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IEEE Conference on wireless communications and networking

作者： Yongchang Deng Yuze Zou Shimin Gong Bin Lyu Dinh Thai Hoang Dusit Niyato School of Intelligent Systems Engineering Sun Yat-sen University China School of Electronic Information and Communications Huazhong University of Science and Technology China Key Laboratory of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China School of Electrical and Data Engineering University of Technology Sydney Australia School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we consider IRS-assisted transmissions from a multi-antenna access point (AP) to a receiver with uncertain channel information. By adjusting the magnitude of reflecting coefficients, the IRS can sustain its operations by harvesting energy from the AP's signal beamforming. Considering channel estimation errors, we model both the AP-IRS channel and the AP-IRS-receiver as a cascaded channel by norm-based uncertainty sets. This allows us to formulate a robust optimization problem to minimize the AP's transmit power, subject to the receiver's worst-case data rate requirement and the IRS's worst-case power budget constraint. Instead of using the alternating optimization (AO) method, we firstly propose a heuristic scheme to decompose the IRS's phase shift optimization and the AP's active beamforming. Based on semidefinite relaxations of the worst-case constraints, we further devise an iterative algorithm to optimize the AP's transmit beamforming and the magnitude of the IRS's reflecting coefficients efficiently by solving a set of semidefinite programs. Simulation results reveal that the AP requires a higher transmit power to deal with the channel uncertainty. Moreover, the negative effect of channel uncertainty can be alleviated by using a larger-size IRS.

关键词： wireless communication Uncertainty Array signal processing Simulation Transmitting antennas Channel estimation Receivers

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Energy-optimized 5G dual connectivity radio resource allocation 2

Energy-optimized 5G dual connectivity radio resource allocat...

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2nd IEEE International Conference on Electronics technology, ICET 2019

作者： Ying, Guo Qingmin, Meng Xiaoming, Wang Ministry of Education College of Telecommunications Information Engineering Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China National Mobile Communications Research Lab Southeast University Nanjing210096 China

ISBN: (纸本)9781728116181

Non-independent networking of 5G NSA (Non-Standalone) is receiving wide attention. This paper considers an NSA architecture in which a 4G base station is used as the primary station and a newly deployed 5G base station is used as the secondary station. Machine-type communication and vehicle networking applications place stringent requirements on end-to-end delay of 5G NSA like systems. Due to limited computing power, part of the terminal data needs to be uploaded to the edge cloud to perform intensive calculations. An optimized radio resource allocation scheme is proposed for dual connectivity transmission under 5G NSA. Second, the relevant handover strategies are also evaluated. Computer simulation results show that compared with single-connection transmission, dual-connection transmission can significantly improve the energy consumption performance of the transmission scheme under a time delay constraint. © 2019 IEEE.

关键词： Mobile edge computing

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Mobile optical communications using second harmonic of intra-cavity laser

arXiv

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arXiv 2021年

作者： Xiong, Mingliang Liu, Qingwen Wang, Xin Zhou, Shengli Zhou, Bin Bu, Zhiyong College of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Communication Science and Engineering Fudan University Shanghai200433 China Department of Electrical and Computer Engineering University of Connecticut StorrsCT06250 United States Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai200050 China

Optical wireless communication (OWC) meets the demands of the future six-generation mobile network (6G) as it operates at several hundreds of Terahertz and has the potential to enable data rate in the order of Tbps. However, most beam-steering OWC technologies require high-accuracy positioning and high-speed control. Resonant beam communication (RBCom), as one kind of non-positioning OWC technologies, has been proposed for high-rate mobile communications. The mobility of RBCom relies on its self-alignment characteristic where no positioning is required. In a previous study, an external-cavity second-harmonic-generation (SHG) RBCom system has been proposed for eliminating the echo interference inside the resonator. However, its energy conversion efficiency and complexity are of concern. In this paper, we propose an intra-cavity SHG RBCom system to simplify the system design and improve the energy conversion efficiency. We elaborate the system structure and establish an analytical model. Numerical results show that the energy consumption of the proposed intra-cavity design is reduced to reach the same level of channel capacity at the receiver compared with the external-cavity one. Copyright © 2021, The Authors. All rights reserved.

关键词： Harmonic generation

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Outage Performance Analysis and Parameter optimization of Hovering UAV-Based FSO System

Outage Performance Analysis and Parameter optimization of Ho...

