2013 IEEE Global Conference on Signal and Information Processing最新文献

Adaptive digital pre-distortion for multiple antenna transmitters 多天线发射机的自适应数字预失真

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-23 DOI: 10.1109/GlobalSIP.2013.6737109

P. Suryasarman, A. Springer

{"title":"Adaptive digital pre-distortion for multiple antenna transmitters","authors":"P. Suryasarman, A. Springer","doi":"10.1109/GlobalSIP.2013.6737109","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6737109","url":null,"abstract":"This paper proposes adaptive algorithms to implement a cross-talk canceling pre-distorter (CTC-DPD), which accurately models the cross-talk and nonlinearity in multiple-input multiple-output (MIMO) radio systems, and compensates for these effects. The cross-talk introduced before the power amplifier (PA) in a multi-antenna transmitter, which is termed as non-linear cross-talk, degrades the performance of digital pre-distortion (DPD). A cross-over pre-distortion (CO-DPD) that compensates for the cross-talk and non-linearity in multi-antenna transmitters was proposed in [2]. However, CO-DPD ignores the higher order cross-terms between the input signals. As a result, the performance of CO-DPD degrades, as the crosstalk between the branches of the multi-antenna transmitter becomes stronger. A CTC-DPD structure which out-performs CO-DPD especially at high cross-talk levels, was proposed in [5]. In this paper, an indirect learning architecture for CTC-DPD with Recursive least square (RLS) pre-distortion and cross-talk cancellation, and three methods for cross-talk estimation are proposed. From simulations using a memory polynomial model of order 7 and memory length 3 for the PAs, it is found that CTC-DPD achieves a normalised mean square error (NMSE) less than -70 dB for cross-talk levels up to -15 dB, for a 2 antenna MIMO transmitter. This performance is similar to that of conventional DPDs in the case with no cross-talk.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131494714","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: 14

MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics 偏头痛:核磁共振图像可靠性分析和连接组推断

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-17 DOI: 10.1109/GlobalSIP.2013.6736878

William Gray Roncal, Zachary H. Koterba, Disa Mhembere, D. Kleissas, J. Vogelstein, R. Burns, A. Bowles, Dimitrios K. Donavos, S. Ryman, R. Jung, Lei Wu, V. Calhoun, R. J. Vogelstein

引用次数: 50

Vulnerability of LTE to hostile interference LTE对敌对干扰的脆弱性

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-12 DOI: 10.1109/GlobalSIP.2013.6736871

Marc Lichtman, Jeffrey H. Reed, T. Clancy, M. Norton

引用次数: 78

Networks as signals, with an application to a bike sharing system 网络作为信号，应用于自行车共享系统

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-03 DOI: 10.1109/GlobalSIP.2013.6736952

Ronan Hamon, P. Borgnat, P. Flandrin, C. Robardet

引用次数: 18

Providing disruption QoS in an OFDM system using Residual Idle Time Based opportunistic spectrum access 利用基于剩余空闲时间的机会频谱接入在OFDM系统中提供中断QoS

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-03 DOI: 10.1109/GlobalSIP.2013.6737124

A. Sahoo, M. Souryal, M. Ranganathan

引用次数: 1

Blind collaborative 20 questions for target localization 盲合作目标定位的20个问题

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-03 DOI: 10.1109/GlobalSIP.2013.6736840

