Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge

Yuan Jiang; Hongbin Li; Muralidhar Rangaswamy

doi:10.1109/IEEECONF44664.2019.9049068

Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge

Yuan Jiang
, Hongbin Li
, Muralidhar Rangaswamy

Stevens Institute of Technology
Air Force Research Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a new Bayesian learning algorithm, referred to as the mSKL-GAMP, for signal detection in subspace interference with uncertain/partial prior knowledge of the subspace. It is an extension of the recently introduced SKL algorithm [1] that employs a fixed dictionary for subspace recovery, which causes the grid-mismatch problem. mSKL-GAMP overcomes the problem via a subspace refining procedure. In addition, it integrates the generalized approximate message passing (GAMP) for posterior approximation, which bypasses iterative matrix inversions required by SKL, and thus is computationally much simpler. Numerical results show mSKL-GAMP yields improved detection performance over SKL and other benchmark schemes.

Original language	English
Title of host publication	Conference Record of the 53rd Asilomar Conference on Signals, Systems and Computers, ACSSC 2019
Editors	Michael B. Matthews
Pages	74-78
Number of pages	5
ISBN (Electronic)	9781728143002
DOIs	https://doi.org/10.1109/IEEECONF44664.2019.9049068
State	Published - Nov 2019
Event	53rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 2019 - Pacific Grove, United States Duration: 3 Nov 2019 → 6 Nov 2019

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2019-November
ISSN (Electronic)	2576-2303

Conference

Conference	53rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 2019
Country/Territory	United States
City	Pacific Grove
Period	3/11/19 → 6/11/19

Access to Document

10.1109/IEEECONF44664.2019.9049068

Cite this

Jiang, Y., Li, H., & Rangaswamy, M. (2019). Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge. In M. B. Matthews (Ed.), Conference Record of the 53rd Asilomar Conference on Signals, Systems and Computers, ACSSC 2019 (pp. 74-78). Article 9049068 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2019-November). https://doi.org/10.1109/IEEECONF44664.2019.9049068

@inproceedings{f84a32090ede4bf6bc957577e50105b7,

title = "Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge",

abstract = "We present a new Bayesian learning algorithm, referred to as the mSKL-GAMP, for signal detection in subspace interference with uncertain/partial prior knowledge of the subspace. It is an extension of the recently introduced SKL algorithm [1] that employs a fixed dictionary for subspace recovery, which causes the grid-mismatch problem. mSKL-GAMP overcomes the problem via a subspace refining procedure. In addition, it integrates the generalized approximate message passing (GAMP) for posterior approximation, which bypasses iterative matrix inversions required by SKL, and thus is computationally much simpler. Numerical results show mSKL-GAMP yields improved detection performance over SKL and other benchmark schemes.",

author = "Yuan Jiang and Hongbin Li and Muralidhar Rangaswamy",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 53rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 2019 ; Conference date: 03-11-2019 Through 06-11-2019",

year = "2019",

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doi = "10.1109/IEEECONF44664.2019.9049068",

language = "English",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

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}

Jiang, Y, Li, H & Rangaswamy, M 2019, Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge. in MB Matthews (ed.), Conference Record of the 53rd Asilomar Conference on Signals, Systems and Computers, ACSSC 2019., 9049068, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2019-November, pp. 74-78, 53rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 2019, Pacific Grove, United States, 3/11/19. https://doi.org/10.1109/IEEECONF44664.2019.9049068

Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge. / Jiang, Yuan; Li, Hongbin; Rangaswamy, Muralidhar.
Conference Record of the 53rd Asilomar Conference on Signals, Systems and Computers, ACSSC 2019. ed. / Michael B. Matthews. 2019. p. 74-78 9049068 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2019-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - We present a new Bayesian learning algorithm, referred to as the mSKL-GAMP, for signal detection in subspace interference with uncertain/partial prior knowledge of the subspace. It is an extension of the recently introduced SKL algorithm [1] that employs a fixed dictionary for subspace recovery, which causes the grid-mismatch problem. mSKL-GAMP overcomes the problem via a subspace refining procedure. In addition, it integrates the generalized approximate message passing (GAMP) for posterior approximation, which bypasses iterative matrix inversions required by SKL, and thus is computationally much simpler. Numerical results show mSKL-GAMP yields improved detection performance over SKL and other benchmark schemes.

AB - We present a new Bayesian learning algorithm, referred to as the mSKL-GAMP, for signal detection in subspace interference with uncertain/partial prior knowledge of the subspace. It is an extension of the recently introduced SKL algorithm [1] that employs a fixed dictionary for subspace recovery, which causes the grid-mismatch problem. mSKL-GAMP overcomes the problem via a subspace refining procedure. In addition, it integrates the generalized approximate message passing (GAMP) for posterior approximation, which bypasses iterative matrix inversions required by SKL, and thus is computationally much simpler. Numerical results show mSKL-GAMP yields improved detection performance over SKL and other benchmark schemes.

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Jiang Y, Li H, Rangaswamy M. Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge. In Matthews MB, editor, Conference Record of the 53rd Asilomar Conference on Signals, Systems and Computers, ACSSC 2019. 2019. p. 74-78. 9049068. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/IEEECONF44664.2019.9049068

Adaptive Signal Detection in Subspace Interference with Uncertain Prior Knowledge

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