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IEEE International Conference on communications (ICC)

作者： Yang Ma Jin-Yuan Wang Jun-Bo Wang Min Lin Hua Zhang Chuanwen Chang National Mobile Communications Research Laboratory Southeast University Nanjing China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China The 28th Research Institute of China Electronics Technology Group Corporation Nanjing China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

In this paper, a hovering unmanned aerial vehicle (UAV)-based free-space optical (FSO) serial multi-hop decode-and-forward relaying system is investigated. Considering the joint effect of atmospheric loss, atmospheric turbulence, pointing error and angle-of-arrival (AOA) fluctuation, the novel closed-form expressions of the link outage probabilities for ground-to-UAV, UAV-to-UAV, and UAV-to-ground links are derived, and the expression of the end-to-end outage probability for the UAV-based relaying system is also obtained. The asymptotic outage performance bounds for each link and the considered system are presented to reveal insights into the impact of AOA fluctuations. Based on the derived theoretical results, an optimization problem of receiver's field-of-view (FOV) is formulated to alleviate the impairment of AOA fluctuation. Numerical results show that the derived theoretical expressions are accurate to evaluate the outage performance of UAV-based FSO system. Moreover, the derived FOV can improve performance significantly.

关键词： Atmospheric modeling Optical fiber communication Adaptive optics Unmanned aerial vehicles Optical receivers Power system reliability Probability

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Tight capacity bounds for indoor visible light communications with signal-dependent noise

arXiv

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arXiv 2020年

作者： Wang, Jin-Yuan Fu, Xian-Tao Lu, Rong-Rong Wang, Jun-Bo Lin, Min Cheng, Julian Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Communications Research Laboratory Southeast University Nanjing211111 China School of Engineering University of British Columbia KelownaBCV1V 1V7 Canada

Channel capacity bounds are derived for a point-to-point indoor visible light communications (VLC) system with signal-dependent Gaussian noise. Considering both illumination and communication, the non-negative input of VLC is constrained by peak and average optical intensity constraints. Two scenarios are taken into account: one scenario has both average and peak optical intensity constraints, and the other scenario has only average optical intensity constraint. For both two scenarios, we derive closed-from expressions of capacity lower and upper bounds. Specifically, the capacity lower bound is derived by using the variational method and the property that the output entropy is invariably larger than the input entropy. The capacity upper bound is obtained by utilizing the dual expression of capacity and the principle of "capacity-achieving source distributions that escape to infinity". Moreover, the asymptotic analysis shows that the asymptotic performance gap between the capacity lower and upper bounds approaches zero. Finally, all derived capacity bounds are confirmed using numerical results. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Voiceprint recognition based on BP Neural network and CNN 4

Voiceprint recognition based on BP Neural Network and CNN

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2019 4th International Conference on Intelligent Computing and Signal Processing, ICSP 2019

作者： Zhipeng, Dong Jingcheng, Wei Yumin, Xu Qingmin, Meng Xiaoming, Wang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education College of Telecommunications and Information Engineering Nanjing210003 China National Mobile Communications Research Lab Southeast University Nanjing210096 China

At present, speech recognition has become a key technology of human-computer interaction, which can be used in semantic recognition and speaker identification and other related applications. This paper focuses on a speaker identification scene and the technical design. Because artificial neural network has the ability to distinguish complex classification boundaries, plenty of work on speech recognition had studied multi-layer perceptual networks to improve the accuracy of classification where back propagation method (BP algorithm) has been used. In the studied scheme, when the test objects (speakers) speak the same isolated word, the identification system can judge who the speaker is by identifying the voice voiceprint of different people. Our design not only considers the recognition based on BP as well as its variant, but also explores the voiceprint recognition based on convolution neural network (CNN). Secondly, the network structure and performance are also compared in detail. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Speech recognition

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Spectrum Occupancy Prediction for Internet of Things via Long Short-Term Memory

Spectrum Occupancy Prediction for Internet of Things via Lon...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Haoyu Li Xiaojin Ding Yiguang Yang Xiaogu Huang Genxin Zhang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology NUPT National Mobile Communications Research Laboratory Southeast University Nanjing China

With the development of Internet of things (IoT), the demand on spectrum is increasing rapidly. Moreover, due to lack of power and the feature of short burst, the signals of IoT may be transmitted relying on accessing the idle spectrum, leading to a higher successful transmitting probability. Thus, the spectrum should be allocated in advance for the ongoing terminals of IoT. In this paper, a long short-term memory aided spectrum-prediction (LSTMSP) scheme has been conceived by analyzing the relationships between time and frequency of historical spectrum data. Performance evaluations on realworld spectrum data show that the accuracy of the spectrum occupancy prediction is above 0.7, demonstrating the benefits of the conceived LSTMSP method.

