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作者： Huang, Yu Wen, Miaowen Zheng, Beixiong Cheng, Xiang Yang, Liuqing Ji, Fei School of Electronics and Information Engineering South China University of Technology Guangzhou510641 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Department of Electrical and Computer Engineering Colorado State University Fort CollinsCO80523 United States

In this paper, two transmit antenna selection schemes are proposed for precoding-aided spatial modulation (PSM) to enhance the secrecy performance with reduced hardware complexity. The first strategy is determined by the channel state information (CSI) of both the legitimate and illegitimate links, called deterministic antenna selection based PSM (DAS-PSM), which selects partial transmit antennas to implement zero-forcing (ZF) precoding for maximizing the secrecy rate. For practical implementation, the low-complexity DAS-PSM criterion is demonstrated. The second strategy resorts to random antenna selection (RAS) with the aid of fast radio-frequency switching. Different from the DAS-PSM, this so-called RAS based PSM (RAS-PSM) dispenses with the CSI of the wiretap channel, which generates the ZF precoding matrix associated with randomly selected transmit antenna combination during each symbol period, creating additional turbulence that solely affects the eavesdropper. To combat the issue of low secrecy rate in the high signal-to-noise ratio regime due to the finite-alphabet inputs, time-varying artificial noise with extra power can be incorporated into both aforementioned strategies, which is exemplified in the RAS-PSM. Finally, the secrecy rates of both proposed schemes are theoretically analyzed and evaluated via Monte Carlo simulations, demonstrating that both proposed schemes with different requirements are capable of enhancing the secrecy performance compared to the conventional PSM. © 1967-2012 IEEE.

关键词： Channel state information

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An application-driven non-orthogonal multiple access enabled computation offloading scheme

arXiv

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arXiv 2020年

作者： Ren, Qiqi Chen, Jian Abbasi, Omid Karabulut Kurt, Gunes Yanikomeroglu, Halim Yu, F. Richard State Key Laboratory of Integrated Service Networks Xidian University Xi’ an Shaanxi710071 China Department of Systems and Computer Engineering Carleton University OttawaON Canada Department of Communications and Electronics Engineering Istanbul Technical University Istanbul34469 Turkey

To cope with the unprecedented surge in demand for data computing for the applications, the promising concept of multi-access edge computing (MEC) has been proposed to enable the network edges to provide closer data processing for mobile devices (MDs). Since enormous workloads need to be migrated, and MDs always remain resource-constrained, data offloading from devices to the MEC server will inevitably require more efficient transmission designs. The integration of non-orthogonal multiple access (NOMA) technique with MEC has been shown to provide applications with lower latency and higher energy efficiency. However, existing designs of this type have mainly focused on the transmission technique, which is still insufficient. To further advance offloading performance, in this work, we propose an application-driven NOMA enabled computation offloading scheme by exploring the characteristics of applications, where the common data of the application is offloaded through multi-device cooperation. Under the premise of successfully offloading the common data, we formulate the problem as the maximization of individual offloading throughput, where the time allocation and power control are jointly optimized. By using the successive convex approximation (SCA) method, the formulated problem can be iteratively solved. Simulation results demonstrate the convergence of our method and the effectiveness of the proposed scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Power control

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Outage performance of cognitive multisource multidestination relay networks with imperfect channel state information and interference from primary transmitter

引用

High Technology Letters 2019年第4期25卷 369-377页

作者： Liu Shuai Sun Dechun Liu Zujun Yi Kechu Yang Hong Wang Kan State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071P.R.China China Academy of Space Technology Beijing 100094P.R.China Faculty of Computer Science and Engineering Xi’an University of TechnologyXi’an 710048P.R.China

Given imperfect channel state information(CSI)and considering the interference from the primary transmitter,an underlay cognitive multisource multidestination relay network is proposed.A closed-form exact outage probability and asymptotic outage probability are derived for the secondary system of the *** results show that the outage probability is influenced by the source and destination number,the CSI imperfection as well as the interference from the primary transmitter,while the diversity order is independent of the CSI imperfection and the interference from the primary transmitter,yet it is equal to the minimum of the source and destination ***,extensive simulations are conducted with different system parameters to verify the theoretical analysis.

