Low-Complexity GSVD-Based Beamforming and Power Allocation for a Cognitive Radio Network

Jaehyun PARK; Yunju PARK; Sunghyun HWANG; Byung Jang JEONG

doi:10.1587/transcom.E95.B.3536

Low-Complexity GSVD-Based Beamforming and Power Allocation for a Cognitive Radio Network

Jaehyun PARK, Yunju PARK, Sunghyun HWANG, Byung Jang JEONG

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In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.

Publication: IEICE TRANSACTIONS on Communications Vol.E95-B No.11 pp.3536-3544

Publication Date: 2012/11/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E95.B.3536

Type of Manuscript: PAPER

Category: Terrestrial Wireless Communication/Broadcasting Technologies

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Jaehyun PARK, Yunju PARK, Sunghyun HWANG, Byung Jang JEONG, "Low-Complexity GSVD-Based Beamforming and Power Allocation for a Cognitive Radio Network" in IEICE TRANSACTIONS on Communications, vol. E95-B, no. 11, pp. 3536-3544, November 2012, doi: 10.1587/transcom.E95.B.3536.
Abstract: In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E95.B.3536/_p

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@ARTICLE{e95-b_11_3536,
author={Jaehyun PARK, Yunju PARK, Sunghyun HWANG, Byung Jang JEONG, },
journal={IEICE TRANSACTIONS on Communications},
title={Low-Complexity GSVD-Based Beamforming and Power Allocation for a Cognitive Radio Network},
year={2012},
volume={E95-B},
number={11},
pages={3536-3544},
abstract={In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.},
keywords={},
doi={10.1587/transcom.E95.B.3536},
ISSN={1745-1345},
month={November},}

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TY - JOUR
TI - Low-Complexity GSVD-Based Beamforming and Power Allocation for a Cognitive Radio Network
T2 - IEICE TRANSACTIONS on Communications
SP - 3536
EP - 3544
AU - Jaehyun PARK
AU - Yunju PARK
AU - Sunghyun HWANG
AU - Byung Jang JEONG
PY - 2012
DO - 10.1587/transcom.E95.B.3536
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E95-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2012
AB - In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.
ER -