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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.

SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING

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23 November 2018 - 5:38am
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PosterGSIP-zahra.pdf

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[1] , "SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3740. Accessed: Dec. 16, 2018.
@article{3740-18,
url = {http://sigport.org/3740},
author = { },
publisher = {IEEE SigPort},
title = {SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING},
year = {2018} }
TY - EJOUR
T1 - SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3740
ER -
. (2018). SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING. IEEE SigPort. http://sigport.org/3740
, 2018. SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING. Available at: http://sigport.org/3740.
. (2018). "SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING." Web.
1. . SOURCE SEPARATION IN THE PRESENCE OF SIDE INFORMATION: NECESSARY AND SUFFICIENT CONDITIONS FOR RELIABLE DE-MIXING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3740

Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning

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Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi
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23 November 2018 - 3:41am
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[1] Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi, "Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3739. Accessed: Dec. 16, 2018.
@article{3739-18,
url = {http://sigport.org/3739},
author = {Mori haruki;Yuki Miyauchi; Kazuki Yamada; Shintaro Izumi; Masahiko Yoshimoto; Hiroshi Kawaguchi },
publisher = {IEEE SigPort},
title = {Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning},
year = {2018} }
TY - EJOUR
T1 - Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning
AU - Mori haruki;Yuki Miyauchi; Kazuki Yamada; Shintaro Izumi; Masahiko Yoshimoto; Hiroshi Kawaguchi
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3739
ER -
Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi. (2018). Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning. IEEE SigPort. http://sigport.org/3739
Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi, 2018. Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning. Available at: http://sigport.org/3739.
Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi. (2018). "Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning." Web.
1. Mori haruki,Yuki Miyauchi, Kazuki Yamada, Shintaro Izumi, Masahiko Yoshimoto, Hiroshi Kawaguchi. Delayed Weight Update for Faster Convergence in Data-parallel Deep Learning [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3739

DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC


This paper studies the application of Beam Hopping (BH) as a key enabler to provide high level of flexibility to manage scarce on-board resources, particularly power, based on the irregular and time variant traffic requests/demands distributed within the coverage of a satellite multibeam system. However, while high throughput full frequency reuse pattern is employed among beams, the performance of BH is significantly degraded due to the generated inter-beam interference, and applying precoding is essential. In this context, we propose Joint Precoding and BH (J-PBH) in a multibeam system.

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Authors:
Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten
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23 November 2018 - 2:37am
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poster_1337_Maturo.pdf

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[1] Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten, "DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3738. Accessed: Dec. 16, 2018.
@article{3738-18,
url = {http://sigport.org/3738},
author = {Vahid Joroughi; Eva Lagunas; Stefano Andrenacci; Nicola Maturo; Symeon Chatzinotas; Joel Grotz and Bjorn Ottersten },
publisher = {IEEE SigPort},
title = {DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC},
year = {2018} }
TY - EJOUR
T1 - DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC
AU - Vahid Joroughi; Eva Lagunas; Stefano Andrenacci; Nicola Maturo; Symeon Chatzinotas; Joel Grotz and Bjorn Ottersten
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3738
ER -
Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten. (2018). DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC. IEEE SigPort. http://sigport.org/3738
Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten, 2018. DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC. Available at: http://sigport.org/3738.
Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten. (2018). "DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC." Web.
1. Vahid Joroughi, Eva Lagunas, Stefano Andrenacci, Nicola Maturo, Symeon Chatzinotas, Joel Grotz and Bjorn Ottersten. DEPLOYING JOINT BEAM HOPPING AND PRECODING IN MULTIBEAM SATELLITE NETWORKS WITH TIME VARIANT TRAFFIC [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3738

Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition


It is well known that empirical mode decomposition can suffer from computational instabilities at the signal boundaries. These ``end effects'' cause two problems: 1) sifting termination issues, i.e.~convergence and 2) estimation error, i.e.~accuracy. In this paper, we propose to use linear prediction in conjunction with a previous method to address end effects, to further mitigate these problems.

