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Novel Methods for Load Estimation in Cell Switching in HAPS-Assisted Sustainable 6G networks

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arXiv 2024年

作者： Salamatmoghadasi, Maryam Ozturk, Metin Yanikomeroglu, Halim Non-Terrestrial Networks Lab Department of Systems and Computer Engineering Carleton University OttawaONK1S5B6 Canada Ankara Yildirim Beyazit University Ankara06010 Turkey

In the evolving landscape of vertical heterogeneous networks (vHetNets), the practice of cell switching—particularly for small base stations (SBSs)—faces a significant challenge due to the lack of accurate data on the traffic load of sleeping SBSs. This information gap is crucial as it hinders the feasibility and applicability of existing power consumption optimization methods;however, the studies in the literature predominantly assume perfect knowledge about the traffic load of sleeping SBSs. Addressing this critical issue, our study introduces innovative methodologies for estimating the traffic load of sleeping SBSs in a vHetNet including the integration of a high altitude platform (HAPS) as a super macro base station (SMBS) into the terrestrial network. We propose three distinct spatial interpolation-based estimation schemes: clustering-based, distance-based, and random neighboring selection. Employing a real data set for empirical validations, we compare the estimation performance of the developed traffic load estimation schemes and assess the impact of estimation errors. Our findings demonstrate that accurate estimation of sleeping SBSs’ traffic loads is essential for making network power consumption optimization methods both feasible and applicable in vHetNets. © 2024, CC BY.

关键词： Electric power utilization

93-GHz Wireless Transmission Enabled by a Wideband Photonic Oscillator Based on Two Phase-Locked Lasers

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93-GHz Wireless Transmission Enabled by a Wideband Photonic ...

International Topical Meeting on Microwave Photonics (MWP)

作者： Antonio Malacarne Alberto Montanaro Alessandra Bigongiari Antonella Bogoni Vito Sorianello Claudio Porzi Photonic Networks & Technologies Nat'l Lab CNIT Pisa Italy Ericsson Research Ericsson Pisa Italy Telecommunications Computer Engineering and Photonics Institute (TeCIP) Scuola Superiore Sant'Anna Pisa Italy

ISBN: (数字)9798350375398

ISBN: (纸本)9798350375404

The mm-wave frequency spectrum offers the possibility to afford the increasing demand of high data-rate communication links. Microwave-photonics techniques can be advantageously used for reconfigurable generation of very high frequency clocks with no need for high-frequency and high-performance electrical oscillators and the additional functionality of remote distribution of the signal through fiber-optics or free-space optic links. Here we successfully test the spectral purity and stability of a wideband tunable photonic oscillator (WTPO) for supporting analog up-conversion of GHz-rate complex data signals in a W-band wireless transmission testbed. The oscillator output is derived from the beating into a photodiode of two narrow-linewidth lasers which are phase locked thanks to an electronic locking system. In this first demonstration, the WTPO output frequency has been multiplied to reach the target W band and error vector magnitude measurements attest the suitability of the solution for next generation 6G mobile networks.

关键词： Microwave measurement Wireless communication Masers Measurement by laser beam Microwave communication Microwave oscillators Vectors Frequency measurement Microwave photonics Wideband

Interpretation-Enabled Software Reuse Detection Based on a Multi-level Birthmark Model

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Interpretation-Enabled Software Reuse Detection Based on a M...

International Conference on Software engineering (ICSE)

作者： Xi Xu Qinghua Zheng Zheng Yan Ming Fan Ang Jia Ting Liu Key Laboratory of Intelligent Networks and Network Security Ministry of Education China School of Computer Science and Technology Xi’an Jiaotong University China State Key Lab on Integrated Services Networks School of Cyber Engineering Xidian University China Department of Communications and Networking Aalto University Finland School of Cyber Science and Engineering Xi’an Jiaotong University China

ISBN: (纸本)9781665402965;9781665448314

Software reuse, especially partial reuse, poses legal and security threats to software development. Since its source codes are usually unavailable, software reuse is hard to be detected with interpretation. On the other hand, current approaches suffer from poor detection accuracy and efficiency, far from satisfying practical demands. To tackle these problems, in this paper, we propose ISRD, an interpretation-enabled software reuse detection approach based on a multi-level birthmark model that contains function level, basic block level, and instruction level. To overcome obfuscation caused by cross-compilation, we represent function semantics with Minimum Branch Path (MBP) and perform normalization to extract core semantics of instructions. For efficiently detecting reused functions, a process for "intent search based on anchor recognition" is designed to speed up reuse detection. It uses strict instruction match and identical library call invocation check to find anchor functions (in short anchors) and then traverses neighbors of the anchors to explore potentially matched function pairs. Extensive experiments based on two real-world binary datasets reveal that ISRD is interpretable, effective, and efficient, which achieves 97.2% precision and 94.8% recall. Moreover, it is resilient to cross-compilation, outperforming state-of-the-art approaches.

