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16th International Conference on wireless communications and Signal Processing, WCSP 2024

作者： Yu, Han Dou, Haie Xu, Xinmian Cui, Jingwu Wang, Lei Liu, Chen Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China

ISBN: (纸本)9798350390643

The emergence of new applications has increased the demand of mobile users for edge computing. Therefore, the optimization of base station load balancing and task offloading is particularly important. In this paper, a two-tier heterogeneous mobile edge computing (MEC) system based on Stackelberg Game (SG) is studied. The introduction of SG can improve user association flexibility while reducing base station load. The introduction of network slicing can classify users according to different types, which increases the universality of the proposed framework. To solve the above problem, we map an optimization problem of efficiency, computation delay and computation energy consumption. Due to the non-convexity of the optimization problem, the Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm based on SG is proposed in this paper. The gradient descent strategy can converge faster and obtain the optimal solution of user association policy and unload policy. Through simulation, it is verified that the proposed scheme can obtain lower computation delay and computation energy consumption on the basis of solving the problem of base station overload. © 2024 IEEE.

关键词： Deep reinforcement learning

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Utility Maximization for NFV-Based Tactile Internet

Utility Maximization for NFV-Based Tactile Internet

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2023 IEEE/CIC International Conference on communications in China, ICCC 2023

作者： Xu, Xinmian Dou, Haie Chen, Mingkai Wang, Lei Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China

ISBN: (纸本)9798350345384

In recent years, there has been significant attention and development in the Tactile Internet (TI) as a new type of network that supports typical applications such as remote healthcare and virtual reality. However, the demand for ultra-low latency and the inflexibility of traditional network architecture have presented serious challenges. In this paper, we propose a utility function for TI based on 5G network function virtualization (NFV) technology to evaluate network performance. The utility function considers the transmission of haptic and video data flows, as well as their latency and cost. We then formulate a network optimization problem with the utility function as the objective, strictly constraining latency and cost. To address this problem, we design two algorithms: the VNF deployment and routing of haptic and video flows (DRHV) algorithm tackles the VNF deployment and path selection issue, while the deep deterministic policy gradient(DDPG)-based traffic scheduling (DTS) algorithm allocates traffic resources and saves costs. Simulation results demonstrate that our algorithms achieve excellent optimization performance under the given constraints, and parameter changes align with the expected relationships and trends. © 2023 IEEE.

关键词： network function virtualization

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Distributed Deep Learning for Cooperative Computation Offloading in Low Earth Orbit Satellite networks

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China communications 2022年第4期19卷 230-243页

作者： Qingqing Tang Zesong Fei Bin Li School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 210044China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsMinistry of EducationNanjing 210003China

Low earth orbit(LEO) satellite network is an important development trend for future mobile communication systems, which can truly realize the“ubiquitous connection” of the whole world. In this paper, we present a cooperative computation offloading in the LEO satellite network with a three-tier computation architecture by leveraging the vertical cooperation among ground users, LEO satellites, and the cloud server, and the horizontal cooperation between LEO satellites. To improve the quality of service for ground users, we optimize the computation offloading decisions to minimize the total execution delay for ground users subject to the limited battery capacity of ground users and the computation capability of each LEO satellite. However, the formulated problem is a large-scale nonlinear integer programming problem as the number of ground users and LEO satellites increases, which is difficult to solve with general optimization algorithms. To address this challenging problem, we propose a distributed deep learning-based cooperative computation offloading(DDLCCO) algorithm, where multiple parallel deep neural networks(DNNs) are adopted to learn the computation offloading strategy dynamically. Simulation results show that the proposed algorithm can achieve near-optimal performance with low computational complexity compared with other computation offloading strategies.

关键词： LEO satellite networks computation offloading deep neural networks

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Reinforcement Learning from Human-like Feedback Enhances Semantic communication with Multimodal LLMs 16

Reinforcement Learning from Human-like Feedback Enhances Sem...