Theodoros Tsiligkaridis, Brian M. Sadler, A. Hero

{"title":"Blind collaborative 20 questions for target localization","authors":"Theodoros Tsiligkaridis, Brian M. Sadler, A. Hero","doi":"10.1109/GlobalSIP.2013.6736840","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736840","url":null,"abstract":"We consider the problem of collaborative target localization by several observers, called players, where the reliability of each player is unknown. As in our previous work [1] we formulate this problem as a 20 questions game with noise for collaborative players under a minimum entropy criterion. We extend the setting of [1] to the case where the players' error channels have unknown crossover probabilities. First, we use dynamic programming to characterize the structure of the optimal policy for constructing the sequence of questions. This generalizes the multiplayer policies derived in [1] for the known error channel setting. Second, we prove a separation theorem showing that a sequential bisection scheme achieves the same performance as the optimal joint queries. This generalizes the separation theorem recently derived for the known error channel case in [1]. Third, we derive bounds for the maximum entropy loss per iteration. Finally, we show that even for the one-dimensional case, the optimal query policy for the unknown error channel is not equivalent to a probabilistic bisection policy. This framework provides a methodology for simultaneous sequential estimation of target location and learning the error channels associated with the players.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132969107","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

Least laxity first scheduling of thermostatically controlled loads for regulation services 调节服务中恒温控制负荷的最小松弛优先调度

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736925

M. Alizadeh, A. Scaglione

引用次数: 9

Optimal index policies for quickest localization of anomaly in cyber networks 网络异常快速定位的最优索引策略

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736855

Kobi Cohen, Qing Zhao, A. Swami

{"title":"Optimal index policies for quickest localization of anomaly in cyber networks","authors":"Kobi Cohen, Qing Zhao, A. Swami","doi":"10.1109/GlobalSIP.2013.6736855","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736855","url":null,"abstract":"We consider the problem of quickest localization of anomaly in a resource-constrained cyber network consisting of multiple components. Due to resource constraints, only one component can be probed at each time. The observations are random realizations drawn from two different distributions depending on whether the component is normal or anomalous. Components are assigned priorities. Components with higher priorities in an abnormal state should be fixed before components with lower priorities to reduce the overall damage to the network. The objective is to minimize the expected weighted sum of completion times of abnormal components subject to error probability constraints. We consider two different anomaly models: the independent model in which each component can be abnormal independent of other components, and the exclusive model in which there is one and only one abnormal component. We develop index policies under both models. Optimal low-complexity algorithms are derived for the simple hypotheses case, where the distribution is completely known under both hypotheses. Asymptotically (as the error probability approaches zero) optimal low-complexity algorithms are derived for the composite hypotheses case, where there is uncertainty in the distribution parameters. Simulation results then illustrate the performance of the algorithms.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"518 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123691007","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: 9

Diffusion estimation over cooperative networks with missing data 缺失数据下合作网络的扩散估计

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736902

M. R. Gholami, E. Ström, A. H. Sayed

{"title":"Diffusion estimation over cooperative networks with missing data","authors":"M. R. Gholami, E. Ström, A. H. Sayed","doi":"10.1109/GlobalSIP.2013.6736902","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2013.6736902","url":null,"abstract":"In many fields, and especially in the medical and social sciences and in various recommender systems, data are often gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they may lack information to respond adequately to the questions. The data collected from these studies tend to lead to linear regression models where the regression vectors are only known partially: some of their entries are either missing completely or replaced randomly by noisy values. There are also situations where it is not known beforehand which entries are missing or censored. There have been many useful studies in the literature on techniques to perform estimation and inference with missing data. In this work, we examine how a connected network of agents, with each one of them subjected to a stream of data with incomplete regression information, can cooperate with each other through local interactions to estimate the underlying model parameters in the presence of missing data. We explain how to modify traditional distributed strategies through regularization in order to eliminate the bias introduced by the incomplete model. We also examine the stability and performance of the resulting diffusion strategy and provide simulations in support of the findings. We consider two applications: one dealing with a mental health survey and the other dealing with a household consumption survey.","PeriodicalId":311464,"journal":{"name":"2013 IEEE Global Conference on Signal and Information Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114957919","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: 7

Inference in time series of graphs using locality statistics 用局域统计进行时间序列图的推理

2013 IEEE Global Conference on Signal and Information Processing Pub Date : 2013-12-01 DOI: 10.1109/GlobalSIP.2013.6736917

Heng Wang, M. Tang, C. Priebe, Youngser Park

引用次数: 1