Sorry, you need to enable JavaScript to visit this website.

GlobalSIP 2018

The 6th IEEE Global Conference on Signal and Information Processing (GlobalSIP)  focuses on signal and information processing with an emphasis on up-and-coming signal processing themes. The conference features world-class plenary speeches, distinguished symposium talks, tutorials, exhibits, oral and poster sessions, and panels. GlobalSIP is comprised of co-located General Symposium and symposia selected based on responses to the call-for-symposia proposals.

Rumour Source Detection in Social Networks using Partial Observations

Paper Details

Authors:
Submitted On:
22 November 2018 - 9:30am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

globalsip18.pdf

(78)

Keywords

Additional Categories

Subscribe

[1] , "Rumour Source Detection in Social Networks using Partial Observations", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3716. Accessed: Sep. 20, 2019.
@article{3716-18,
url = {http://sigport.org/3716},
author = { },
publisher = {IEEE SigPort},
title = {Rumour Source Detection in Social Networks using Partial Observations},
year = {2018} }
TY - EJOUR
T1 - Rumour Source Detection in Social Networks using Partial Observations
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3716
ER -
. (2018). Rumour Source Detection in Social Networks using Partial Observations. IEEE SigPort. http://sigport.org/3716
, 2018. Rumour Source Detection in Social Networks using Partial Observations. Available at: http://sigport.org/3716.
. (2018). "Rumour Source Detection in Social Networks using Partial Observations." Web.
1. . Rumour Source Detection in Social Networks using Partial Observations [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3716

JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH


Compared with traditional device-to-device (D2D) communication networks, the users in the cache-enabled D2D communication networks can easily obtain their requested contentsfromthenearbyusers,andreducethebackhaulcosts. In this paper, we investigate the caching strategy for the cacheenabled D2D communication networks, with the consideration of caching placement and caching delivery. The content popularity and user mobility are predicted by a machine learning approach of echo state networks (ESNs) in order to determine which content to cache and where to cache.

Paper Details

Authors:
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han
Submitted On:
27 March 2019 - 9:05am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP_YJY.pdf

(35)

Subscribe

[1] Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han, "JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3715. Accessed: Sep. 20, 2019.
@article{3715-18,
url = {http://sigport.org/3715},
author = {Jiaying Yin; Lixin Li; Yang Xu; Wei Liang; Huisheng Zhang; and Zhu Han },
publisher = {IEEE SigPort},
title = {JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH},
year = {2018} }
TY - EJOUR
T1 - JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH
AU - Jiaying Yin; Lixin Li; Yang Xu; Wei Liang; Huisheng Zhang; and Zhu Han
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3715
ER -
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. (2018). JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH. IEEE SigPort. http://sigport.org/3715
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han, 2018. JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH. Available at: http://sigport.org/3715.
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. (2018). "JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH." Web.
1. Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3715

Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks

Paper Details

Authors:
Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu
Submitted On:
22 November 2018 - 8:27am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP2018_Chensheng.pdf

(50)

Subscribe

[1] Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu, "Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3714. Accessed: Sep. 20, 2019.
@article{3714-18,
url = {http://sigport.org/3714},
author = {Sheng Chen; Zhiyuan Jiang; Sheng Zhou; Zhisheng Niu },
publisher = {IEEE SigPort},
title = {Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks},
year = {2018} }
TY - EJOUR
T1 - Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks
AU - Sheng Chen; Zhiyuan Jiang; Sheng Zhou; Zhisheng Niu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3714
ER -
Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu. (2018). Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks. IEEE SigPort. http://sigport.org/3714
Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu, 2018. Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks. Available at: http://sigport.org/3714.
Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu. (2018). "Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks." Web.
1. Sheng Chen, Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu. Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3714

Generalized Graph Signal Processing

Paper Details

Authors:
Feng Ji, Wee Peng Tay
Submitted On:
22 November 2018 - 7:23am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Globalsip.pdf

(2119)

Subscribe

[1] Feng Ji, Wee Peng Tay, "Generalized Graph Signal Processing", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3713. Accessed: Sep. 20, 2019.
@article{3713-18,
url = {http://sigport.org/3713},
author = {Feng Ji; Wee Peng Tay },
publisher = {IEEE SigPort},
title = {Generalized Graph Signal Processing},
year = {2018} }
TY - EJOUR
T1 - Generalized Graph Signal Processing
AU - Feng Ji; Wee Peng Tay
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3713
ER -
Feng Ji, Wee Peng Tay. (2018). Generalized Graph Signal Processing. IEEE SigPort. http://sigport.org/3713
Feng Ji, Wee Peng Tay, 2018. Generalized Graph Signal Processing. Available at: http://sigport.org/3713.
Feng Ji, Wee Peng Tay. (2018). "Generalized Graph Signal Processing." Web.
1. Feng Ji, Wee Peng Tay. Generalized Graph Signal Processing [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3713

GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks


A terrestrial network deployment with mobile cell connectivity using a bandwidth limited satellite backhaul is being investigated in terms of the integration of state-of-the-art 4G commercial off-the-shelf network components. A testbed is analyzed for providing end-to-end quality of service and flexible resource allocation on the satellite link using a novel multi-carrier modem technology with dynamic bandwidth allocation.

Paper Details

Authors:
Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann
Submitted On:
23 November 2018 - 3:47am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP_2018_Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks.pptx

(30)

Subscribe

[1] Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann, "GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3712. Accessed: Sep. 20, 2019.
@article{3712-18,
url = {http://sigport.org/3712},
author = {Robert T. Schwarz; Mario Lorenz; Andreas Knopp; Markus Landmann },
publisher = {IEEE SigPort},
title = {GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks},
year = {2018} }
TY - EJOUR
T1 - GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks
AU - Robert T. Schwarz; Mario Lorenz; Andreas Knopp; Markus Landmann
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3712
ER -
Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann. (2018). GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks. IEEE SigPort. http://sigport.org/3712
Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann, 2018. GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks. Available at: http://sigport.org/3712.
Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann. (2018). "GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks." Web.
1. Robert T. Schwarz, Mario Lorenz, Andreas Knopp, Markus Landmann. GlobalSIP 2018: Concept and Evaluation of Mobile Cell Connectivity over a Satellite Backhaul for Future 5G Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3712

DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS


The knowledge of the downlink (DL) channel spatial covariance matrix at the BS is of fundamental importance for large-scale array systems operating in frequency division duplexing (FDD) mode. In particular, this knowledge plays a key role in the DL channel state information (CSI) acquisition. In the massive MIMO regime, traditional schemes based on DL pilots are severely limited by the covariance feedback and the DL training overhead. To overcome this problem, many authors have proposed to obtain an estimate of the DL spatial covariance based on uplink (UL) measurements.

Paper Details

Authors:
Renato L.G. Cavalcante, Slawomir Stanczak
Submitted On:
22 November 2018 - 5:17am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

Poster_GlobalSIP.pdf

(62)

Subscribe

[1] Renato L.G. Cavalcante, Slawomir Stanczak, "DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3711. Accessed: Sep. 20, 2019.
@article{3711-18,
url = {http://sigport.org/3711},
author = {Renato L.G. Cavalcante; Slawomir Stanczak },
publisher = {IEEE SigPort},
title = {DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS},
year = {2018} }
TY - EJOUR
T1 - DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS
AU - Renato L.G. Cavalcante; Slawomir Stanczak
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3711
ER -
Renato L.G. Cavalcante, Slawomir Stanczak. (2018). DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS. IEEE SigPort. http://sigport.org/3711
Renato L.G. Cavalcante, Slawomir Stanczak, 2018. DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS. Available at: http://sigport.org/3711.
Renato L.G. Cavalcante, Slawomir Stanczak. (2018). "DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS." Web.
1. Renato L.G. Cavalcante, Slawomir Stanczak. DOWNLINK CHANNEL SPATIAL COVARIANCE ESTIMATION IN REALISTIC FDD MASSIVE MIMO SYSTEMS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3711

Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees


We consider a bi-directional Full-Duplex (FD) Multiple-Input Multiple-Output (MIMO) communication system in which nodes are capable of performing transitter (TX)- Receiver (RX) digital precoding/combining and multi-tap analog cancellation, and have individual Signal-to-Interference-plus- noise Ratio (SINR) requirements. We present an iterative algorithm for the TX powers minimization that includes closed- form expressions for the TX/RX digital beamformers at each algorithmic iteration step.

