically, we first propose the delay and reliability models for our considered 5G-TSN IIoT system. Subsequently, our proposed scheme is introduced in detail. The simulation results demonstrate that the proposed scheme can increase the number of deterministic transmission flows by 170.52% and 27.98% with 100 devices compared to 1) single NACK-based and 2) traditional hybrid HARQ schemes.

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Deep Joint Source-Channel Coding for Wireless Image Transmission with Semantic Importance

arXiv

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arXiv 2023年

作者： Sun, Qizheng Guo, Caili Yang, Yang Chen, Jiujiu Tang, Rui Liu, Chuanhong Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing100876 China

The sixth-generation mobile communication system proposes the vision of smart interconnection of everything, which requires accomplishing communication tasks while ensuring the performance of intelligent tasks. A joint source-channel coding method based on semantic importance is proposed, which aims at preserving semantic information during wireless image transmission and thereby boosting the performance of intelligent tasks for images at the receiver. Specifically, we first propose semantic importance weight calculation method, which is based on the gradient of intelligent task’s perception results with respect to the features. Then, we design the semantic loss function in the way of using semantic weights to weight the features. Finally, we train the deep joint source-channel coding network using the semantic loss function. Experiment results demonstrate that the proposed method achieves up to 57.7% and 9.1% improvement in terms of intelligent task’s performance compared with the source-channel separation coding method and the deep source-channel joint coding method without considering semantics at the same compression rate and signal-to-noise ratio, respectively. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Spatial-Temporal Alignment via Optimal Transport for Video-Text Retrieval

Spatial-Temporal Alignment via Optimal Transport for Video-T...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Feng, Zerun Zeng, Zhimin Guo, Caili Li, Zheng Zhang, Yufeng School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China China Telecom Dict Application Capability Center China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Video-text retrieval is one of the most popular branches in the cross-modal research area facing the exponential growth of multimedia services. Present methods typically mea-sure cross-modal similarities only by the cosine metric in a common space. However, this function ignores the in-herent discrepancy between videos and texts for reflecting spatial-temporal contents and fails to align them under the weakly supervised setting. To address this issue, we propose a novel Spatial-Temporal Optimal Transport (STOT) frame-work building upon advances in optimal transport. The spatial and temporal characteristics of videos and texts are carefully considered in STOT and associated by calculating a spatial-temporal alignment distance, which can be implemented as a regularizer for existing models to improve retrieval accu-racy. Extensive experiments are conducted on two video-text datasets with two models as base architectures to demonstrate the outperformance of our framework due to the powerful spatial-temporal alignment capability. © 2022 IEEE.

关键词： Multimedia services

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Multi-Task Semantic Communications: An Extended Rate-Distortion Theory Based Scheme

Multi-Task Semantic Communications: An Extended Rate-Distort...

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IEEE International Conference on Communications Workshops, ICC

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

Semantic communication is a new communication paradigm, which aims at transmitting semantic symbols for artificial intelligence (AI) tasks. When there are multiple target AI tasks, existing studies typically require extracting and transmitting dedicated semantics for each AI task. Considering the fact that each AI task may share common semantics, this paper proposes a joint source-channel coding scheme for multi-task semantic communication systems, which can extract the common semantics required by multiple AI tasks, so that the overall transmitted semantics can be reduced. To this end, we first formulate the multi-task semantic communication problem as an rate-distortion problem, which simultaneously takes the rate of the extracted semantics and the distortion of multiple AI tasks into consideration. Then, we derive a new form of rate-distortion, coined as extended rate-distortion, which can guide the extraction of the compact semantics of multiple AI tasks simultaneously. To guarantee the appropriate trade-off between the rate and distortion of multiple AI tasks, we further propose a rate adjustment module that can dynamically adjust the rate according to channel conditions. Experimental results show that the proposed method can achieve 7.6% multi-task performance gain with 40% reduction in transmission overhead compared with existing single-task oriented communication systems.

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Enhanced Precision Time Synchronization with Measurement and Compensation in TSN

Enhanced Precision Time Synchronization with Measurement and...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Chenlong Yao Guochu Shou Boyang Niu Xiaodong Zhang Hongxing Li Yaqiong Liu Yihong Hu Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Time synchronization is a key technology in time-sensitive networking (TSN) to support deterministic data transmission with bounded latency, low delay jitter, and zero congestion loss guarantee. TSN uses IEEE 802. IAS protocol to achieve time synchronization. The asymmetry of the propagation link, clock drift, and limited node clock frequency resolution limit the TSN time synchronization performance improvement. In this paper, we propose a scheme for enhancing the time synchronization performance of TSN and design a method to enhance the TSN time synchronization accuracy by precisely measuring the deviation of the start frame delimiter (SFD) identification signal of the frame initiator from the local received clock signal, and taking the measured value as the compensation amount. Furthermore, we introduce a time correction algorithm in the compensation process. The corresponding development implementation is completed in FPGA, and a test environment is constructed for experimental verification. The experimental results obtain a time synchronization accuracy of 7.5ns, and the synchronization accuracy is even better than 5ns after introducing the time correction algorithm.

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Delay-bounded Topology Construction and Routing Integration for Time-critical Services

Delay-bounded Topology Construction and Routing Integration ...

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IEEE Symposium on network Operations and Management

作者： Xiaofu Huang Guochu Shou Yaqiong Liu Zehua Gao Yihong Hu Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Applications such as virtual/augmented reality, autonomous systems, and telemedicine require delay-bounded transmission. This paper combines the software-defined network (SDN) paradigm and proposes an integrated solution for topology construction and routing (TCR). First, the solution gives a delaybounded constraint for adding valid links, which can be adapted to various topology construction methods. Then, topology discovery, resource management, flow management, and route selection are performed in the orchestration and configuration plane. TCR enables time-sensitive network management and configuration with flexibility. The performance of the TCR is evaluated in a typical industrial network topology. The experimental results show that the TCR can effectively reduce the average path length (APL), guarantee bounded delay, and is beneficial for load balancing.

