2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)最新文献_第10页

Distributed Low-Complexity Multi-Cell Coordinated Multicast Beamforming with Large-Scale Antennas 大规模天线分布式低复杂度多小区协调组播波束形成

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8446030

Jiawei Yu, Min Dong

引用次数: 8

A Two-Step Chunk-Based Algorithm for Offloading Streaming Traffic Through a Vehicular Cloud 一种基于分块的两步车云分流算法

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445782

Luigi Vigneri, T. Spyropoulos, C. Barakat

{"title":"A Two-Step Chunk-Based Algorithm for Offloading Streaming Traffic Through a Vehicular Cloud","authors":"Luigi Vigneri, T. Spyropoulos, C. Barakat","doi":"10.1109/SPAWC.2018.8445782","DOIUrl":"https://doi.org/10.1109/SPAWC.2018.8445782","url":null,"abstract":"Using vehicles equipped with small caches as small base stations has recently been proposed as an interesting middle ground between caching at fixed base stations (which has higher CAPEX/OPEX), and caching at user devices (which has resource limitations). A typical problem in this setup is which content to store in which vehicles. The correct answer depends on the application. Indeed, if the stored content will be streamed (not downloaded), then this offers a natural delay tolerance: latter parts of the content do not need to be downloaded immediately from expensive links (e.g., macro-cells), but could be fetched from encountered vehicles cheaply. In an earlier work, we formulated a related optimal cache allocation problem, in which the proposed solution stores a content in its entirety. In light of recent statistics suggesting that different parts of a content (e.g., YouTube clips) are not watched equally frequently, this method is suboptimal. In this paper, we thus consider per-chunk allocation, and propose a simple two-step heuristic that first allocates the vehicular cloud capacity among content items, then efficiently distributes the capacity for a specific content among its chunks. Trace-driven simulation results suggest that chunk-based allocation can lead to considerable gains.","PeriodicalId":240036,"journal":{"name":"2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131930114","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

Mobile App User Choice Engineering Using Behavioral Science Models 使用行为科学模型的移动应用程序用户选择工程

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445922

M. Karaliopoulos, I. Koutsopoulos

{"title":"Mobile App User Choice Engineering Using Behavioral Science Models","authors":"M. Karaliopoulos, I. Koutsopoulos","doi":"10.1109/SPAWC.2018.8445922","DOIUrl":"https://doi.org/10.1109/SPAWC.2018.8445922","url":null,"abstract":"When interacting with mobile apps, users need to take decisions and make certain choices out of a set of alternative ones offered by the app. We introduce optimization problems through which we engineer the choices presented to users so that they are nudged towards decisions that lead to better outcomes for them and for the app platform. User decision-making rules are modeled by using principles from behavioral science and machine learning. Such instances arise in (i) mobile crowdsensing campaigns, where tasks are assigned to users through the app, and the goal is to optimize the quality of fulfilled tasks; (ii) smart-energy apps, where energy-saving recommendations are issued through the app, and the goal is to optimize energy savings; (iii) mobile advertising, where ads or offers are projected to the user, and the aim is to optimize revenue through user response to ads. Each user is modeled as a vector of feature values for a set of features. In an important class of decision-making models in behavioral science, the lexicographic fast-and-frugal-tree (FFT) heuristics, user decision emerges through a ranking of features that in turn gives rise to a decision tree. Having the incentive as a controllable feature that guides the user decision process, we study and characterize the complexity of the problem of allocating choices and incentives to users out of a limited budget. Numerical results indicate important performance gains when the incentive allocation policy adapts to user lexicographic choices.","PeriodicalId":240036,"journal":{"name":"2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132244289","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: 0

A Machine Learning Assisted Cell Selection Method for Drones in Cellular Networks 蜂窝式网络中无人机的机器学习辅助小区选择方法

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445967

S. Zhang, F. Xue, N. Himayat, S. Talwar, H. T. Kung

引用次数: 7

A Fair Comparison of Virtual to Full Antenna Array Measurements 虚拟与全天线阵测量的公平比较

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445923

Stefan Pratschner, S. Caban, Daniel Schützenhöfer, M. Lerch, E. Zöchmann, M. Rupp

引用次数: 6

Ray-Tracing Based Fingerprinting for Indoor Localization 基于光线追踪的室内指纹定位

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445928

Olivier Renaudin, T. Zemen, Thomas Burgess

{"title":"Ray-Tracing Based Fingerprinting for Indoor Localization","authors":"Olivier Renaudin, T. Zemen, Thomas Burgess","doi":"10.1109/SPAWC.2018.8445928","DOIUrl":"https://doi.org/10.1109/SPAWC.2018.8445928","url":null,"abstract":"Empirical fingerprinting is currently one of the most efficient localization methods in indoor environments, due to the now ubiquitous deployment of wireless local area networks. A fingerprint is the pattern of received signal strengths from all the access points visible at a particular position. Reference fingerprints are obtained from extensive measurement campaigns and used during an offline phase to construct suitable radio maps of the environment of interest. However, this approach is very site-specific and the radio maps require therefore to be regularly updated in order to take into account changes in the environment, i.e. a labor-intensive and time-consuming task. Hence, ray-tracing simulations are instead used in this paper to construct these radio maps based on deterministic prediction of the radio wave propagation. To validate this approach, field experiments were conducted in an indoor office environment. The results show (i): the sensitivity of fingerprints to small-scale fading and human shadowing, as well as (ii): good agreement between the measured and ray-tracing simulated fingerprints, especially with strong line-of-sight.","PeriodicalId":240036,"journal":{"name":"2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115375514","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: 8

