IEICE TRANSACTIONS on Communications
Subchannel and Power Allocation with Fairness Guaranteed for the Downlink of NOMA-Based Networks
Summary :
This paper investigates the resource allocation problem for the downlink of non-orthogonal multiple access (NOMA) networks. A novel resource allocation method is proposed to deal with the problem of maximizing the system capacity while taking into account user fairness. Since the optimization problem is nonconvex and intractable, we adopt the idea of step-by-step optimization, decomposing it into user pairing, subchannel and power allocation subproblems. First, all users are paired according to their different channel gains. Then, the subchannel allocation is executed by the proposed subchannel selection algorithm (SSA) based on channel priority. Once the subchannel allocation is fixed, to further improve the system capacity, the subchannel power allocation is implemented by the successive convex approximation (SCA) approach where the nonconvex optimization problem is transformed into the approximated convex optimization problem in each iteration. To ensure user fairness, the upper and lower bounds of the power allocation coefficients are derived and combined by introducing the tuning coefficients. The power allocation coefficients are dynamically adjustable by adjusting the tuning coefficients, thus the diversified quality of service (QoS) requirements can be satisfied. Finally, simulation results demonstrate the superiority of the proposed method over the existing methods in terms of system performance, furthermore, a good tradeoff between the system capacity and user fairness can be achieved.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E103-B No.12 pp.1447-1461
- Publication Date
- 2020/12/01
- Publicized
- 2020/06/08
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2019EBP3256
- Type of Manuscript
- PAPER
- Category
- Wireless Communication Technologies
Authors
Qingyuan LIU
Beijing University of Posts and Telecommunications
Qi ZHANG
Beijing University of Posts and Telecommunications
Xiangjun XIN
Beijing University of Posts and Telecommunications
Ran GAO
Beijing Institute of Technology
Qinghua TIAN
Beijing University of Posts and Telecommunications
Feng TIAN
Beijing University of Posts and Telecommunications
Keyword
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Qingyuan LIU, Qi ZHANG, Xiangjun XIN, Ran GAO, Qinghua TIAN, Feng TIAN, "Subchannel and Power Allocation with Fairness Guaranteed for the Downlink of NOMA-Based Networks" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 12, pp. 1447-1461, December 2020, doi: 10.1587/transcom.2019EBP3256.
Abstract: This paper investigates the resource allocation problem for the downlink of non-orthogonal multiple access (NOMA) networks. A novel resource allocation method is proposed to deal with the problem of maximizing the system capacity while taking into account user fairness. Since the optimization problem is nonconvex and intractable, we adopt the idea of step-by-step optimization, decomposing it into user pairing, subchannel and power allocation subproblems. First, all users are paired according to their different channel gains. Then, the subchannel allocation is executed by the proposed subchannel selection algorithm (SSA) based on channel priority. Once the subchannel allocation is fixed, to further improve the system capacity, the subchannel power allocation is implemented by the successive convex approximation (SCA) approach where the nonconvex optimization problem is transformed into the approximated convex optimization problem in each iteration. To ensure user fairness, the upper and lower bounds of the power allocation coefficients are derived and combined by introducing the tuning coefficients. The power allocation coefficients are dynamically adjustable by adjusting the tuning coefficients, thus the diversified quality of service (QoS) requirements can be satisfied. Finally, simulation results demonstrate the superiority of the proposed method over the existing methods in terms of system performance, furthermore, a good tradeoff between the system capacity and user fairness can be achieved.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019EBP3256/_p
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@ARTICLE{e103-b_12_1447,
author={Qingyuan LIU, Qi ZHANG, Xiangjun XIN, Ran GAO, Qinghua TIAN, Feng TIAN, },
journal={IEICE TRANSACTIONS on Communications},
title={Subchannel and Power Allocation with Fairness Guaranteed for the Downlink of NOMA-Based Networks},
year={2020},
volume={E103-B},
number={12},
pages={1447-1461},
abstract={This paper investigates the resource allocation problem for the downlink of non-orthogonal multiple access (NOMA) networks. A novel resource allocation method is proposed to deal with the problem of maximizing the system capacity while taking into account user fairness. Since the optimization problem is nonconvex and intractable, we adopt the idea of step-by-step optimization, decomposing it into user pairing, subchannel and power allocation subproblems. First, all users are paired according to their different channel gains. Then, the subchannel allocation is executed by the proposed subchannel selection algorithm (SSA) based on channel priority. Once the subchannel allocation is fixed, to further improve the system capacity, the subchannel power allocation is implemented by the successive convex approximation (SCA) approach where the nonconvex optimization problem is transformed into the approximated convex optimization problem in each iteration. To ensure user fairness, the upper and lower bounds of the power allocation coefficients are derived and combined by introducing the tuning coefficients. The power allocation coefficients are dynamically adjustable by adjusting the tuning coefficients, thus the diversified quality of service (QoS) requirements can be satisfied. Finally, simulation results demonstrate the superiority of the proposed method over the existing methods in terms of system performance, furthermore, a good tradeoff between the system capacity and user fairness can be achieved.},
keywords={},
doi={10.1587/transcom.2019EBP3256},
ISSN={1745-1345},
month={December},}
Copy
TY - JOUR
TI - Subchannel and Power Allocation with Fairness Guaranteed for the Downlink of NOMA-Based Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 1447
EP - 1461
AU - Qingyuan LIU
AU - Qi ZHANG
AU - Xiangjun XIN
AU - Ran GAO
AU - Qinghua TIAN
AU - Feng TIAN
PY - 2020
DO - 10.1587/transcom.2019EBP3256
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2020
AB - This paper investigates the resource allocation problem for the downlink of non-orthogonal multiple access (NOMA) networks. A novel resource allocation method is proposed to deal with the problem of maximizing the system capacity while taking into account user fairness. Since the optimization problem is nonconvex and intractable, we adopt the idea of step-by-step optimization, decomposing it into user pairing, subchannel and power allocation subproblems. First, all users are paired according to their different channel gains. Then, the subchannel allocation is executed by the proposed subchannel selection algorithm (SSA) based on channel priority. Once the subchannel allocation is fixed, to further improve the system capacity, the subchannel power allocation is implemented by the successive convex approximation (SCA) approach where the nonconvex optimization problem is transformed into the approximated convex optimization problem in each iteration. To ensure user fairness, the upper and lower bounds of the power allocation coefficients are derived and combined by introducing the tuning coefficients. The power allocation coefficients are dynamically adjustable by adjusting the tuning coefficients, thus the diversified quality of service (QoS) requirements can be satisfied. Finally, simulation results demonstrate the superiority of the proposed method over the existing methods in terms of system performance, furthermore, a good tradeoff between the system capacity and user fairness can be achieved.
ER -
English
