GLOBECOM 2020 - 2020 IEEE Global Communications Conference最新文献_第8页

Service Migration for Multi-Cell Mobile Edge Computing 多小区移动边缘计算的业务迁移

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9348247

Zezu Liang, Yuan Liu, T. Lok, Kaibin Huang

{"title":"Service Migration for Multi-Cell Mobile Edge Computing","authors":"Zezu Liang, Yuan Liu, T. Lok, Kaibin Huang","doi":"10.1109/GLOBECOM42002.2020.9348247","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9348247","url":null,"abstract":"Mobile-edge computing (MEC) enhances the capacities and features of mobile devices via offloading computation-intensive tasks over wireless networks to the edge servers. One challenge faced by the deployment of MEC in cellular networks is to support user mobility, so that the offloaded tasks can be seamlessly migrated between base stations (BSs) without compromising the resource-utilization efficiency and link reliability. In this paper, we tackle the challenge by optimizing the policy for migration/handover between BSs by jointly managing computation-and-radio resources. The policy design is formulated as a multi-objective optimization problem that maximizes the sum offloading rate, quantifying MEC throughput, and minimizes the migration cost, where the issues of virtualization, I/O interference between virtual machines (VMs), and wireless multi-access are taken into account. To solve the complex combinatorial problem, we develop an efficient relaxation-and-rounding based approach, including an optimal iterative algorithm for solving the integer-relaxed problem and a novel integer-recovery design that exploits the derived problem properties. The simulation results show the close-to-optimal performance of the proposed migration policies under various settings, validating their efficiency in computation-and-radio resource management for joint service migration and BS handover in multi-cell MEC networks.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"124 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90983213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A DNN-based Multi-Objective Precoding for Gaussian MIMO Networks 基于dnn的高斯MIMO网络多目标预编码

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322490

Xinliang Zhang, M. Vaezi

{"title":"A DNN-based Multi-Objective Precoding for Gaussian MIMO Networks","authors":"Xinliang Zhang, M. Vaezi","doi":"10.1109/GLOBECOM42002.2020.9322490","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9322490","url":null,"abstract":"This paper investigates a precoding design for a two-user multiple-input multiple-output (MIMO) network with various objectives, including simultaneous wireless information and power transfer, energy harvesting, and security. Conventionally, precoding and power allocation matrices for these objectives are obtained via different solutions. While in some cases analytic solutions are known, in other cases only time-consuming iterative methods are available. To overcome this issue and unify the solutions for multi-objective networks, a deep learning-enabled framework is proposed in this paper. The proposed deep neural network (DNN)-based precoding learns how to optimize multiple objective functions and find their corresponding input covariance matrices concurrently, efficiently, and reliably. Compared to conventional iterative precoding methods, the proposed approach reduces on-the-fly computational complexity 91.19% while reaching near-optimal performance (99.64% of the optimal solution). The proposed DNN-based precoding can flexibly adapt itself to the different needs of the network and is faster and more robust than transitional approaches, making it an attractive solution for current and future communication networks.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91292715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

MCMC Decoding of LDPC Codes with BP Preprocessing 基于BP预处理的LDPC码的MCMC解码

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9348002

Jiun-Ting Huang, Young-Han Kim

引用次数: 1

Self-Interference-Resistant IEEE 802.11ad-Based Joint Communication and Automotive Long Range Radar 基于IEEE 802.11ad的自抗干扰联合通信与汽车远程雷达

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9348201

Aimin Tang, Xudong Wang

{"title":"Self-Interference-Resistant IEEE 802.11ad-Based Joint Communication and Automotive Long Range Radar","authors":"Aimin Tang, Xudong Wang","doi":"10.1109/GLOBECOM42002.2020.9348201","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9348201","url":null,"abstract":"The IEEE 802.11ad based joint communication and radar sensing has attracted great attentions for vehicles in recent years. The existing studies all assume full duplex communications between the transmitter and radar receiver based on perfect self-interference cancellation. However, the self-interference may not be fully cancelled due to the limitation of self-interference cancellation capability in practical cases, which will significantly degrade the sensing capability of the radar function, especially for the detection range. In this paper, the imperfect self-interference cancellation is considered and a novel joint communication and automotive long range radar sensing design is proposed based on OFDM frame structure in 802.11ad standard. The received signal model in the frequency domain synchronized with the self-interference is derived, in which the target reflection signal suffers inter-carrier-interference (ICI) and inter-symbol-interference (ISI). However, we show that the ISI can be leveraged for enhancing radar parameter estimation. Based on the received signal model, a novel pilot signal design is first developed to combat the self-interference for accurate velocity and coarse range estimation. Then, a few self-interference-free OFDM symbols at the end of the data frame are utilized to achieve accurate range estimation. Simulation results show that the decimeter-per-second level velocity estimation and centimeter level range estimation can be achieved for up to 200-meter radar sensing.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"18 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89860964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Game-based Network Slicing and Resource Scheduling for Compute First Networking 计算优先网络中基于游戏的网络切片和资源调度

