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GlobalSIP 2019

The 7th 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.

VayuAnukulani: Adaptive memory networks for air pollution forecasting


Air pollution is the leading environmental health hazard globally due to various sources which include factory emissions, car exhaust and cooking stoves. As a precautionary measure, air pollution forecast serves as the basis for taking effective pollution control measures, and accurate air pollution forecasting has become an important task. In this paper, we forecast fine-grained ambient air quality information for 5 prominent locations in Delhi based on the historical and realtime ambient air quality and meteorological data reported by Central Pollution Control board.

Paper Details

Authors:
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall
Submitted On:
13 November 2019 - 9:53am
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[1] Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall, "VayuAnukulani: Adaptive memory networks for air pollution forecasting", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4917. Accessed: Dec. 15, 2019.
@article{4917-19,
url = {http://sigport.org/4917},
author = {Divyam Madaan; Radhika Dua; Prerana Mukherjee; Brejesh Lall },
publisher = {IEEE SigPort},
title = {VayuAnukulani: Adaptive memory networks for air pollution forecasting},
year = {2019} }
TY - EJOUR
T1 - VayuAnukulani: Adaptive memory networks for air pollution forecasting
AU - Divyam Madaan; Radhika Dua; Prerana Mukherjee; Brejesh Lall
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4917
ER -
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. (2019). VayuAnukulani: Adaptive memory networks for air pollution forecasting. IEEE SigPort. http://sigport.org/4917
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall, 2019. VayuAnukulani: Adaptive memory networks for air pollution forecasting. Available at: http://sigport.org/4917.
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. (2019). "VayuAnukulani: Adaptive memory networks for air pollution forecasting." Web.
1. Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. VayuAnukulani: Adaptive memory networks for air pollution forecasting [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4917

Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System


The 3GPP is investigating the concept of integrated access and backhaul (IAB) to provide high capacity wireless backhaul for 5G network. In this paper, we present an analysis of ergodic capacity for full-duplex IAB system, where full-duplex is introduced to further improve the ergodic capacity. Two kinds of interference are considered: the backward interference between two adjacent base stations and the residual self-interference introduced by full-duplex.

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Authors:
Xiaoqian Zhang, Fangfang Liu, Hailun Xia
Submitted On:
8 November 2019 - 9:46pm
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Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System.pptx

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[1] Xiaoqian Zhang, Fangfang Liu, Hailun Xia, "Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4915. Accessed: Dec. 15, 2019.
@article{4915-19,
url = {http://sigport.org/4915},
author = {Xiaoqian Zhang; Fangfang Liu; Hailun Xia },
publisher = {IEEE SigPort},
title = {Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System},
year = {2019} }
TY - EJOUR
T1 - Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System
AU - Xiaoqian Zhang; Fangfang Liu; Hailun Xia
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4915
ER -
Xiaoqian Zhang, Fangfang Liu, Hailun Xia. (2019). Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System. IEEE SigPort. http://sigport.org/4915
Xiaoqian Zhang, Fangfang Liu, Hailun Xia, 2019. Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System. Available at: http://sigport.org/4915.
Xiaoqian Zhang, Fangfang Liu, Hailun Xia. (2019). "Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System." Web.
1. Xiaoqian Zhang, Fangfang Liu, Hailun Xia. Ergodic Capacity Analysis for Full-Duplex Integrated Access and Backhaul System [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4915

Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach

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Authors:
C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel
Submitted On:
13 November 2019 - 11:22am
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[1] C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel, "Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4914. Accessed: Dec. 15, 2019.
@article{4914-19,
url = {http://sigport.org/4914},
author = {C. Chatzichristos; M. Vandecapelle; E. Kofidis; S. Theodoridis; L. De Lathauwer and S. Van Huffel },
publisher = {IEEE SigPort},
title = {Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach},
year = {2019} }
TY - EJOUR
T1 - Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach
AU - C. Chatzichristos; M. Vandecapelle; E. Kofidis; S. Theodoridis; L. De Lathauwer and S. Van Huffel
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4914
ER -
C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel. (2019). Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach. IEEE SigPort. http://sigport.org/4914
C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel, 2019. Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach. Available at: http://sigport.org/4914.
C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel. (2019). "Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach." Web.
1. C. Chatzichristos, M. Vandecapelle, E. Kofidis, S. Theodoridis, L. De Lathauwer and S. Van Huffel. Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption – A β-Divergence Approach [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4914

A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic


Abstract—To satisfy the strict latency requirement of Ultra Reliable Low Latency Communications (URLLC) traffic, it is usually scheduled on resources occupied by enhanced Mobile Broadband (eMBB) transmissions at the expense of a highly degraded eMBB spectral efficiency (SE). In this paper, we propose a back propagation neural network (BPNN) based punctured scheduling scheme to address the URLLC placement problem on eMBB traffic within mini-slots.