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An edge caching strategy based on separated learning of user preference and content popularity

An edge caching strategy based on separated learning of user...

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2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

作者： Chen, Guanpeng Jing, Wenpeng Wen, Xiangming Lu, Zhaoming Zhao, Shuyue Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing China

ISBN: (纸本)9781665443852

Mobile edge caching has recently been proposed as a promising technique to efficiently relieve traffic burden by storing contents in the mobile edge server, or even the base station (BS). However, it remains a challenging problem that how to select the appropriate content considering the limited users and cache capacity of a BS. Motivated by the advance for mining the preference of users in the recommendation system, we propose a proactive edge caching strategy which is based on a novel user preference prediction model called Neural Collaborative Filtering without Content Popularity (N CFCP). Since content popularity and personal preference have different laws of change, our proposed strategy attempts to separate them to improve the accuracy of prediction for user preference. An optimization problem is formulated to maximize the cache hit ratio and is decomposed into two subproblems, i.e., the individual preference prediction and content placement. For individual preference prediction, we design the novel NCFCP method, which can model the relationship between users and contents more precisely. For content placement, we develop a caching mechanism based on the group preference where user activity is considered. Performance evaluation over a real-world dataset shows that the proposed algorithm outperforms baseline algorithms in terms of the cache hit ratio and users' satisfaction by 18% and 20% on average, respectively. © 2021 IEEE.

关键词： Forecasting

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Genetic-Based Cluster Routing Algorithm for Wireless Sensor networks 7

Genetic-Based Cluster Routing Algorithm for Wireless Sensor ...

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7th International Conference on Computer and Communications, ICCC 2021

作者： Guo, Jin Wu, Muqing Beijing University of Posts and Telecommunication Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

ISBN: (纸本)9781665409506

Wireless sensor networks consist of numerous sensor nodes with limited energy. Since wireless sensor networks are primarily deployed in complex environments, it is difficult to charge or replace nodes. So, a primary concern of wireless sensor networks is the efficient use of node energy. In this research, we propose a genetic-based cluster routing algorithm. The algorithm uses the distance to the base station and the remaining energy to select the appropriate cluster heads. Besides, it uses the genetic algorithm to find the optimal transmission paths with load balance and low total energy consumption. Simulation results show that our algorithm is superior to LEACH in terms of the network lifetime, the variance of the energy, and residual energy. © 2021 IEEE.

关键词： Routing algorithms

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Beam-Based Secure Physical Layer key Generation for mmWave Massive MIMO system 15th

Beam-Based Secure Physical Layer Key Generation for mmWave M...

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15th EAI International Conference on Communications and networking, ChinaCom 2020

作者： Gao, Hao Huang, Yanling Liu, Danpu Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9783030677190

Massive MIMO system greatly enriches the randomness of the secret keys in the physical layer and increases the rate of key generation. However, it is not practical to obtain full channel state information for key generation in actual communication scenarios due to a large number of additional signaling overhead. In this paper, we proposed a feasible physical layer key generation scheme by using the beam information as a random source. The procedure for key generation is designed based on the current beam management mechanism in 5G NR. Therefore, the secret key is synchronously generated in the process of two-stage beam search between the gNB and the UE before data transmission, and the additional signaling overhead for key generation is little. Furthermore, to cope with the non-uniform distributed characteristics of the beams, we adopt Huffman code in the encoding of the beam index, thereby improving the efficiency of the key generation. Simulation results show that the proposed scheme can achieve mutual information per bit as high as 0.97, which is 2% to 3% better than that of equal length coding. Furthermore, the bit disagreement rate can be less than 1% in a harsh communication environment with a signal-to-noise ratio of −10 dB. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： MIMO systems

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Research on Unequal Clustering Protocol based on Fuzzy Logic and Entropy Weight Method 7

Research on Unequal Clustering Protocol based on Fuzzy Logic...

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7th International Conference on Computer and Communications, ICCC 2021

作者： An, Quanbiao Wu, Muqing Lu, Sixu Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

ISBN: (纸本)9781665409506

Clustering is an effective strategy to minimize the energy consumption of nodes in energy-constrained wireless sensor networks. In clustered wireless sensor networks, the network is divided into multiple clusters, and each cluster has a coordinator called cluster head, which collects data from its cluster members and forwards it to the base station through other cluster heads. Cluster wireless sensor networks often have hot spot problems. Due to high energy consumption caused by data forwarding load, cluster heads near the base station die earlier. This kind of node death leads to the coverage loophole of the network early and reduces the life cycle of the network. Unequal clustering is a technology to solve this problem. In non-uniform clustering wireless sensor networks, the size of clusters near the base station is smaller than that far away from the base station. In the process of cluster formation, non-cluster-head nodes are generally added to nearby cluster-head nodes. In this paper, an unequal clustering protocol based on fuzzy logic and entropy weight method (FEUC) is proposed to extend the life cycle of the network. This protocol makes the network form clusters of different sizes. Fuzzy logic method is used to select cluster heads and non-cluster heads join cluster heads to form clusters. The objective entropy weight method is used to select relay cluster heads to implement multi-hop routing strategy. Mamdani method is used for fuzzy reasoning. The proposed protocol is compared with the low-energy adaptive clustering hierarchy (LEACH) protocol, the energy-aware unequal clustering fuzzy protocol (EAUCF), and the fuzzy-based unequal clustering protocol (FUCA), in all scenarios, the proposed protocol has better performance. © 2021 IEEE.

关键词： Base stations

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