关键词： Law Semantics Libraries Security Software reusability Software engineering Resilience

Extended $T$T: Learning With Mixed Closed-Set and Open-Set Noisy labels

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2022年第3期45卷 3047-3058页

作者： Xiaobo Xia Bo Han Nannan Wang Jiankang Deng Jiatong Li Yinian Mao Tongliang Liu Trustworthy Machine Learning Lab School of Computer Science Faculty of Engineering University of Sydney Camperdown NSW Australia Department of Computer Science Hong Kong Baptist University Hong Kong State Key Laboratory of Integrated Services Networks School of Telecommunications Engineering Xidian University Xi'an Shaanxi China Department of Computing Imperial College London London U.K. Meituan Beijing China

The noise transition matrix $T$ , reflecting the probabilities that true labels flip into noisy ones, is of vital importance to model label noise and build statistically consistent classifiers. The traditional transition matrix is limited to model closed-set label noise, where noisy training data have true class labels within the noisy label set. It is unfitted to employ such a transition matrix to model open-set label noise, where some true class labels are outside the noisy label set. Therefore, when considering a more realistic situation, i.e., both closed-set and open-set label noises occur, prior works will give unbelievable solutions. Besides, the traditional transition matrix is mostly limited to model instance-independent label noise, which may not perform well in practice. In this paper, we focus on learning with the mixed closed-set and open-set noisy labels. We address the aforementioned issues by extending the traditional transition matrix to be able to model mixed label noise, and further to the cluster-dependent transition matrix to better combat the instance-dependent label noise in real-world applications. We term the proposed transition matrix as the cluster-dependent extended transition matrix. An unbiased estimator (i.e., extended $T$ -estimator) has been designed to estimate the cluster-dependent extended transition matrix by only exploiting the noisy data. Comprehensive experiments validate that our method can better cope with realistic label noise, following its more robust performance than the prior state-of-the-art label-noise learning methods.

关键词： Noise measurement Training Training data Data models Search engines Face recognition computer science

Energy management of cooperative microgrids with P2P energy sharing in distribution networks

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Energy management of cooperative microgrids with P2P energy ...

IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Tian Liu Xiaoqi Tan Bo Sun Yuan Wu Xiaohong Guan Danny H. K. Tsang Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an China College of Information Engineering Zhejiang University of Technology Hangzhou China

To handle the mismatch problem between local demand and local generation in microgrids (MGs), the paradigm of peer-to-peer (P2P) energy sharing among neighboring MGs has been considered as a promising solution for improving the utilization of local distributed energy resources and saving the energy bills for all MGs. Existing works on cooperative MGs usually consider the high-level energy sharing and trading strategies but little about the physical constraints (e.g. voltage tolerance and power flow constraints) in the underlying distribution network. Hence, their solutions may not be applicable to practical power systems. This paper proposes an optimization problem that aims at minimizing the overall energy cost and the P2P energy sharing losses in a distribution network consisting of multiple MGs and explicitly incorporates the practical constraints (e.g., power balance and battery's operational constraints). The proposed optimization problem is difficult to solve directly due to the non-convex constraints. Nevertheless, motivated by the very recent result in radial distribution networks, the proposed non-convex optimization problem can be relaxed to a second-order cone programming (SOCP) problem without incurring any loss of optimality. We apply the proposed problem to a radial distribution network testbed and obtain the corresponding optimal energy management strategy, which exploits the diversified energy consumption profiles to dynamically coordinate multiple MGs and reduces the total energy bill of all MGs. Moreover, an interesting observation from the simulation results is that the cooperation scheme in the P2P sharing network is significantly affected by the MGs' relative locations in the distribution network.

关键词： Propagation losses Smart grids Microgrids Optimization Numerical models Renewable energy sources

Interpretation-enabled software reuse detection based on a multi-level birthmark model

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arXiv 2021年

作者： Xu, Xi Zheng, Qinghua Yan, Zheng Fan, Ming Jia, Ang Liu, Ting Key Laboratory of Intelligent Networks and Network Security Ministry of Education China School of Computer Science and Technology Xi'an Jiaotong University China School of Cyber Science and Engineering Xi'an Jiaotong University China State Key Lab on Integrated Services Networks School of Cyber Engineering Xidian University China Department of Communications and Networking Aalto University Finland