Paper Details

Authors:
Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao
Submitted On:
5 November 2019 - 3:55am
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GlobalSIP-Shangqingqing-PPT.pptx

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[1] Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao, "A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4913. Accessed: Dec. 15, 2019.
@article{4913-19,
url = {http://sigport.org/4913},
author = {Qingqing Shang; Fangfang Liu; Chunyan Feng; Ruiyi Zhang and Shulun Zhao },
publisher = {IEEE SigPort},
title = {A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic},
year = {2019} }
TY - EJOUR
T1 - A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic
AU - Qingqing Shang; Fangfang Liu; Chunyan Feng; Ruiyi Zhang and Shulun Zhao
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4913
ER -
Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao. (2019). A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic. IEEE SigPort. http://sigport.org/4913
Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao, 2019. A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic. Available at: http://sigport.org/4913.
Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao. (2019). "A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic." Web.
1. Qingqing Shang, Fangfang Liu, Chunyan Feng, Ruiyi Zhang and Shulun Zhao. A BP Neural Network Based Punctured Scheduling Scheme Within Mini-slots for Joint URLLC and eMBB Traffic [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4913

A Novel Blurring based Method for Video Compression

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4 November 2019 - 11:35pm
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Video Compression Poster

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[1] , "A Novel Blurring based Method for Video Compression ", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4912. Accessed: Dec. 15, 2019.
@article{4912-19,
url = {http://sigport.org/4912},
author = { },
publisher = {IEEE SigPort},
title = {A Novel Blurring based Method for Video Compression },
year = {2019} }
TY - EJOUR
T1 - A Novel Blurring based Method for Video Compression
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4912
ER -
. (2019). A Novel Blurring based Method for Video Compression . IEEE SigPort. http://sigport.org/4912
, 2019. A Novel Blurring based Method for Video Compression . Available at: http://sigport.org/4912.
. (2019). "A Novel Blurring based Method for Video Compression ." Web.
1. . A Novel Blurring based Method for Video Compression [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4912

On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery


Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous methods for signal recovery over an orthonormal basis. However, modern applications have sparked the emergence of related methods for signals not sparse in an orthonormal basis but in some arbitrary, perhaps highly overcomplete, dictionary, particularly due to their potential to generate different kinds of sparse representation of signals.

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4 November 2019 - 10:52pm
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GlobalSIP 2019 jianchen zhu(1)(1).pdf

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[1] , "On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4911. Accessed: Dec. 15, 2019.
@article{4911-19,
url = {http://sigport.org/4911},
author = { },
publisher = {IEEE SigPort},
title = {On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery},
year = {2019} }
TY - EJOUR
T1 - On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4911
ER -
. (2019). On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery. IEEE SigPort. http://sigport.org/4911
, 2019. On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery. Available at: http://sigport.org/4911.
. (2019). "On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery." Web.
1. . On theoretical optimization of the sensing matrix for sparse-dictionary signal recovery [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4911

Incentivizing Crowdsourced Workers via Truth Detection


Crowdsourcing platforms often want to incentivize workers to finish tasks with high quality and truthfully report their solutions. A high-quality solution requires a worker to exert effort; a platform can motivate such effort exertion and truthful reporting by providing a reward.

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Authors:
Haoran Yu, Jianwei Huang, Randall A Berry
Submitted On:
4 November 2019 - 10:19pm
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[1] Haoran Yu, Jianwei Huang, Randall A Berry, "Incentivizing Crowdsourced Workers via Truth Detection", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4910. Accessed: Dec. 15, 2019.
@article{4910-19,
url = {http://sigport.org/4910},
author = {Haoran Yu; Jianwei Huang; Randall A Berry },
publisher = {IEEE SigPort},
title = {Incentivizing Crowdsourced Workers via Truth Detection},
year = {2019} }
TY - EJOUR
T1 - Incentivizing Crowdsourced Workers via Truth Detection
AU - Haoran Yu; Jianwei Huang; Randall A Berry
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4910
ER -
Haoran Yu, Jianwei Huang, Randall A Berry. (2019). Incentivizing Crowdsourced Workers via Truth Detection. IEEE SigPort. http://sigport.org/4910
Haoran Yu, Jianwei Huang, Randall A Berry, 2019. Incentivizing Crowdsourced Workers via Truth Detection. Available at: http://sigport.org/4910.
Haoran Yu, Jianwei Huang, Randall A Berry. (2019). "Incentivizing Crowdsourced Workers via Truth Detection." Web.
1. Haoran Yu, Jianwei Huang, Randall A Berry. Incentivizing Crowdsourced Workers via Truth Detection [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4910

Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering


Power delay profiles (PDPs) are an important factor in the design of wireless networks, e.g., in choosing the length of a cyclic prefix. While distributed networks are receiving increasing attention, the impact of cooperation on the PDP has not been addressed. We address this issue in this paper. Specifically, we analyze a network where each user is served by a cluster of Remote Radio Heads (RRHs) with RRH locations modeled as a Poisson point process.