关键词： outage performance cognitive network channel state information(CSI) primary transmitter

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Deep Reinforcement Learning Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications

arXiv

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arXiv 2021年

作者： Shi, Zhaoyuan Yang, Helin Xie, Xianzhong Lu, Huabing Cai, Jun Ding, Zhiguo School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing China Chongqing Key Lab of Computer networks and Communication Technology Chongqing University of Posts and Telecommunications Chongqing China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Department of Electrical and Computer Engineering Concordia University MontrealQCH3G 1M8 Canada Department of Electrical Engineering Princeton University PrincetonNJ08544 United States School of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom

The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficiency of the upcoming beyond fifth generation network (B5G), especially for support the wireless sensor communications in Internet of things (IoT) system. However, how to realize intelligent frequency, time, and energy resource allocation to support better performances is an important problem to be solved. In this paper, we study joint spectrum, energy, and time resource management for the EH-CR-NOMA IoT systems. Our goal is to minimize the number of data packets losses for all secondary sensing users (SSU), while satisfying the constraints on the maximum charging battery capacity, maximum transmitting power, maximum buffer capacity, and minimum data rate of primary users (PU) and SSUs. Due to the nonconvexity of this optimization problem and the stochastic nature of the wireless environment, we propose a distributed multidimensional resource management algorithm based on deep reinforcement learning (DRL). Considering the continuity of the resources to be managed, the deep deterministic policy gradient (DDPG) algorithm is adopted, based on which each agent (SSU) can manage its own multidimensional resources without collaboration. In addition, a simplified but practical action adjuster (AA) is introduced for improving the training efficiency and battery performance protection. The provided results show that the convergence speed of the proposed algorithm is about 4 times faster than that of DDPG, and the average number of packet losses (ANPL) is about 8 times lower than that of the greedy algorithm. Copyright © 2021, The Authors. All rights reserved.

关键词： Resource allocation

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Generating superpixels for high-resolution images with Decoupled Patch Calibration

arXiv

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arXiv 2021年

作者： Wang, Yaxiong Wei, Yunchao Qian, Xueming Zhu, Li Yang, Yi The School of Software Engineering Xi'an Jiaotong University Xi'an710049 China School of Computer and Information Technology Beijing Jiaotong University Beijing100000 China The Key Laboratory for Intelligent Networks and Network Security Ministry of Education Xi'an Jiaotong University Xi'an710049 China The SMILES Laboratory Xi'an Jiaotong University Xi'an710049 China Zhibian Technology Co. Ltd. Taizhou317000 China The School of Software Xi'an Jiaotong University Xi'an710049 China School of Computer Science and Technology Zhejiang University Hangzhou310000 China

Superpixel segmentation has recently seen important progress benefiting from the advances in differentiable deep learning. However, the very high-resolution superpixel segmentation still remains challenging due to the expensive memory and computation cost, making the current advanced superpixel networks fail to process. In this paper, we devise Patch Calibration networks (PCNet), aiming to efficiently and accurately implement high-resolution superpixel segmentation. PCNet follows the principle of producing high-resolution output from low-resolution input for saving GPU memory and relieving computation cost. To recall the fine details destroyed by the down-sampling operation, we propose a novel Decoupled Patch Calibration (DPC) branch for collaboratively augment the main superpixel generation branch. In particular, DPC takes a local patch from the high-resolution images and dynamically generates a binary mask to impose the network to focus on region boundaries. By sharing the parameters of DPC and main branches, the fine-detailed knowledge learned from high-resolution patches will be transferred to help calibrate the destroyed information. To the best of our knowledge, we make the first attempt to consider the deep-learning-based superpixel generation for high-resolution cases. To facilitate this research, we build evaluation benchmarks from two public datasets and one new constructed one, covering a wide range of diversities from fine-grained human parts to cityscapes. Extensive experiments demonstrate that our PCNet can not only perform favorably against the state-of-the-arts in the quantitative results but also improve the resolution upper bound from 3K to 5K on 1080Ti GPUs. © 2021, CC BY.

关键词： Image segmentation

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The impact of social and economic development on the spread of infectious respiratory diseases, push or constrain? Empirical research from China based on machine learning methods

The impact of social and economic development on the spread ...

引用

IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Ke Yuan Yabing Huang Qian Tang School of Computer and Information Engineering Henan University International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Kaifeng China School of Computer and Information Engineering Henan University Kaifeng China College of Environment and Planning Henan University Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Henan University Ministry of Education Kaifeng China

ISBN: (纸本)9781728176505

It is unclear whether socioeconomic factors affect the incidence of respiratory infectious diseases in China. This article uses generalized linear model and generalized additive model to analyze the relationship between socioeconomic factors and infectious diseases. Studies have shown that both models can reflect the relationship between socioeconomic factors and infectious diseases, but generalized additive model has better goodness of fit. Nationwide, considering the impact of a single economic and social factor on the incidence of respiratory infectious diseases, the GDP Per capita, age structure of population, local fiscal budgetary receipts and proportion of higher education have a significant impact on the incidence rate of five diseases (p

关键词： Analytical models Additives Infectious diseases Pulmonary diseases Sociology Lung Machine learning

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Hardware-Efficient ROADM Design with Fiber-Core Bypassing for WDM/SDM networks

Hardware-Efficient ROADM Design with Fiber-Core Bypassing fo...

