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Signal Processing for Communications and Networking

OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION


We consider a cooperative cognitive wireless network sce- nario where a primary wireless network is co-located with a cognitive (or secondary) network. In the considered scenario, the nodes of the secondary network make local binary de- cisions about the presence of a signal emitted by a primary node. Then, they transmit their decisions to a fusion center (FC). The final decision about the channel state is up to the FC by means of a proper fusion rule.

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Authors:
Andrea Abrardo
Submitted On:
23 February 2016 - 1:44pm
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[1] Andrea Abrardo, "OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION", IEEE SigPort, 2014. [Online]. Available: http://sigport.org/122. Accessed: Feb. 25, 2017.
@article{122-14,
url = {http://sigport.org/122},
author = {Andrea Abrardo },
publisher = {IEEE SigPort},
title = {OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION},
year = {2014} }
TY - EJOUR
T1 - OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION
AU - Andrea Abrardo
PY - 2014
PB - IEEE SigPort
UR - http://sigport.org/122
ER -
Andrea Abrardo. (2014). OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION. IEEE SigPort. http://sigport.org/122
Andrea Abrardo, 2014. OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION. Available at: http://sigport.org/122.
Andrea Abrardo. (2014). "OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION." Web.
1. Andrea Abrardo. OPTIMUM DECISION FUSION IN COGNITIVE WIRELESS SENSOR NETWORKS WITH UNKNOWN USERS LOCATION [Internet]. IEEE SigPort; 2014. Available from : http://sigport.org/122

SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL


We study the problem of remote reconstruction of a continuous signal from its multiple corrupted versions. We are interested in the optimal number of samples and their locations for each corrupted signal to minimize the total reconstruction distortion of the remote signal. The correlation among the corrupted signals can be utilized to reduce the sampling rate.

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7 December 2016 - 3:17am
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[1] , "SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1399. Accessed: Feb. 25, 2017.
@article{1399-16,
url = {http://sigport.org/1399},
author = { },
publisher = {IEEE SigPort},
title = {SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL},
year = {2016} }
TY - EJOUR
T1 - SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1399
ER -
. (2016). SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL. IEEE SigPort. http://sigport.org/1399
, 2016. SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL. Available at: http://sigport.org/1399.
. (2016). "SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL." Web.
1. . SAMPLING AND DISTORTION TRADEOFFS FOR INDIRECT SOURCE RETRIEVAL [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1399

Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN


Compressed sensing recovery techniques allow for reconstruction of an unknown sparse vector from an underdetermined system of linear equations. Recently, a lot of attention was drawn to the problem of recovering the sparse vector from quantized CS measurements. Especially interesting is the case, when extreme quantization is enforced that captures only the sign of the measurements. The problem becomes even more difficult if the measurements are corrupted by noise. In this paper we consider \ac{AWGN}.

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Authors:
Osman Musa,Gabor Hannak,Norbert Goertz
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6 December 2016 - 12:16pm
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[1] Osman Musa,Gabor Hannak,Norbert Goertz, "Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1368. Accessed: Feb. 25, 2017.
@article{1368-16,
url = {http://sigport.org/1368},
author = {Osman Musa;Gabor Hannak;Norbert Goertz },
publisher = {IEEE SigPort},
title = {Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN},
year = {2016} }
TY - EJOUR
T1 - Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN
AU - Osman Musa;Gabor Hannak;Norbert Goertz
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1368
ER -
Osman Musa,Gabor Hannak,Norbert Goertz. (2016). Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN. IEEE SigPort. http://sigport.org/1368
Osman Musa,Gabor Hannak,Norbert Goertz, 2016. Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN. Available at: http://sigport.org/1368.
Osman Musa,Gabor Hannak,Norbert Goertz. (2016). "Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN." Web.
1. Osman Musa,Gabor Hannak,Norbert Goertz. Generalized Approximate Message Passing for One-Bit Compressed Sensing with AWGN [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1368

In-Network Linear Regression with Arbitrarily Split Data Matrices


We address for the first time the question of how networked agents can collaboratively fit a Morozov-regularized linear model when each agent knows a summand of the regression data. This question generalizes previously studied data-splitting scenarios, which require that the data be partitioned among the agents. To answer the question, we introduce a class of network-structured problems, which contains the regularization problem, and by using the Douglas-Rachford splitting algorithm, we develop a distributed algorithm to solve these problems.

