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Downlink beamforming in underlay cognitive cellular networks

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Downlink beamforming in underlay cognitive cellular networks. / Anh Le, Tuan; Navaie, Keivan.

In: IEEE Transactions on Communications, Vol. 62, No. 7, 07.2014, p. 2212-2223.

Research output: Contribution to journalJournal article

Harvard

Anh Le, T & Navaie, K 2014, 'Downlink beamforming in underlay cognitive cellular networks', IEEE Transactions on Communications, vol. 62, no. 7, pp. 2212-2223. https://doi.org/10.1109/TCOMM.2014.2323051

APA

Vancouver

Anh Le T, Navaie K. Downlink beamforming in underlay cognitive cellular networks. IEEE Transactions on Communications. 2014 Jul;62(7):2212-2223. https://doi.org/10.1109/TCOMM.2014.2323051

Author

Anh Le, Tuan ; Navaie, Keivan. / Downlink beamforming in underlay cognitive cellular networks. In: IEEE Transactions on Communications. 2014 ; Vol. 62, No. 7. pp. 2212-2223.

Bibtex

@article{81ddbe3fd86e4456a40c2215943ddde3,
title = "Downlink beamforming in underlay cognitive cellular networks",
abstract = "We propose a novel scheme for downlink beamforming design in an underlay cognitive cellular system. The beamforming design is formulated as an optimization problem with the objective of keeping the cognitive base station transmit power as well as the induced interference on the primary users, below predefined system thresholds. This is subject to providing a certain level of signal-to-interference-plus-noise ratio (SINR) to the secondary users. We then derive the corresponding semidefinite programming form for the formulated optimization problem and propose an iterative algorithm to obtain the beamforming vectors as the optimal solutions. We further analytically show the convergence of the proposed iterative algorithm. Extensive simulations verify that the proposed algorithm quickly converges to the optimal solution. We then compare the proposed scheme with a benchmarking system defined based on the previous methods proposed in the related literature. Comparisons show that the proposed algorithm outperforms the benchmarking system and induces lower interference at the primary service receivers. It is also observed that the proposed algorithm offers a higher sum rate in comparison to the benchmarking system. Simulation results further reveal that the proposed approach effectively works at a relatively high SINR level required by secondary users and strict interference threshold set by the primary system while the benchmarking system fails to do so.",
keywords = "Downlink beamforming, underlay cognitive cellular networks, interference management, CONVEX-OPTIMIZATION, POWER-CONTROL, CONSTRAINTS, FRAMEWORK, SYSTEMS",
author = "{Anh Le}, Tuan and Keivan Navaie",
year = "2014",
month = jul
doi = "10.1109/TCOMM.2014.2323051",
language = "English",
volume = "62",
pages = "2212--2223",
journal = "IEEE Transactions on Communications",
issn = "0090-6778",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "7",

}

RIS

TY - JOUR

T1 - Downlink beamforming in underlay cognitive cellular networks

AU - Anh Le, Tuan

AU - Navaie, Keivan

PY - 2014/7

Y1 - 2014/7

N2 - We propose a novel scheme for downlink beamforming design in an underlay cognitive cellular system. The beamforming design is formulated as an optimization problem with the objective of keeping the cognitive base station transmit power as well as the induced interference on the primary users, below predefined system thresholds. This is subject to providing a certain level of signal-to-interference-plus-noise ratio (SINR) to the secondary users. We then derive the corresponding semidefinite programming form for the formulated optimization problem and propose an iterative algorithm to obtain the beamforming vectors as the optimal solutions. We further analytically show the convergence of the proposed iterative algorithm. Extensive simulations verify that the proposed algorithm quickly converges to the optimal solution. We then compare the proposed scheme with a benchmarking system defined based on the previous methods proposed in the related literature. Comparisons show that the proposed algorithm outperforms the benchmarking system and induces lower interference at the primary service receivers. It is also observed that the proposed algorithm offers a higher sum rate in comparison to the benchmarking system. Simulation results further reveal that the proposed approach effectively works at a relatively high SINR level required by secondary users and strict interference threshold set by the primary system while the benchmarking system fails to do so.

AB - We propose a novel scheme for downlink beamforming design in an underlay cognitive cellular system. The beamforming design is formulated as an optimization problem with the objective of keeping the cognitive base station transmit power as well as the induced interference on the primary users, below predefined system thresholds. This is subject to providing a certain level of signal-to-interference-plus-noise ratio (SINR) to the secondary users. We then derive the corresponding semidefinite programming form for the formulated optimization problem and propose an iterative algorithm to obtain the beamforming vectors as the optimal solutions. We further analytically show the convergence of the proposed iterative algorithm. Extensive simulations verify that the proposed algorithm quickly converges to the optimal solution. We then compare the proposed scheme with a benchmarking system defined based on the previous methods proposed in the related literature. Comparisons show that the proposed algorithm outperforms the benchmarking system and induces lower interference at the primary service receivers. It is also observed that the proposed algorithm offers a higher sum rate in comparison to the benchmarking system. Simulation results further reveal that the proposed approach effectively works at a relatively high SINR level required by secondary users and strict interference threshold set by the primary system while the benchmarking system fails to do so.

KW - Downlink beamforming

KW - underlay cognitive cellular networks

KW - interference management

KW - CONVEX-OPTIMIZATION

KW - POWER-CONTROL

KW - CONSTRAINTS

KW - FRAMEWORK

KW - SYSTEMS

U2 - 10.1109/TCOMM.2014.2323051

DO - 10.1109/TCOMM.2014.2323051

M3 - Journal article

VL - 62

SP - 2212

EP - 2223

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

SN - 0090-6778

IS - 7

ER -