Paper Details

Authors:
Submitted On:
22 November 2018 - 4:46am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees

(49)

Subscribe

[1] , "Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3710. Accessed: Sep. 20, 2019.
@article{3710-18,
url = {http://sigport.org/3710},
author = { },
publisher = {IEEE SigPort},
title = {Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees},
year = {2018} }
TY - EJOUR
T1 - Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3710
ER -
. (2018). Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees. IEEE SigPort. http://sigport.org/3710
, 2018. Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees. Available at: http://sigport.org/3710.
. (2018). "Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees." Web.
1. . Full-Duplex Transmission Optimization for Bi-directional MIMO links with QoS Guarantees [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3710

Consensus Optimization for Distributed Registration


We consider the problem of jointly registering multiple point sets using rigid transforms. We propose a distributed algorithm based on consensus optimization for the least-squares formulation of this problem. In each iteration, the computation is distributed among the point sets and the results are averaged. For each point set, the dominant cost per iteration is the SVD of a square matrix of size d, where d is the ambient dimension. Existing methods for joint registration are either centralized or perform the optimization sequentially.

Paper Details

Authors:
Kunal N. Chaudhury
Submitted On:
21 November 2018 - 10:16pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

We propose a distributed algorithm based on consensus optimization for the registering multiple point-clouds.

(36)

Subscribe

[1] Kunal N. Chaudhury, "Consensus Optimization for Distributed Registration", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3709. Accessed: Sep. 20, 2019.
@article{3709-18,
url = {http://sigport.org/3709},
author = {Kunal N. Chaudhury },
publisher = {IEEE SigPort},
title = {Consensus Optimization for Distributed Registration},
year = {2018} }
TY - EJOUR
T1 - Consensus Optimization for Distributed Registration
AU - Kunal N. Chaudhury
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3709
ER -
Kunal N. Chaudhury. (2018). Consensus Optimization for Distributed Registration. IEEE SigPort. http://sigport.org/3709
Kunal N. Chaudhury, 2018. Consensus Optimization for Distributed Registration. Available at: http://sigport.org/3709.
Kunal N. Chaudhury. (2018). "Consensus Optimization for Distributed Registration." Web.
1. Kunal N. Chaudhury. Consensus Optimization for Distributed Registration [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3709

Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment

Paper Details

Authors:
Kanke Wu, Pamela C. Cosman, Laurence B. Milstein
Submitted On:
21 November 2018 - 8:23pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System.pdf

(26)

Subscribe

[1] Kanke Wu, Pamela C. Cosman, Laurence B. Milstein, "Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3708. Accessed: Sep. 20, 2019.
@article{3708-18,
url = {http://sigport.org/3708},
author = {Kanke Wu; Pamela C. Cosman; Laurence B. Milstein },
publisher = {IEEE SigPort},
title = {Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment},
year = {2018} }
TY - EJOUR
T1 - Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment
AU - Kanke Wu; Pamela C. Cosman; Laurence B. Milstein
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3708
ER -
Kanke Wu, Pamela C. Cosman, Laurence B. Milstein. (2018). Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment. IEEE SigPort. http://sigport.org/3708
Kanke Wu, Pamela C. Cosman, Laurence B. Milstein, 2018. Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment. Available at: http://sigport.org/3708.
Kanke Wu, Pamela C. Cosman, Laurence B. Milstein. (2018). "Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment." Web.
1. Kanke Wu, Pamela C. Cosman, Laurence B. Milstein. Joint Partial-time Partial-band Jamming of a Multicarrier DS-CDMA System in a Fading Environment [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3708

Real-Time Power Outage Detection System using Social Sensing and Neural Networks

Paper Details

Authors:
Submitted On:
21 November 2018 - 7:49pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

Paper Presentation1.pdf

(29)

Subscribe

[1] , "Real-Time Power Outage Detection System using Social Sensing and Neural Networks ", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3707. Accessed: Sep. 20, 2019.
@article{3707-18,
url = {http://sigport.org/3707},
author = { },
publisher = {IEEE SigPort},
title = {Real-Time Power Outage Detection System using Social Sensing and Neural Networks },
year = {2018} }
TY - EJOUR
T1 - Real-Time Power Outage Detection System using Social Sensing and Neural Networks
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3707
ER -
. (2018). Real-Time Power Outage Detection System using Social Sensing and Neural Networks . IEEE SigPort. http://sigport.org/3707
, 2018. Real-Time Power Outage Detection System using Social Sensing and Neural Networks . Available at: http://sigport.org/3707.
. (2018). "Real-Time Power Outage Detection System using Social Sensing and Neural Networks ." Web.
1. . Real-Time Power Outage Detection System using Social Sensing and Neural Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3707

Pages