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Authors:
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon
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26 November 2018 - 4:23pm
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GlobalSIP_2018_Poster___Mitigating_End_Effects.pdf

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[1] Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon, "Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3735. Accessed: Dec. 16, 2018.
@article{3735-18,
url = {http://sigport.org/3735},
author = {Steven Sandoval; Matthew Bredin; and Phillip L.~De Leon },
publisher = {IEEE SigPort},
title = {Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition},
year = {2018} }
TY - EJOUR
T1 - Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition
AU - Steven Sandoval; Matthew Bredin; and Phillip L.~De Leon
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3735
ER -
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. (2018). Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition. IEEE SigPort. http://sigport.org/3735
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon, 2018. Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition. Available at: http://sigport.org/3735.
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. (2018). "Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition." Web.
1. Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3735

Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model


It is well known that the empirical mode decomposition algorithm does not always return an appropriate decomposition due to problems like mode mixing. In this paper, we consider the problem of a component being split across several intrinsic mode functions (IMFs). We propose the use of a hidden Markov model (HMM) to track the dominant component across the set of IMFs returned by EMD.

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Authors:
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon
Submitted On:
26 November 2018 - 4:23pm
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Lecture___Dominant_Component_Tracking.pdf

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[1] Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon, "Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3734. Accessed: Dec. 16, 2018.
@article{3734-18,
url = {http://sigport.org/3734},
author = {Steven Sandoval; Matthew Bredin; and Phillip L.~De Leon },
publisher = {IEEE SigPort},
title = {Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model},
year = {2018} }
TY - EJOUR
T1 - Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model
AU - Steven Sandoval; Matthew Bredin; and Phillip L.~De Leon
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3734
ER -
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. (2018). Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model. IEEE SigPort. http://sigport.org/3734
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon, 2018. Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model. Available at: http://sigport.org/3734.
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. (2018). "Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model." Web.
1. Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon. Dominant Component Tracking for Empirical Mode Decomposition using a Hidden Markov Model [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3734

Single image super-resolution with limited number of filters


In this paper, we propose a single image super-resolution with limited number of filters based on RAISR. RAISR is well known as rapid and accurate super-resolution method which utilizes 864 filters for upscaling. This super-resolution idea utilizes the filter learned with sufficient training set. To get low cost of calculation and comparable image quality with other highly accurate super-resolution methods, the patch of input image is classified into classes by simple hash calculation.

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22 November 2018 - 11:51pm
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Single image super-resolution with limited number of filters.pptx

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[1] , "Single image super-resolution with limited number of filters", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3733. Accessed: Dec. 16, 2018.
@article{3733-18,
url = {http://sigport.org/3733},
author = { },
publisher = {IEEE SigPort},
title = {Single image super-resolution with limited number of filters},
year = {2018} }
TY - EJOUR
T1 - Single image super-resolution with limited number of filters
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3733
ER -
. (2018). Single image super-resolution with limited number of filters. IEEE SigPort. http://sigport.org/3733
, 2018. Single image super-resolution with limited number of filters. Available at: http://sigport.org/3733.
. (2018). "Single image super-resolution with limited number of filters." Web.
1. . Single image super-resolution with limited number of filters [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3733

BEM-based UKF Channel Estimation for 5G-enabled V2V Channel

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Authors:
Xuanfan Shen, Yong Liao, Xuewu Dai
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23 November 2018 - 8:20am
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GlobalSIP-1123.pdf

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[1] Xuanfan Shen, Yong Liao, Xuewu Dai, "BEM-based UKF Channel Estimation for 5G-enabled V2V Channel", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3730. Accessed: Dec. 16, 2018.
@article{3730-18,
url = {http://sigport.org/3730},
author = {Xuanfan Shen; Yong Liao; Xuewu Dai },
publisher = {IEEE SigPort},
title = {BEM-based UKF Channel Estimation for 5G-enabled V2V Channel},
year = {2018} }
TY - EJOUR
T1 - BEM-based UKF Channel Estimation for 5G-enabled V2V Channel
AU - Xuanfan Shen; Yong Liao; Xuewu Dai
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3730
ER -
Xuanfan Shen, Yong Liao, Xuewu Dai. (2018). BEM-based UKF Channel Estimation for 5G-enabled V2V Channel. IEEE SigPort. http://sigport.org/3730
Xuanfan Shen, Yong Liao, Xuewu Dai, 2018. BEM-based UKF Channel Estimation for 5G-enabled V2V Channel. Available at: http://sigport.org/3730.
Xuanfan Shen, Yong Liao, Xuewu Dai. (2018). "BEM-based UKF Channel Estimation for 5G-enabled V2V Channel." Web.
1. Xuanfan Shen, Yong Liao, Xuewu Dai. BEM-based UKF Channel Estimation for 5G-enabled V2V Channel [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3730

ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING


Without relative motion or beam scanning, orbitalangular-momentum (OAM)-based radar is shown to be able to estimate azimuth of targets, which opens a new perspective for traditional radar techniques. However, the existing application of two-dimensional (2-D) fast Fourier transform (FFT) and multiple signal classification (MUSIC) algorithms in OAM-based radar targets detection doesn’t realize 2-D super-resolution and robust estimation.

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Authors:
Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li
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22 November 2018 - 10:45pm
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ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL.pdf

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[1] Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li, "ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3729. Accessed: Dec. 16, 2018.
@article{3729-18,
url = {http://sigport.org/3729},
author = {Rui Chen; Wen-xuan Long; Yue Gao and Jiandong Li },
publisher = {IEEE SigPort},
title = {ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING},
year = {2018} }
TY - EJOUR
T1 - ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING
AU - Rui Chen; Wen-xuan Long; Yue Gao and Jiandong Li
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3729
ER -
Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li. (2018). ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING. IEEE SigPort. http://sigport.org/3729
Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li, 2018. ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING. Available at: http://sigport.org/3729.
Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li. (2018). "ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING." Web.
1. Rui Chen, Wen-xuan Long, Yue Gao and Jiandong Li. ORBITAL ANGULAR MOMENTUM-BASED TWO-DIMENSIONAL SUPER-RESOLUTION TARGETS IMAGING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3729

LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER


Satellite system is regarded as important part of 5G networks. Software Defined Satellite Networking (SDSN), utilizing the advantages of Software Defined Networking (SDN), as believed in former work, can provide better performance. Different SDN architectures based on either multi-layer satellite constellation or sing-layer constellation have been proposed and the key technology has been validated. However, characteristics of satellites such as high propagation delay and coverage characteristics pose some problems on the network performance.

poster2.pdf

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Authors:
Hefei Hu, Bihua Tang
Submitted On:
22 November 2018 - 9:35pm
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poster2.pdf

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[1] Hefei Hu, Bihua Tang, "LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3725. Accessed: Dec. 16, 2018.
@article{3725-18,
url = {http://sigport.org/3725},
author = {Hefei Hu; Bihua Tang },
publisher = {IEEE SigPort},
title = {LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER},
year = {2018} }
TY - EJOUR
T1 - LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER
AU - Hefei Hu; Bihua Tang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3725
ER -
Hefei Hu, Bihua Tang. (2018). LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER. IEEE SigPort. http://sigport.org/3725
Hefei Hu, Bihua Tang, 2018. LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER. Available at: http://sigport.org/3725.
Hefei Hu, Bihua Tang. (2018). "LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER." Web.
1. Hefei Hu, Bihua Tang. LEO SOFTWARE DEFINED NETWORKING BASED ON ONBOARD CONTROLLER [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3725

Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables


This work proposes a direct method to generate phase shift keying (PSK) symbols with desired correlation properties by mapping complex Gaussian random variables. The relationship between the cross-correlation of Gaussian and PSK symbols is derived in closed-form. This non-iterative approach outputs finite-alphabet constant-modulus waveforms capable of matching desired transmit beampatterns.

Poster.pdf

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Authors:
Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini
Submitted On:
22 November 2018 - 7:49pm
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Poster.pdf

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[1] Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini, "Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3724. Accessed: Dec. 16, 2018.
@article{3724-18,
url = {http://sigport.org/3724},
author = {Seifallah Jardak; Sajid Ahmed; Mohamed-Slim Alouini },
publisher = {IEEE SigPort},
title = {Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables},
year = {2018} }
TY - EJOUR
T1 - Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables
AU - Seifallah Jardak; Sajid Ahmed; Mohamed-Slim Alouini
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3724
ER -
Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini. (2018). Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables. IEEE SigPort. http://sigport.org/3724
Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini, 2018. Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables. Available at: http://sigport.org/3724.
Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini. (2018). "Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables." Web.
1. Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini. Generation of Correlated PSK Waveforms Using Complex Gaussian Random Variables [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3724

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