Sum Rate Optimization in Multiuser Cognitive Radio Networks

Fanggang WANG; Bo AI; Zhangdui ZHONG

doi:10.1587/transcom.E94.B.3505

Sum Rate Optimization in Multiuser Cognitive Radio Networks

Fanggang WANG, Bo AI, Zhangdui ZHONG

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In multiuser cognitive radio (CR) networks, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is a nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed by iteratively performing BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP²) is used to design beamformers and subgradient method is used to control the power. VIP² algorithm is devised for the case in which the interference caused by MMSE beamformer exceeds the threshold. Moreover, channel uncertainty due to lack of cooperation is considered. A closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. A robust algorithm based on IDuSuG is provided by modifying updates in iterative process. Furthermore, second-order cone programming approximation (SOCPA) method is proposed as another robust algorithm. Typical network models are approximated to SOCP problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.

Publication: IEICE TRANSACTIONS on Communications Vol.E94-B No.12 pp.3505-3514

Publication Date: 2011/12/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E94.B.3505

Type of Manuscript: PAPER

Category: Wireless Communication Technologies

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Fanggang WANG, Bo AI, Zhangdui ZHONG, "Sum Rate Optimization in Multiuser Cognitive Radio Networks" in IEICE TRANSACTIONS on Communications, vol. E94-B, no. 12, pp. 3505-3514, December 2011, doi: 10.1587/transcom.E94.B.3505.
Abstract: In multiuser cognitive radio (CR) networks, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is a nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed by iteratively performing BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP²) is used to design beamformers and subgradient method is used to control the power. VIP² algorithm is devised for the case in which the interference caused by MMSE beamformer exceeds the threshold. Moreover, channel uncertainty due to lack of cooperation is considered. A closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. A robust algorithm based on IDuSuG is provided by modifying updates in iterative process. Furthermore, second-order cone programming approximation (SOCPA) method is proposed as another robust algorithm. Typical network models are approximated to SOCP problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.3505/_p

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@ARTICLE{e94-b_12_3505,
author={Fanggang WANG, Bo AI, Zhangdui ZHONG, },
journal={IEICE TRANSACTIONS on Communications},
title={Sum Rate Optimization in Multiuser Cognitive Radio Networks},
year={2011},
volume={E94-B},
number={12},
pages={3505-3514},
abstract={ In multiuser cognitive radio (CR) networks, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is a nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed by iteratively performing BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP²) is used to design beamformers and subgradient method is used to control the power. VIP² algorithm is devised for the case in which the interference caused by MMSE beamformer exceeds the threshold. Moreover, channel uncertainty due to lack of cooperation is considered. A closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. A robust algorithm based on IDuSuG is provided by modifying updates in iterative process. Furthermore, second-order cone programming approximation (SOCPA) method is proposed as another robust algorithm. Typical network models are approximated to SOCP problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.},
keywords={},
doi={10.1587/transcom.E94.B.3505},
ISSN={1745-1345},
month={December},}

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TY - JOUR
TI - Sum Rate Optimization in Multiuser Cognitive Radio Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 3505
EP - 3514
AU - Fanggang WANG
AU - Bo AI
AU - Zhangdui ZHONG
PY - 2011
DO - 10.1587/transcom.E94.B.3505
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2011
AB - In multiuser cognitive radio (CR) networks, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is a nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed by iteratively performing BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP²) is used to design beamformers and subgradient method is used to control the power. VIP² algorithm is devised for the case in which the interference caused by MMSE beamformer exceeds the threshold. Moreover, channel uncertainty due to lack of cooperation is considered. A closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. A robust algorithm based on IDuSuG is provided by modifying updates in iterative process. Furthermore, second-order cone programming approximation (SOCPA) method is proposed as another robust algorithm. Typical network models are approximated to SOCP problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.
ER -