TY - GEN
T1 - Sum Rate Fairness Trade-off-based Resource Allocation Technique for MISO NOMA Systems
AU - Al-Obiedollah, Haitham
AU - Cumanan, Kanapathippillai
AU - Thiyagalingam, Jeyarajan
AU - Burr, Alister G.
AU - Ding, Zhiguo
AU - Dobre, Octavia A.
N1 - Funding Information:
The work of K. Cumanan, A. Burr and Z. Ding was supported by H2020-MSCA-RISE-2015 under grant no: 690750.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - In this paper, we propose a beamforming design that jointly considers two conflicting performance metrics, namely the sum rate and fairness, for a multiple-input single-output non-orthogonal multiple access system. Unlike the conventional rate-aware beamforming designs, the proposed approach has the flexibility to assign different weights to the objectives (i.e., sum rate and fairness) according to the network requirements and the channel conditions. In particular, the proposed design is first formulated as a multi-objective optimization problem, and subsequently mapped to a single objective optimization (SOO) problem by exploiting the weighted sum approach combined with a prior articulation method. As the resulting SOO problem is non-convex, we use the sequential convex approximation technique, which introduces multiple slack variables, to solve the overall problem. Simulation results are provided to demonstrate the performance and the effectiveness of the proposed approach along with detailed comparisons with conventional rate-aware-based beamforming designs.
AB - In this paper, we propose a beamforming design that jointly considers two conflicting performance metrics, namely the sum rate and fairness, for a multiple-input single-output non-orthogonal multiple access system. Unlike the conventional rate-aware beamforming designs, the proposed approach has the flexibility to assign different weights to the objectives (i.e., sum rate and fairness) according to the network requirements and the channel conditions. In particular, the proposed design is first formulated as a multi-objective optimization problem, and subsequently mapped to a single objective optimization (SOO) problem by exploiting the weighted sum approach combined with a prior articulation method. As the resulting SOO problem is non-convex, we use the sequential convex approximation technique, which introduces multiple slack variables, to solve the overall problem. Simulation results are provided to demonstrate the performance and the effectiveness of the proposed approach along with detailed comparisons with conventional rate-aware-based beamforming designs.
KW - Beamforming design
KW - multi-objective optimization
KW - non-orthogonal multiple access
KW - Pareto-optimal
UR - http://www.scopus.com/inward/record.url?scp=85074758701&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2019.8886335
DO - 10.1109/WCNC.2019.8886335
M3 - Conference contribution
AN - SCOPUS:85074758701
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Y2 - 15 April 2019 through 19 April 2019
ER -