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16th International Conference on wireless communications and Signal Processing, WCSP 2024

作者： Zhang, Xinyu He, Xitao Chen, Mingkai Wang, Lei Ministry of Education Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China

ISBN: (纸本)9798350390643

Semantic communication is an emerging intelligent paradigm that provides some special solutions for the various future applications. With the rise of large language model (LLM), it may enhance well on semantic communication. However, how to balance on the accuracy and the efficiency of compression remains an urgent issue to semantic communication with LLMs. In this paper, we design a multimodal large language models (MLLMs)-enabled semantic communication system specifically designed for image transmission, where the reinforcement learning from human-like feedback (RLHLF) framework is proposed to apply reasoning and self-reflection capabilities of MLLMs to enhance the quality of semantic extraction and image generation. For one thing, we first optimize the image semantic information at the transmitter by RLHLF framework. For another thing, the generated images are optimized at the receiver by RLHLF framework. Simulation results show that our proposed system provides bandwidth savings and enables graceful performance improvement as the channel quality improves, which proves the potential of MLLMs for future semantic communication. © 2024 IEEE.

关键词： Channel coding

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Bessel–Gaussian beam-based orbital angular momentum holography

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Chinese Physics B 2024年第1期33卷 407-413页

作者：季佳滢郑志刚朱家龙王乐王新光赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing 210003China National Laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM), as a new degree of freedom, has recently been applied in holography *** to the infinite helical mode index of OAM mode, a large number of holographic images can be reconstructed from an OAM-multiplexing hologram. However, the traditional design of an OAM hologram is constrained by the helical mode index of the selected OAM mode, for a larger helical mode index OAM mode has a bigger sampling distance, and the crosstalk is produced for different sampling distances for different OAM modes. In this paper, we present the design of the OAM hologram based on a Bessel–Gaussian beam, which is non-diffractive and has a self-healing property during its propagation. The Fourier transform of the Bessel–Gaussian beam is the perfect vortex mode that has the fixed ring radius for different OAM modes. The results of simulation and experiment have demonstrated the feasibility of the generation of the OAM hologram with the Bessel–Gaussian beam. The quality of the reconstructed holographic image is increased, and the security is enhanced. Additionally, the anti-interference property is improved owing to its self-healing property of the Bessel-OAM holography.

关键词： orbital angular momentum holography Bessel–Gaussian beam OAM-multiplexing hologram

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Performance Analysis for Intrusion Target Detection in wireless sensor networks

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电子学报(英文版) 2011年第4期20卷 725-729页

作者： FAN Gaojuan WANG Ruchuan HUANG Haiping SUN Lijuan XIAO Fu College of Computer Nanjing University of Posts and Telecommunications Nanjing Chin School of Computer and Information Engineering Henan University Kaifeng China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications) Ministry of Education of Jiangsu Province Nanjing China

Target detection and field surveillance are among the most prominent applications of wireless sensor networks. The quality of detection achieved by a sensor network can be quantified by evaluating the probability of detecting a mobile target crossing a sensing field. Detection probability of sensor nodes has been studied in sensor networks for many purposes such as quality of service and decision making. However, the sensing capabilities of sensors are affected by environmental factors in real deployment. This paper investigates the problem of detecting probability in a log-normal shadow fading environment. It presents an analytic method to evaluate the detection probability by at least k sensors under practical considerations. Furthermore, we also shows that shadow fading makes significant influence in detection probability compared to unit disk sensing model through extensive simulation experiments.

关键词：无线传感器网络目标检测性能分析入侵检测概率环境因素阴影衰落传感器节点

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Delay constraint adaptive routing based on seed spray in opportunistic networks

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Journal of Computational Information Systems 2012年第12期8卷 5137-5148页

作者： Xu, Jia Wang, Ruchuan Sun, Lijuan College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing 210003 China Key Lab. of Broadband Wireless Communication and Sensor Network Technol. Min. of Edu. Jiangsu Prov. Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Laboratory for Computer Network and Information Integration Ministry of Education Southeast University Nanjing 211189 China State Key Lab. for Novel Software Technology Nanjing University Nanjing 210093 China

Opportunistic networks are sparse wireless networks which have no complete path from the source to the destination most of the time. Many applications require the support of delay constrained routing mechanism which can provide acceptable and resilient services in the challenged environments. We proposed Adaptive Seed Spray (ASS) to achieve the delay constraint with low cost in dynamic opportunistic networks. ASS will estimate the routing cost in source node, and use a small number of seed nodes to spray message copies in order to reduce redundant copies. Furthermore, ASS will make spray decisions in relay nodes which have the latest information of the networking conditions. Simulation results have shown that ASS has prominent superiority in routing cost and adaptability, and it is an efficient delay-bounded multi-copy routing protocol for opportunistic networks especially for dynamic conditions. © 2012 Binary Information Press.