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Authors:
Raviraj Adve
Submitted On:
13 November 2019 - 11:43am
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Presentation material for IEEE GlobalSIP2019

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[1] Raviraj Adve, "Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4909. Accessed: Dec. 15, 2019.
@article{4909-19,
url = {http://sigport.org/4909},
author = {Raviraj Adve },
publisher = {IEEE SigPort},
title = {Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering},
year = {2019} }
TY - EJOUR
T1 - Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering
AU - Raviraj Adve
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4909
ER -
Raviraj Adve. (2019). Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering. IEEE SigPort. http://sigport.org/4909
Raviraj Adve, 2019. Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering. Available at: http://sigport.org/4909.
Raviraj Adve. (2019). "Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering." Web.
1. Raviraj Adve. Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4909

GOP Level Quality Dependency Based Frame Level Rate Control Algorithm


This paper proposes a rate control algorithm based on group of pictures (GOP) level quality dependency for high efficiency video coding (HEVC) low delay hierarchical coding structure. Firstly, this paper builds a GOP level quality dependency model. Secondly, a GOP level quality dependency model based GOP level rate-distortion optimization is introduced to make bit allocation more reasonable.

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Authors:
Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan
Submitted On:
7 November 2019 - 12:58am
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Poster PDF of GOP Level Quality Dependency Based Frame Level Rate Control Algorithm

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[1] Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan, "GOP Level Quality Dependency Based Frame Level Rate Control Algorithm", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4907. Accessed: Dec. 15, 2019.
@article{4907-19,
url = {http://sigport.org/4907},
author = {Guanwen Zhang; Henglu Wei; Wei Zhou; Zhemin Duan },
publisher = {IEEE SigPort},
title = {GOP Level Quality Dependency Based Frame Level Rate Control Algorithm},
year = {2019} }
TY - EJOUR
T1 - GOP Level Quality Dependency Based Frame Level Rate Control Algorithm
AU - Guanwen Zhang; Henglu Wei; Wei Zhou; Zhemin Duan
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4907
ER -
Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan. (2019). GOP Level Quality Dependency Based Frame Level Rate Control Algorithm. IEEE SigPort. http://sigport.org/4907
Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan, 2019. GOP Level Quality Dependency Based Frame Level Rate Control Algorithm. Available at: http://sigport.org/4907.
Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan. (2019). "GOP Level Quality Dependency Based Frame Level Rate Control Algorithm." Web.
1. Guanwen Zhang, Henglu Wei, Wei Zhou, Zhemin Duan. GOP Level Quality Dependency Based Frame Level Rate Control Algorithm [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4907

Data Driven QoE-QoS Association Modeling of Conversational Video


In recent years, the variety and volume of multimedia services have increased exponentially. Like most of other multimedia services, the conversational video service has stringent quality of service and experience requirements. In order to better support users QoE (Quality of Experience) and allocate network resources more effectively, this paper focuses on the QoS (Quality of Service)-QoE association modeling of conversational video flows.

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29 October 2019 - 11:08pm
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Data Driven QoE-QoS Association Modeling of Conversational Video - upload.pptx

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[1] , "Data Driven QoE-QoS Association Modeling of Conversational Video", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4901. Accessed: Dec. 15, 2019.
@article{4901-19,
url = {http://sigport.org/4901},
author = { },
publisher = {IEEE SigPort},
title = {Data Driven QoE-QoS Association Modeling of Conversational Video},
year = {2019} }
TY - EJOUR
T1 - Data Driven QoE-QoS Association Modeling of Conversational Video
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4901
ER -
. (2019). Data Driven QoE-QoS Association Modeling of Conversational Video. IEEE SigPort. http://sigport.org/4901
, 2019. Data Driven QoE-QoS Association Modeling of Conversational Video. Available at: http://sigport.org/4901.
. (2019). "Data Driven QoE-QoS Association Modeling of Conversational Video." Web.
1. . Data Driven QoE-QoS Association Modeling of Conversational Video [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4901

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