Energy-Efficient Joint Power and Bandwidth Allocation for NOMA Systems

Wang, Jun; Xu, Hongbo; Fan, Lvrong; Zhu, Bingru; Zhou, Anyu

doi:10.1109/lcomm.2018.2794521

Cited by 43 publications

(15 citation statements)

References 17 publications

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“…In [23], the authors tried their best to transform original probabilistic and non-convex problem into a nonprobabilistic and convex one with the target of maximizing energy efficiency with imperfect channel state information. Considering the constraints of user QoS and queue stability, literatures [24] and [25] investigated power allocation in MC-NOMA networks using the stochastic optimization method. In [26] and [27], for uplink and downlink MC-NOMA systems respectively, the authors studied power and subcarrier allocations to maximize WSR.…”

Section: A Motivation and Related Workmentioning

confidence: 99%

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Wang

Chen

et al. 2019

IEEE Access

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In this paper, we investigate the power allocation for maximizing weighted sum rate (WSR) in downlink multiple carriers non-orthogonal multiple access (MC-NOMA) systems with imperfect successive interference cancellation (SIC). We formulate the power allocation problem as a non-convex optimization problem with the total power constraint of all sub-channels while considering often-neglected issues of SIC error and power order constraints at users. First, we discuss that the optimization problem assuming receivers can perform perfect SIC, and we provide a concavity condition of the WSR maximization problem for the MC-NOMA system. When the concavity condition is not satisfied, a fractional quadratic transformation is used to overcome the difficulty of problem non-convexity. Based on the transformation, we propose an iterative power allocation algorithm. Then, we consider the SIC error and the power order constraints in the optimization problem and present a power allocation method with imperfect SIC. Moreover, for both the perfect and imperfect SIC, we derive some propositions of the optimal power allocation solution to the WSR maximization problem and propose a low-complexity power allocation algorithm based on these propositions. Finally, we provide a joint user scheduling and power allocation algorithm for maximizing the WSR. The simulation results illustrate that the proposed resource allocation methods have a better performance than the existing schemes.

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Section: A Motivation and Related Workmentioning

confidence: 99%

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Wang

Chen

et al. 2019

IEEE Access

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“…These results confirmed that the NOMA system can achieve a better performance in terms of sum rate and EE compared to the conventional orthogonal multiple access (OMA) systems, for example orthogonal frequency-division multiple access (OFDMA). An energyefficient power and bandwidth allocations were derived in [28] for a NOMA system which has multiple subchannels with unequal bandwidth. Some other related works can be found in [29], [30].…”

Section: A Literaturementioning

confidence: 99%

Robust Energy-Efficient Design for MISO Non-Orthogonal Multiple Access Systems

Alavi

Cumanan

Fozooni

et al. 2019

IEEE Trans. Commun.

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Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its significant enhancement of spectral efficiency. In this paper, we investigate a robust energy efficiency design for multiuser multiple-input singleoutput (MISO) NOMA systems where imperfect channel state information is available at the base station. A clustering algorithm is applied to group the users into different clusters, and then NOMA technique is employed to share the available resources fairly among the users in each cluster. To remove the interference between clusters, two different types of zero-forcing (ZF) designs, namely, hybrid-ZF and full-ZF are employed at the BS. The full-ZF scheme completely removes the interference leakage at the cost of more number of antennas and the hybrid-ZF scheme partially mitigates the interference leakage. To solve the problem, the Dinkelbach's algorithm is employed to convert the non-linear fractional programming problem into a simple subtractive form. Finally, simulation results reveal that hybrid-ZF outperforms the full-ZF scheme with a few clusters, while full-ZF shows a better performance with the higher number of clusters. The numerical results confirm that our proposed robust scheme outperforms the non-robust scheme in terms of the rate-satisfaction ratio at each user.

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“…As a key measure of the next generation networks, energy efficiency (EE) in NOMA systems has been investigated in several studies. EE maximization for single cell NOMA systems was investigated in [9], [10], multicarrier NOMA (MC-NOMA) [11]- [15], multi-cell multi-carrier NOMA (MCMC-NOMA) networks [16]. Weighted EE maximization with user's fairness were considered in [17]- [20].…”

Section: Introductionmentioning

confidence: 99%

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

Adam

Wang

2020

IEEE Access

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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 pseudoconvexity. 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). INDEX TERMS Binary whale optimization algorithm (BWOA), energy efficiency (EE), hardware impairments (HIs), multi-cell multi-carrier (MCMC), non-orthogonal multiple access (NOMA).

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Energy-Efficient Joint Power and Bandwidth Allocation for NOMA Systems

Cited by 43 publications

References 17 publications

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Robust Energy-Efficient Design for MISO Non-Orthogonal Multiple Access Systems

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

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