引用

Optical Fiber Communication (OFC) Conference

作者： Lida Liu Shuangyi Yan Gerald Q. Maguire Yanlong Li Dimitra Simeonidou High Performance Networks Group University of Bristol UK School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Tsinghua National Laboratory for Information Science and Technology (TNList) Beijing China

A SDM/WDM ROADM is proposed with low port-count WSSs. Fiber-core bypassing reduces the number of and port-count of WSSs in the implementation. The design requires less hardware without compromising on network performa... 详细信息

ISBN: (数字)9781943580712

ISBN: (纸本)9781728167626

关键词： bypasses Allocation Algorithm wavelength assignment compromise Network

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Computation efficiency maximization in wireless-powered mobile edge computing networks

arXiv

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arXiv 2020年

作者： Zhou, Fuhui Hu, Rose Qingyang College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210000 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China Department of Electrical and Computer Engineering Utah State University United States

Energy-efficient computation is an inevitable trend for mobile edge computing (MEC) networks. Resource allocation strategies for maximizing the computation efficiency are critically important. In this paper, computation efficiency maximization problems are formulated in wireless-powered MEC networks under both partial and binary computation offloading modes. A practical non-linear energy harvesting model is considered. Both time division multiple access (TDMA) and non-orthogonal multiple access (NOMA) are considered and evaluated for offloading. The energy harvesting time, the local computing frequency, and the offloading time and power are jointly optimized to maximize the computation efficiency under the max-min fairness criterion. Two iterative algorithms and two alternative optimization algorithms are respectively proposed to address the non-convex problems formulated in this paper. Simulation results show that the proposed resource allocation schemes outperform the benchmark schemes in terms of user fairness. Moreover, a tradeoff is elucidated between the achievable computation efficiency and the total number of computed bits. Furthermore, simulation results demonstrate that the partial computation offloading mode outperforms the binary computation offloading mode and NOMA outperforms TDMA in terms of computation efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Mobile edge computing

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Spatial Multiplexing with Limited RF Chains: Generalized Beamspace Modulation (GBM) for mmWave Massive MIMO

Spatial Multiplexing with Limited RF Chains: Generalized Bea...

引用

作者： Gao, Shijian Cheng, Xiang Yang, Liuqing Department of Electrical and Computer Engineering Colorado State University Fort CollinsCO United States Department of Electronics State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computing Sciences Peking University Beijing China

Millimeter wave (mmWave) massive multiple-input multiple-output (mMIMO) has been recognized as a promising candidate for 5G communications for its capability of supporting Gb/s transmission. However, it is a common exercise to deploy a limited number of radio-frequency (RF) chains at mmWave mMIMO transceivers due to hardware complexity and cost. As a result, the potential multiplexing gain (MG), which is restricted by the smaller number of RF chains at the transmitter and receiver, is markedly compromised. In order to boost the MG and spectral efficiency (SE), we innovatively develop a novel index modulation termed as the generalized beamspace modulation (GBM). The acquisition of (sub-)beamspace is owing to a natural exploitation of the unique features of mmWave mMIMO. Based on the (sub-)beamspace, a complete GBM transceiver is designed and optimized. Unlike existing alternatives that are largely digital based, our GBM is tailored for the hybrid structure of mmWave mMIMO and can, thereby, realize efficient spatial multiplexing despite the limited RF chains. Extensive analyses and simulations have demonstrated remarkable superiority of GBM over existing counterparts in terms of the error performance and SE. © 1983-2012 IEEE.

关键词： Modulation

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Privacy-Preserving Spectrum Allocation in Cognitive Radio networks Based on Truthful Online Double Auction Mechanism

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Procedia computer Science 2020年 174卷 304-308页

作者： Yue Yan Anming Dong Haili Zheng Yi Sun School of Information Science and Engineering Qufu Normal University Rizhao 276826 China School of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan 250353 China Computer Science Center (National Supercomputer Center in Jinan) Shandong Provincial Key Laboratory of Computer Networks Qilu University of Technology (Shandong Academy of Sciences) Jinan 250014 China

Cognitive radio can improve spectrum utilization through spectrum sharing between primary and secondary users, thereby alleviating spectrum scarcity. Spectrum auction is one of the effective methods that can be utilized to achieve spectrum sharing. However, traditional spectrum auction is unable to guarantee the truth of the price given by bidders comprehensively, while neglecting the online characteristics of the buyers request arrival. Existing truthful online auction mechanisms do not consider the privacy leakage problem and fail to provide adequate privacy protection for bidders. In this paper, we propose a privacy-preserving spectrum allocation strategy based on a double online truthful auction mechanism. Specifically, we first propose a critical bid determination algorithm to guarantee the truth of the auction. Then, the channel allocation is modeled as a social welfare maximization optimization problem. Since the problem is NP-hard and it is difficult to solve in polynomial time. We propose a greedy algorithm that can effectively obtain a feasible solution to the problem. An online dynamic accessing mechanism is further designed by considering the arrival of requests of secondary users. Finally, differential privacy is introduced to encrypt sensitive information such as buyers location privacy and time dynamic. Experimental results validate our auction mechanism achieving higher social welfare and spectrum utilization.

关键词： spectrum allocation online auction privacy preservation truthfulness

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