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9348177

Zitong Wang, Deze Zeng, Lin Gu, Song Guo

{"title":"A Game-based Network Slicing and Resource Scheduling for Compute First Networking","authors":"Zitong Wang, Deze Zeng, Lin Gu, Song Guo","doi":"10.1109/GLOBECOM42002.2020.9348177","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9348177","url":null,"abstract":"Compute First Networking (CFN) recently is proposed as an in-network computing paradigm for well balancing between the networking and computation resource scheduling. Thanks to the proliferation of network functions virtualization, the virtualized network functions can coexist with the computing services on a shared platform like edge computing environment. Thus, one critical issue incurred by CFN is how to manage and schedule the resources among various services from different over-the-top service provider (OSP) with different resource requirements, i.e., network slicing. In this paper, we first formulate the network slicing problem as a Stackelberg game problem and prove that there exists a Nash equilibrium beneficial to both the Network Slice Broker (NSB) and OSP. Furthermore, we propose a cooperative game model on the networking and computation resource allocation within each slice and invent a Nash bargaining solution to resolve the intra-slice resource competition for slice performance promotion. Simulation results are provided to validate the effectiveness and high efficiency of the our proposed game based network slicing and resource scheduling algorithm.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"19 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89603306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Partially Observable Multi-Agent Deep Reinforcement Learning for Cognitive Resource Management 面向认知资源管理的部分可观察多智能体深度强化学习

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322150

Ning Yang, Haijun Zhang, R. Berry

引用次数: 9

Bayesian Online Learning for MEC Object Recognition Systems MEC对象识别系统的贝叶斯在线学习

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322146

Apostolos Galanopoulos, J. Ayala-Romero, G. Iosifidis, D. Leith

引用次数: 4

Networking Performance of Power Optimized C+L+S Multiband Transmission 功率优化C+L+S多波段传输的组网性能

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322068

B. Correia, R. Sadeghi, E. Virgillito, A. Napoli, N. Costa, J. Pedro, V. Curri

{"title":"Networking Performance of Power Optimized C+L+S Multiband Transmission","authors":"B. Correia, R. Sadeghi, E. Virgillito, A. Napoli, N. Costa, J. Pedro, V. Curri","doi":"10.1109/GLOBECOM42002.2020.9322068","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9322068","url":null,"abstract":"Both spatial-division multiplexing (SDM) and band-division multiplexing (BDM) emerge as possible solutions to increase the optical network capacity to support the traffic demand which has been rising over time. In this work, two different ROADM (Re-configurable Optical Add Drop Multiplexer) switching techniques, namely SDM-InS (Independent switching) and SDM-CCC (Core Continue Constant) are investigated and the resulting network capacity is compared with the BDM approach. In the BDM case, both L- and S-bands have been used in addition to C-band to increase the network capacity. The launch power is optimized to control the QoT (Quality of Transmission) summarized by the generalized SNR (GSNR) per channel. Due to: stimulated Raman scattering, frequency variation of loss, frequency variation of dispersion coefficient and noise figures, an optimum power tilt and offset are calculated for each band. We show that the total network capacity increased by $sim 2 times$ and $sim 3 times$, when using the L-band and L+S-bands in addition to the C-band, respectively, in both a reference German and a reference US network. Additionally, it was also shown that using additional bands, the increase in network capacity is close to the result of using additional optical fibers in the SDM case.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"36 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90309923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks 高能效异构低功耗物联网网络的能源交易与时间调度

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322418

Ngoc-Tan Nguyen, Diep N. Nguyen, D. Hoang, Nguyen Van Huynh, H. Nguyen, Q. Nguyen, E. Dutkiewicz

{"title":"Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks","authors":"Ngoc-Tan Nguyen, Diep N. Nguyen, D. Hoang, Nguyen Van Huynh, H. Nguyen, Q. Nguyen, E. Dutkiewicz","doi":"10.1109/GLOBECOM42002.2020.9322418","DOIUrl":"https://doi.org/10.1109/GLOBECOM42002.2020.9322418","url":null,"abstract":"In this paper, an economic model is proposed to jointly optimize profits for participants in a heterogeneous IoT wireless-powered backscatter communication network. In the network under considerations, a power beacon and IoT devices (with various communication types and energy constraints) are assumed to belong to different service providers, i.e., energy service provider (ESP) and IoT service provider (ISP), respectively. To jointly maximize the utility for both service providers in terms of energy efficiency and network throughput, a Stackelberg game model is proposed to study the strategic interaction between the ISP and ESP. In particular, the ISP first evaluates its benefits from providing IoT services to its customers and then sends its requested price together with the service time to the ESP. Based on the request from the ISP, the ESP offers an optimized transmission power that maximizes its utility while meeting energy demands of the ISP. To study the Stackelberg equilibrium, we first obtain a closed-form solution for the ESP and propose a low-complexity iterative method based on block coordinate descent (BCD) to address the non-convex optimization problem for the ISP. Through simulation results, we show that our approach can significantly improve the profits for both providers compared with those of conventional transmission methods, e.g., bistatic backscatter and harvest-then-transmit communication methods.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"3 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89261452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Fingerprinting-based Indoor and Outdoor Localization with LoRa and Deep Learning 基于指纹识别的LoRa和深度学习的室内外定位

GLOBECOM 2020 - 2020 IEEE Global Communications Conference Pub Date : 2020-12-01 DOI: 10.1109/GLOBECOM42002.2020.9322261

Jait Purohit, Xuyu Wang, S. Mao, Xiaoyan Sun, Chao Yang

引用次数: 20