Poster.pdf

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Authors:
François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross
Submitted On:
5 December 2016 - 6:33pm
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[1] François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross, "In-Network Linear Regression with Arbitrarily Split Data Matrices", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1353. Accessed: Feb. 25, 2017.
@article{1353-16,
url = {http://sigport.org/1353},
author = {François D. Côté; Ioannis N. Psaromiligkos; Warren J. Gross },
publisher = {IEEE SigPort},
title = {In-Network Linear Regression with Arbitrarily Split Data Matrices},
year = {2016} }
TY - EJOUR
T1 - In-Network Linear Regression with Arbitrarily Split Data Matrices
AU - François D. Côté; Ioannis N. Psaromiligkos; Warren J. Gross
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1353
ER -
François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross. (2016). In-Network Linear Regression with Arbitrarily Split Data Matrices. IEEE SigPort. http://sigport.org/1353
François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross, 2016. In-Network Linear Regression with Arbitrarily Split Data Matrices. Available at: http://sigport.org/1353.
François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross. (2016). "In-Network Linear Regression with Arbitrarily Split Data Matrices." Web.
1. François D. Côté, Ioannis N. Psaromiligkos, Warren J. Gross. In-Network Linear Regression with Arbitrarily Split Data Matrices [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1353

DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS

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Authors:
Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama
Submitted On:
7 December 2016 - 10:49am
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[1] Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama, "DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1347. Accessed: Feb. 25, 2017.
@article{1347-16,
url = {http://sigport.org/1347},
author = {Mahmoud Abdelaziz; Lauri Anttila; Mikko Valkama },
publisher = {IEEE SigPort},
title = {DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS},
year = {2016} }
TY - EJOUR
T1 - DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS
AU - Mahmoud Abdelaziz; Lauri Anttila; Mikko Valkama
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1347
ER -
Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama. (2016). DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS. IEEE SigPort. http://sigport.org/1347
Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama, 2016. DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS. Available at: http://sigport.org/1347.
Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama. (2016). "DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS." Web.
1. Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama. DIGITAL PREDISTORTION FOR MITIGATING TRANSMITTER-INDUCED RECEIVER DESENSITIZATION IN CARRIER AGGREGATION FDD TRANSCEIVERS [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1347

A New Perspective on Randomized Gossip Algorithms


In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

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Authors:
Nicolas Loizou, Peter Richtarik
Submitted On:
5 December 2016 - 8:10am
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[1] Nicolas Loizou, Peter Richtarik , "A New Perspective on Randomized Gossip Algorithms", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1345. Accessed: Feb. 25, 2017.
@article{1345-16,
url = {http://sigport.org/1345},
author = {Nicolas Loizou; Peter Richtarik },
publisher = {IEEE SigPort},
title = {A New Perspective on Randomized Gossip Algorithms},
year = {2016} }
TY - EJOUR
T1 - A New Perspective on Randomized Gossip Algorithms
AU - Nicolas Loizou; Peter Richtarik
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1345
ER -
Nicolas Loizou, Peter Richtarik . (2016). A New Perspective on Randomized Gossip Algorithms. IEEE SigPort. http://sigport.org/1345
Nicolas Loizou, Peter Richtarik , 2016. A New Perspective on Randomized Gossip Algorithms. Available at: http://sigport.org/1345.
Nicolas Loizou, Peter Richtarik . (2016). "A New Perspective on Randomized Gossip Algorithms." Web.
1. Nicolas Loizou, Peter Richtarik . A New Perspective on Randomized Gossip Algorithms [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1345

A New Perspective on Randomized Gossip Algorithms


In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

Paper Details

Authors:
Nicolas Loizou, Peter Richtarik
Submitted On:
5 December 2016 - 8:10am
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PosterGlobalSip.pdf

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[1] Nicolas Loizou, Peter Richtarik , "A New Perspective on Randomized Gossip Algorithms", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1344. Accessed: Feb. 25, 2017.
@article{1344-16,
url = {http://sigport.org/1344},
author = {Nicolas Loizou; Peter Richtarik },
publisher = {IEEE SigPort},
title = {A New Perspective on Randomized Gossip Algorithms},
year = {2016} }
TY - EJOUR
T1 - A New Perspective on Randomized Gossip Algorithms
AU - Nicolas Loizou; Peter Richtarik
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1344
ER -
Nicolas Loizou, Peter Richtarik . (2016). A New Perspective on Randomized Gossip Algorithms. IEEE SigPort. http://sigport.org/1344
Nicolas Loizou, Peter Richtarik , 2016. A New Perspective on Randomized Gossip Algorithms. Available at: http://sigport.org/1344.
Nicolas Loizou, Peter Richtarik . (2016). "A New Perspective on Randomized Gossip Algorithms." Web.
1. Nicolas Loizou, Peter Richtarik . A New Perspective on Randomized Gossip Algorithms [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1344