Bayesian Learning Based Millimeter-Wave Sparse Channel Estimation with Hybrid Antenna Array 基于贝叶斯学习的混合天线阵列毫米波稀疏信道估计

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445972

M. Aminu, M. Codreanu, M. Juntti

{"title":"Bayesian Learning Based Millimeter-Wave Sparse Channel Estimation with Hybrid Antenna Array","authors":"M. Aminu, M. Codreanu, M. Juntti","doi":"10.1109/SPAWC.2018.8445972","DOIUrl":"https://doi.org/10.1109/SPAWC.2018.8445972","url":null,"abstract":"We consider the problem of millimeter-wave (mmWave) channel estimation with a hybrid digital-analog two-stage beamforming structure. A radio frequency (RF) chain excites a dedicated set of antenna subarrays. To compensate for the severe path loss, known training signals are beamformed and swept to scan the angular space. Since the mmWave channels typically exhibit sparsity, the channel response can usually be expressed as a linear combination of a small number of scattering clusters. Thereby the number of angles of arrival (AoAs) and angles of departure (AoDs) with significant signal components is limited, and compressive sensing techniques can be leveraged for estimating the channel. In this paper, we investigate two sparse recovery algorithms: a Bayesian and non-Bayesian one. In the Bayesian approach, we invoke the sparse Bayesian learning (SBL) framework, which relies on a 2-layer hierarchical prior model for channel. A highly efficient and fast iterative Bayesian inference method is then applied to the proposed model. The non-Bayesian approach is a LASSO-based approach, where we devise a low complexity solution by adopting alternating directions method of multipliers (ADMM) technique to solve the problem. The efficacy of the proposed algorithms is demonstrated using numerical examples. The Bayesian approach shows improved estimation performance in relation to the non-Bayesian approach.","PeriodicalId":240036,"journal":{"name":"2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124352940","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

Information Aging Through Queues: A Mutual Information Perspective 通过队列的信息老化:一个相互信息的视角

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445873

Yin Sun, Benjamin Cyr

引用次数: 64

Limited Feedback Double Directional Massive MIMO Channel Estimation: From Low-Rank Modeling to Deep Learning 有限反馈双向大规模MIMO信道估计:从低秩建模到深度学习

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8446005

Haoran Sun, Ziping Zhao, Xiao Fu, Mingyi Hong

{"title":"Limited Feedback Double Directional Massive MIMO Channel Estimation: From Low-Rank Modeling to Deep Learning","authors":"Haoran Sun, Ziping Zhao, Xiao Fu, Mingyi Hong","doi":"10.1109/SPAWC.2018.8446005","DOIUrl":"https://doi.org/10.1109/SPAWC.2018.8446005","url":null,"abstract":"In frequency division duplex massive MIMO systems, one critical challenge is that the mobiles need to feed back a large downlink channel matrix to the base station, creating large signaling overhead. Estimating a large downlink channel matrix at the mobile may also be costly in terms of power and memory consumption. Prior work addresses these issues using appropriate angle parameterization and compressed sensing techniques, but this approach involves solving a challenging, and sometimes extremely large, sparse inverse problem-which is difficult to solve to global optimality, and often leads to unaffordable memory and computational costs. In this work, we propose an alternative framework that explores the fact that double directional channels for mmWave massive MIMO usually have low rank. The base station estimates the downlink channel via recovering a low-rank matrix, utilizing samples of the channel matrix compressed and fed back from the mobiles. This way, the mobile users can avoid performing resource-consuming tasks. In addition, the number of feedback measurements can be much smaller than the size of the channel matrix without losing channel recovery guarantees. Further, the low-rank estimation problem at the base station has a manageable size that scales gracefully with the channel size. Based on the new model, we propose two methods for channel estimation, which are based on iterative optimization and deep learning, respectively. Compared with the state-of-the-art, the optimization method obtains 10x improvement and the deep learning approach achieves up to 1000x improvement in computational complexity, while achieving high estimation quality in very low sample region.","PeriodicalId":240036,"journal":{"name":"2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122494343","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: 27

Optimizing Reciprocity-Based Backscattering with a Full-Duplex Antenna Array Reader 利用全双工天线阵列读取器优化基于往复的后向散射

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) Pub Date : 2018-06-01 DOI: 10.1109/SPAWC.2018.8445886

Deepak Mishra, E. Larsson

引用次数: 9