Optimal Resource Allocation for MC-NOMA in SWIPT-Enabled Networks

Jalali, Jalal; Khalili, Ata

doi:10.1109/lcomm.2020.3004418

Cited by 15 publications

(11 citation statements)

References 16 publications

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“…For baseline scheme 3, we consider our proposed scheme based on the OMA in which we set L = 1 for the simulation results. For baseline scheme 4, we consider our proposed scheme in which the SIC ordering is done based on the sorting the channel gains as considered commonly in the literature [27], [29], [33]. It can be observed that our proposed method clearly outperforms the other baseline schemes due to the performing joint resource allocation policy.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…However, all of the requirements for IoT cannot be satisfied by OFDM any longer [25]. The combination of SWIPT and NOMA has provoked great interest and it is verified that combining SWIPT with NOMA could bring plenty of advantages [26]- [29]. In particular, the authors in [26] aimed to maximize the total energy efficiency of time switching (TS)-SWIPT assisted NOMA system, by considering the joint optimization of TS ratio and power allocation.…”

Section: B Related Workmentioning

confidence: 99%

“…The authors in [28] investigated the joint resource allocation problem for a TS-SWIPT multi carrier (MC)-NOMA system, where pattern division multiple access (PDMA) technique was employed to minimize the total transmit power of the system. An optimal resource allocation for the MC-NOMA enabled SWIPT technique was proposed in [29] to maximize energy harvesting. However, only a single access point as well as single antenna were considered.…”

Section: B Related Workmentioning

confidence: 99%

“…Nonetheless, to the best of authors knowledge the problem of joint subcarrier allocation, beamforming design, and decoding order for ID user, and energy beam for EH users in a NOMA assisted SWIPT while considering a non-linear energy harvesting model has not been addressed yet. Besides, in contrast to works in [27], [29], [33], we also consider SIC decoding order at the receiver due to coupling between beamfroming design and subcarrier allocation. In the paper we aim at addressing these challenges.…”

Section: B Related Workmentioning

confidence: 99%

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Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

2020

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This paper proposes a resource allocation for multi carrier (MC) multiple input single output (MISO) non-orthogonal multiple access (NOMA) enabling simultaneous wireless information and power transfer (SWIPT) where a separated architecture (SA)-based heterogeneous network (HetNet) is considered. More precisely, we focus on designing MC MISO-NOMA scheme in HetNets, where each base stations (BSs) serves multiple information decoding (ID) and energy harvesting (EH) users with a non-linear energy harvesting model which are equipped with multi antennas. For this configuration, we propose a joint subcarrier assignment, beamforming design, and energy beamforming to maximize the total rate of the network. Moreover, we take into account the condition of cross-layer interference constraints to coordinate interference, satisfying a minimum data rate requirement, fulfilling a minimum harvested energy, and respecting the maximum allowed power transfer constraints. We also consider successive interference cancellation (SIC) decoding order to detect the signal of each user due to coupling between SIC order, beamforming design, and subcarrier allocation. As a result of interference in the rate function, our optimization problem is non-convex and thus challenging to solve. Subsequently, first we adopt semidefinite relaxation (SDR) for beamforming design and then an efficient algorithm via the majorization minimization (MM) approach based on the difference of convex (DC) programming is proposed to obtain a locally optimal solution for the original problem. Simulation results reveal the superiority of our proposed scheme as compared to other existing works addressed in the literature. INDEX TERMS Multi carrier (MC), multiple input single output (MISO), non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), subcarrier assignment, beamforming design, and successive interference cancellation (SIC).

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Section: Simulation Resultsmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

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Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

2020

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“…In fact, this iterative algorithm can be adopted to tighten the obtained lower bound where the solution of (38) in iteration (t) is exploited as an initial point for the next iteration (t + 1). It should be noted that the sub-optimal iterative algorithm reaches a locally optimal solution of the original problem (5) with a polynomial time complexity [16], [23]- [25], [32]- [34]. The flowchart of this suboptimal solution is depicted in Fig.…”

Section: Startmentioning

confidence: 99%

Optimal Multi-Objective Resource Allocation for D2D Underlaying Cellular Networks in Uplink Communications

et al. 2021

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In this paper, we study a resource allocation problem in orthogonal frequency division multiple access (OFDMA)-based Device-to-Device (D2D) communications. To this end, we propose a multi-objective optimization problem (MOOP) framework, which jointly maximizes the sum rate of D2D users (DUs) and cellular users (CUs) in uplink communications and minimizes the total transmit power. The proposed problem formulation takes into account the minimum data-rates and the maximum transmitted power budget for both DUs and CUs. We transform this MOOP into a single-objective optimization problem (SOOP) using the weighted sum method and then propose an approach to solve this SOOP via a monotonic approach yielding an efficient optimal solution. Furthermore, a suboptimal solution based on the successive convex approximation (SCA) is presented to compromise complexity and performance gain. This is done to reveal that the proposed suboptimal solution closely approaches an optimal solution through simulation analysis. Numerical results unveil an interesting tradeoff between D2Ds CUs and demonstrate the superiority of our proposed solution compared to other baseline schemes.

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An optimised resource allocation scheme based on NOMA-SWIPT in cooperative network

Potluri

Swarnalatha

2023

International Journal of Electronics

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Optimal Resource Allocation for MC-NOMA in SWIPT-Enabled Networks

Cited by 15 publications

References 16 publications

Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

Optimal Multi-Objective Resource Allocation for D2D Underlaying Cellular Networks in Uplink Communications

An optimised resource allocation scheme based on NOMA-SWIPT in cooperative network

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