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Distributed Edge Caching with Content Recommendation in Fog-RANs Via Deep Reinforcement Learning

Distributed Edge Caching with Content Recommendation in Fog-...

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IEEE International Conference on communications Workshops, ICC

作者： Jie Yan Yanxiang Jiang Fuchun Zheng F. Richard Yu Xiqi Gao Xiaohu You National Mobile Communications Research Laboratory Southeast University Nanjing China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China School of Information Technology Carleton University Canada

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

In this paper, the distributed edge caching problem with dynamic content recommendation is investigated in fog radio access networks (F-RANs). Firstly, the joint caching and recommendation policy is transformed into a `single' caching policy by incorporating the recommendation policy into the cache policy and the corresponding training complexity is halved. Considering that there is no existing user requests dataset involving content recommendation, we propose a time-varying personalized user request model to describe the fluctuant demands of each user after content recommendation. Then, to maximize the long-term net profit of each fog access point (F-AP), we formulate the caching optimization problem and resort to a reinforcement learning (RL) framework. Finally, to circumvent the curse of dimensionality of RL and speed up the convergence, we propose a double deep Q-network (DDQN) based distributed edge caching algorithm to find the optimal caching policy with content recommendation. Simulation results show that the average net profit of our proposed algorithm is increased by nearly half compared with the traditional methods. Besides, content recommendation could indeed accelerate the convergence and increase cache efficiency.

关键词： Optimization Servers Machine learning Radio access networks Training Complexity theory Convergence

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Hierarchical Cooperative Caching in Fog Radio Access networks: A Brain Storm Optimization Approach

Hierarchical Cooperative Caching in Fog Radio Access Network...

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GLOBECOM 2020 - 2020 IEEE Global communications Conference

作者： Xuan Chen Yanxiang Jiang Baotian Fan Fu-Chun Zheng Dusit Niyato Xiaohu You Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China School of Computer Engineering Nanyang Technological University (NTU) Singapore National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

In this paper, the cooperative caching problem in fog radio access networks (F-RANs) is investigated. To minimize the content request delay, we formulate the hierarchical cooperative caching optimization problem to find the optimal caching policy. Considering the non-deterministic polynomial hard (NP-hard) property of this problem, we propose a brain storm optimization (BSO) approach which utilizes the penaltybased fitness function in individuals evaluation to meet the storage capacity constraint and the genetic algorithm (GA) in new individuals generation to meet the integer constraint, respectively. To further reduce the computational complexity, we propose to implement the convergent operation in the objective space via individuals classification. Simulation results show that our proposed BSO-based hierarchical cooperative caching policy achieves remarkable performance in minimizing the content request delay.

关键词： Delays Cooperative caching Servers Optimization Computational complexity Storms Statistics

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Secrecy capacity bounds for visible light communications with signal-dependent noise

arXiv

引用

arXiv 2021年

作者： Wang, Jin-Yuan Fu, Xian-Tao Wang, Jun-Bo Lin, Min Cheng, Julian Alouini, Mohamed-Slim Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai200062 China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Communications Research Laboratory Southeast University Nanjing211111 China School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In physical-layer security, one of the most fundamental issues is the secrecy capacity. The objective of this paper is to determine the secrecy capacity for an indoor visible light communication system consisting of a transmitter, a legitimate receiver and an eavesdropping receiver. In such a system, both signal-independent and signal-dependent Gaussian noises are considered. Under non-negativity and average optical intensity constraints, lower and upper secrecy capacity bounds are first derived by the variational method, the dual expression of the secrecy capacity, and the concept of "the optimal input distribution that escapes to infinity". Numerical results show that the secrecy capacity upper and lower bounds are tight. By an asymptotic analysis at large optical intensity, there is a small performance gap between the asymptotic upper and lower bounds. Then, by adding a peak optical intensity constraint, we further analyze the exact and asymptotic secrecy capacity bounds. Finally, the tightness of the derived bounds is verified by numerical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Asymptotic analysis

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