关键词： Cost benefit analysis

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Analysis of Satellite Interference Source Location Algorithm 7

Analysis of Satellite Interference Source Location Algorithm

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7th International Conference on Computer and communications, ICCC 2021

作者： Yan, Hui Zhao, Laiding Zhang, Gengxin Ruan, Cen 'Telecommunication and Network' National Engineering Research Center Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing China

ISBN: (纸本)9781665409506

There are many methods and principles of satellite interference source location, but no matter which method is chosen, the positioning equation is nonlinear. Therefore, it is very important to solve the nonlinear equations accurately for the accuracy of the final positioning results. In this paper, an improved particle swarm optimization (PSO) algorithm is proposed. Based on the combination of PSO and grid search algorithm, the precision requirement is set in the iterative stop condition. When the calculation results meet the set precision, iteration can be stopped. Compared with the ordinary particle swarm optimization algorithm, the results can be obtained more quickly and accurately. © 2021 IEEE.

关键词： Satellites

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TA3C: Teaching-Oriented Adaptive Wi-Fi Authorized Access Control Based on CSI 12

TA3C: Teaching-Oriented Adaptive Wi-Fi Authorized Access Con...

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12th International Conference on Mobile Ad-Hoc and sensor networks, MSN 2016

作者： Xiao, Fu Chen, Jing Xie, Xiaohui Sun, Lijuan Wang, Ruchuan College of Computer Nanjing University of Posts and Telecommunications Jiangsu China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Jiangsu China Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Jiangsu China

ISBN: (纸本)9781509056965

Wi-Fi has been widely deployed with the rapid development of wireless communication technique. Wi-Fi hotspots are popular in campus, making convenient wireless network access possible. However, during class teaching, in order to avoid students browsing the web based on Wi-Fi hotspots and distracting, we hope Wi-Fi hotspots adaptively shield network access to students in the classroom, while grant access to users outside the classroom. In this work, we prototype TA3C system, a teaching-oriented adaptive Wi-Fi authorized access control scheme, using Channel State Information (CSI) to locate instead of coarse-grained and temporally unstable Received Signal Strength Indication (RSSI). CSI can distinguish multipath signals, stay stable in the same propagation environment, and show different characteristics in different propagation environments, based on which, we can distinguish outdoor and indoor environments, and identify user's location to decide whether to offer him wireless network access or not. Experiment results show that TA3C effectively achieve adaptive Wi-Fi authorized access control, which provides a guarantee for the quality of class teaching. Compared to traditional indoor localization techniques, TA3C does not need accurate location information but simply recognizes user's location indoors or outdoors, which means it does not need dedicated hardware, realizing the low-cost indoor localization technique. © 2016 IEEE.

关键词： Access control

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Resource allocation algorithm for uplink OFDMA-based cognitive radio systems

Resource allocation algorithm for uplink OFDMA-based cogniti...

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2011 IEEE 3rd International Conference on communication Software and networks, ICCSN 2011

作者： Wang, Yanping Yang, Longxiang Liu, Xu Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communications and Sensor Network Technology Nanjing China

ISBN: (纸本)9781612844855

This context addresses the subcarrier and power allocation problem in the uplink of an OFDMA system under the cognitive radio environment. The objective is to maximize the sum transmission rate of secondary users, without causing adverse interference to the primary users. We formulate the optimization problem subject to the individual power constraints and the interference constraints. We also propose two suboptimal power loading algorithms that are less complex and a new subcarrier allocation algorithm. The performance of the optimal scheme is compared with the performance of the suboptimal. Simulation results show that the optimal algorithm significantly improves the sum transmission rate, and provides good convergence. © 2011 IEEE.

关键词： Cognitive radio

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