关键词： computer software reusability

Generative partial multi-view clustering

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arXiv 2020年

作者： Wang, Qianqian Ding, Zhengming Tao, Zhiqiang Gao, Quanxue Fu, Yun State Key Lab. Integrated Services Networks Xidian University Xi’an710071 China Department of Computer Information and Technology Indiana University-Purdue University Indianapolis United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Electrical and Computer Engineering Khoury College of Computer Sciences Northeastern University BostonMA02115 United States

Nowadays, with the rapid development of data collection sources and feature extraction methods, multi-view data are getting easy to obtain and have received increasing research attention in recent years, among which, multi-view clustering (MVC) forms a mainstream research direction and is widely used in data analysis. However, existing MVC methods mainly assume that each sample appears in all the views, without considering the incomplete view case due to data corruption, sensor failure, equipment malfunction, etc. In this study, we design and build a generative partial multi-view clustering model, named as GP-MVC, to address the incomplete multi-view problem by explicitly generating the data of missing views. The main idea of GP-MVC lies at two-fold. First, multi-view encoder networks are trained to learn common low-dimensional representations, followed by a clustering layer to capture the consistent cluster structure across multiple views. Second, view-specific generative adversarial networks are developed to generate the missing data of one view conditioning on the shared representation given by other views. These two steps could be promoted mutually, where learning common representations facilitates data imputation and the generated data could further explores the view consistency. Moreover, an weighted adaptive fusion scheme is implemented to exploit the complementary information among different views. Experimental results on four benchmark datasets are provided to show the effectiveness of the proposed GP-MVC over the state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

Time-varying massive MIMO channel estimation: Capturing, reconstruction and restoration

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arXiv 2019年

作者： Li, Muye Zhang, Shun Zhao, Nan Zhang, Weile Wang, Xianbin State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China School of Information and Communication Engineering Dalian University of Technology Dalian116024 China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an710049 China Department of Electrical and Computer Engineering Western University LondonON Canada

On the time-varying channel estimation, the traditional downlink (DL) channel restoration schemes usually require the reconstruction for the covariance of downlink process noise vector, which is dependent on DL channel covariance matrix (CCM). However, the acquisition of the CCM leads to unacceptable overhead in massive MIMO systems. To tackle this problem, in this paper, we propose a novel scheme for the DL channel tracking. First, with the help of virtual channel representation (VCR), we build a dynamic uplink (UL) massive MIMO channel model with the consideration of off-grid refinement. Then, a coordinate-wise maximization based expectation maximization (EM) algorithm is adopted for capturing the model parameters, including the spatial signatures, the time-correlation factors, the off-grid bias, the channel power, and the noise power. Thanks to the angle reciprocity, the spatial signatures, timecorrelation factors and off-grid bias of the DL channel model can be reconstructed with the knowledge of UL ones. However, the other two kinds of model parameters are closely related with the carrier frequency, which cannot be perfectly inferred from the UL ones. Instead of relearning the DL model parameters with dedicated training, we resort to the optimal Bayesian Kalman filter (OBKF) method to accurately track the DL channel with the partially prior knowledge. At the same time, the model parameters will be gradually restored. Specially, the factor-graph and the Metropolis Hastings MCMC are utilized within the OBKF framework. Finally, numerical results are provided to demonstrate the efficiency of our proposed scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： MIMO systems

Unilateral Left-Tail Anderson-Darling Test Based Spectrum Sensing with Laplacian Noise

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arXiv 2018年

作者： Jiang, Lijuan Li, Yongzhao Ye, Yinghui Chen, Yunfei Jin, Ming Zhang, Hailin Integrated Service Networks Lab of Xidian University Xi’an China School of Engineering University of Warwick CoventryCV4 7AL United Kingdom Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China

This paper focuses on spectrum sensing under Laplacian noise. To remit the negative effects caused by heavy-tailed behavior of Laplacian noise, the fractional lower order moments (FLOM) technology is employed to pre-process the received samples before spectrum sensing. Via exploiting the asymmetrical difference between the distribution for the FLOM of received samples in the absence and presence of primary users, we formulate the spectrum sensing problem under Laplacian noise as a unilateral goodness-of-fit (GoF) test problem. Based on this test problem, we propose a new GoF-based detector which is called unilateral left-tail Anderson Darling (ULAD) detector. The analytical expressions for the theoretical performance, in terms of false-alarm and detection probabilities, of the ULAD are derived. Moreover, a closed-form expression for the optimal detection threshold is also derived to minimize the total error rate. Simulation results are provided to validate the theoretical analyses and to demonstrate the superior performance of the proposed detector than others. Copyright © 2018, The Authors. All rights reserved.

关键词： Laplace transforms