Energy Efficiency Maximization in Downlink Multi-Cell Multi-Carrier NOMA Networks With Hardware Impairments

In this paper, we investigate energy efficiency (EE) maximization in multicell multicarrier non-orthogonal multiple access (MCMC-NOMA) networks with hardware impairments (HIs). We formulate the optimization problem as a mixed integer nonlinear NP-hard problem, which is difficult to solve efficiently...

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Bibliographic Details
Published in:IEEE access Vol. 8; pp. 210054 - 210065
Main Authors: Adam, Abuzar B. M., Wan, Xiaoyu, Wang, Zhengqiang
Format: Journal Article
Language:English
Published: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Binary whale optimization algorithm (BWOA)
Convexity
Downlink
Energy conversion efficiency
Energy efficiency
energy efficiency (EE)
Hardware
hardware impairments (HIs)
Lower bounds
Maximization
Mixed integer
multi-cell multi-carrier (MCMC)
NOMA
non-orthogonal multiple access (NOMA)
Nonorthogonal multiple access
Operations research
Optimization
Resource management
Simulation
Throughput
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:In this paper, we investigate energy efficiency (EE) maximization in multicell multicarrier non-orthogonal multiple access (MCMC-NOMA) networks with hardware impairments (HIs). We formulate the optimization problem as a mixed integer nonlinear NP-hard problem, which is difficult to solve efficiently. To solve this problem, we decompose it into two subproblems. The first subproblem is the user and base station (BS) association and subchannel assignment problem, where binary whale optimization algorithm (BWOA) is proposed to handle it. For the second subproblem of the non-convex power allocation problem, successive pseudo-convex approximation (SPCA) is employed to establish the problem's pseudo-convexity. The approximate problem is separable into a sequence of equivalent problems that can be easier to solve. Each problem of the obtained sequence has a stationary point solution and is guaranteed to converge. The simulation results demonstrate that the proposed algorithm achieves a performance comparable to that of the successive lower bound maximization (SLBM) algorithm and outperforms both fractional transmit power allocation (FTPA) benchmark for NOMA and the conventional orthogonal multiple access (OMA).
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3039242