A New Perspective on Randomized Gossip Algorithms


In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

Paper Details

Authors:
Nicolas Loizou, Peter Richtarik
Submitted On:
5 December 2016 - 8:10am
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Type:
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PosterGlobalSip.pdf

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[1] Nicolas Loizou, Peter Richtarik , "A New Perspective on Randomized Gossip Algorithms", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1343. Accessed: Feb. 25, 2017.
@article{1343-16,
url = {http://sigport.org/1343},
author = {Nicolas Loizou; Peter Richtarik },
publisher = {IEEE SigPort},
title = {A New Perspective on Randomized Gossip Algorithms},
year = {2016} }
TY - EJOUR
T1 - A New Perspective on Randomized Gossip Algorithms
AU - Nicolas Loizou; Peter Richtarik
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1343
ER -
Nicolas Loizou, Peter Richtarik . (2016). A New Perspective on Randomized Gossip Algorithms. IEEE SigPort. http://sigport.org/1343
Nicolas Loizou, Peter Richtarik , 2016. A New Perspective on Randomized Gossip Algorithms. Available at: http://sigport.org/1343.
Nicolas Loizou, Peter Richtarik . (2016). "A New Perspective on Randomized Gossip Algorithms." Web.
1. Nicolas Loizou, Peter Richtarik . A New Perspective on Randomized Gossip Algorithms [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1343

Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation


The construction of complementary sets of unimodular sequences of length N, with low correlation and complementary correlation coefficients is addressed. The design criterion is based on the minimisation of a cost function that penalizes the integrated side lobe as well as the sum of the complementary correlations of the sequences in the set. Numerical solution to the proposed cost function is obtained using conventional optimization methods.

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Authors:
Israel Alejandro Arriaga-Trejo
Submitted On:
15 November 2016 - 4:35pm
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[1] Israel Alejandro Arriaga-Trejo, "Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1265. Accessed: Feb. 25, 2017.
@article{1265-16,
url = {http://sigport.org/1265},
author = {Israel Alejandro Arriaga-Trejo },
publisher = {IEEE SigPort},
title = {Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation },
year = {2016} }
TY - EJOUR
T1 - Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation
AU - Israel Alejandro Arriaga-Trejo
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1265
ER -
Israel Alejandro Arriaga-Trejo. (2016). Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation . IEEE SigPort. http://sigport.org/1265
Israel Alejandro Arriaga-Trejo, 2016. Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation . Available at: http://sigport.org/1265.
Israel Alejandro Arriaga-Trejo. (2016). "Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation ." Web.
1. Israel Alejandro Arriaga-Trejo. Construction of Complementary Sets of Sequences with Low Aperiodic Correlation and Complementary Correlation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1265

IEEE SP Cup 2016 Report - Team MGLS


Extracting the Electric Network Frequency (ENF) fluctuations from an audio recording and comparing it to a reference database is a new approach in performing forensic digital audio authentication. The problem statement of the IEEE SP cup 2016 competition relates to time-varying location-dependent signature of power grids as it becomes intrinsically captured in media recordings, due to direct or indirect influences from the respective power grid. In this project signal processing and information security/forensics are collectively elaborated.

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Authors:
Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello
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31 August 2016 - 12:02pm
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[1] Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello, "IEEE SP Cup 2016 Report - Team MGLS", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1146. Accessed: Feb. 25, 2017.
@article{1146-16,
url = {http://sigport.org/1146},
author = {Dr. K. C. B. Wavegedara; Piyumika T. Bandula; W. A. K. Amalika Lahiruni; G. D. C. Nipuni B. Mello },
publisher = {IEEE SigPort},
title = {IEEE SP Cup 2016 Report - Team MGLS},
year = {2016} }
TY - EJOUR
T1 - IEEE SP Cup 2016 Report - Team MGLS
AU - Dr. K. C. B. Wavegedara; Piyumika T. Bandula; W. A. K. Amalika Lahiruni; G. D. C. Nipuni B. Mello
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1146
ER -
Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello. (2016). IEEE SP Cup 2016 Report - Team MGLS. IEEE SigPort. http://sigport.org/1146
Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello, 2016. IEEE SP Cup 2016 Report - Team MGLS. Available at: http://sigport.org/1146.
Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello. (2016). "IEEE SP Cup 2016 Report - Team MGLS." Web.
1. Dr. K. C. B. Wavegedara, Piyumika T. Bandula, W. A. K. Amalika Lahiruni, G. D. C. Nipuni B. Mello. IEEE SP Cup 2016 Report - Team MGLS [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1146

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