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

Adam, Abuzar B. M.; Wang, Xiaoyu; Wang, Zhengqiang

doi:10.1109/access.2020.3039242

Cited by 16 publications

(9 citation statements)

References 49 publications

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“…• We analyze the impact of any suboptimal decoding order on the capacity region of multicell NOMA. In contrast to [20], [23]- [27], we show that under any fixed (thus suboptimal) 3 Imposing the commonly-used SIC necessary condition in NOMA clustering among users would result a suboptimal performance. The global optimality can be guaranteed only if the optimal decoding orders be completely independent from ICI levels at all the cells for some channel conditions.…”

Section: B Our Contributionsmentioning

confidence: 72%

“…• We prove that under any suboptimal decoding order, guaranteeing successful SIC at all the users by imposing the commonly-used SIC necessary constraint on power allocation [23]- [27] may significantly degrade the total spectral efficiency of users.…”

Section: B Our Contributionsmentioning

confidence: 95%

“…eliminating the exploration area of finding optimal rate allocation [20], [23], [25]- [27]. According to (2), to guarantee that user i ∈ U b achieves its Shannon's capacity for decoding its desired signal after successful SIC at users, the condition in (4) should be satisfied for each user k ∈ Φ b,i .…”

mentioning

confidence: 99%

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Optimal SIC Ordering and Power Allocation in Downlink Multi-Cell NOMA Systems

Rezvani,

Jorswieck,

Mokari

et al. 2021

Preprint

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In this work, we consider the problem of finding globally optimal joint successive interference cancellation (SIC) ordering and power allocation (JSPA) for the general sum-rate maximization problem in downlink multi-cell NOMA systems. We propose a globally optimal solution based on the exploration of base stations (BSs) power consumption and distributed power allocation. The proposed centralized algorithm is still exponential in the number of BSs, however scales well with larger number of users.For any suboptimal decoding order, we address the problem of joint rate and power allocation (JRPA) to achieve maximum users sum-rate. Furthermore, we design semi-centralized and distributed JSPA frameworks with polynomial time complexity. Numerical results show that the optimal decoding order results in significant performance gains in terms of outage probability and users total spectral efficiency compared to the channel-to-noise ratio (CNR)-based decoding order known from single-cell NOMA.Moreover, it is shown that the performance gap between our proposed centralized and semi-centralized frameworks is quite low. Therefore, the low-complexity semi-centralized framework with near-to-optimal performance is a good choice for larger number of BSs and users.

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Section: B Our Contributionsmentioning

confidence: 72%

Section: B Our Contributionsmentioning

confidence: 95%

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Optimal SIC Ordering and Power Allocation in Downlink Multi-Cell NOMA Systems

Rezvani,

Jorswieck,

Mokari

et al. 2021

Preprint

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show abstract

“…It is still unknown how to equivalently transform (30b) to a convex form. To this end, the globally optimal solution of (30) with polynomial time complexity is not yet obtained in the One suboptimal solution for (30) is to approximate each nonconcave rate function ( ) to its first order Taylor series, and then apply the sequential programming method [15], [44], [58]. A suboptimal penalty function method is also used in [45].…”

Section: B Hybrid-noma With Per-user Minimum Rate Constraintsmentioning

confidence: 99%

Optimal Power Allocation in Downlink Multicarrier NOMA Systems: Theory and Fast Algorithms

Rezvani

Jorswieck

Joda

et al. 2022

IEEE J. Select. Areas Commun.

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In this work, we propose globally optimal power allocation strategies to maximize the users sum-rate (SR), and system energy efficiency (EE) in the downlink of single-cell multicarrier non-orthogonal multiple access (MC-NOMA) systems. Each NOMA cluster includes a set of users in which the wellknown superposition coding (SC) combined with successive interference cancellation (SIC) technique is applied among them. By obtaining the closed-form expression of intra-cluster power allocation, we show that MC-NOMA can be equivalently transformed to a virtual orthogonal multiple access (OMA) system, where the effective channel gain of these virtual OMA users is obtained in closed-form. Then, the SR and EE maximization problems are solved by using very fast water-filling and Dinkelbach algorithms, respectively. The equivalent transformation of MC-NOMA to the virtual OMA system brings new theoretical insights, which are discussed throughout the paper. The extensions of our analysis to other scenarios, such as considering users rate fairness, admission control, long-term performance, and a number of future nextgeneration multiple access (NGMA) schemes enabling recent advanced technologies, e.g., reconfigurable intelligent surfaces are discussed. Extensive numerical results are provided to demonstrate the performance gaps among single-carrier NOMA (SC-NOMA), OMA-NOMA, and OMA.

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“…The non-convex FP problem was initially transformed into two sub-problems and then an iterative method and a closed-form method were proposed to solve power distribution and bandwidth allocation, respectively. The EE maximization problem for downlink multi-cell NOMA networks was investigated in [22]. The formulated maximization problem is mixed-integer non-convex and NPhard.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Resource Allocation for 5G Heterogeneous Networks Using Genetic Algorithm

Qi¹,

Khattak

Zaib

et al. 2021

IEEE Access

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The energy efficient resource allocation scheme based on genetic algorithm (GA) for the downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) is developed in this paper. To maximize the spectrum efficiency for the fifth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cell interference coordination techniques are required to mitigate the inter-cell interference for 5G HetNets. In this paper, the energy efficient optimization problem based on coordinated scheduling is formulated, which is a mixed-integer nonlinear fractional programming problem and is intractable to solve directly. To tackle this, a two-step GA based scheme is proposed to solve the optimization problem. In the first step, the resource blocks matrix is solved by normal GA in the spectral efficiency aspect with fixed power distribution matrix, and then the power distribution matrix is obtained in the second step by non-dominated sorting genetic algorithm II (NSGA-II) with obtained resource blocks allocation matrix. Finally, the system level numerical evaluation process is provided to illustrate the effectiveness of the developed scheme.INDEX TERMS Energy efficiency, resource allocation, heterogeneous networks, genetic algorithm.

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

Cited by 16 publications

References 49 publications

Optimal SIC Ordering and Power Allocation in Downlink Multi-Cell NOMA Systems

Optimal SIC Ordering and Power Allocation in Downlink Multi-Cell NOMA Systems

Optimal Power Allocation in Downlink Multicarrier NOMA Systems: Theory and Fast Algorithms

Energy Efficient Resource Allocation for 5G Heterogeneous Networks Using Genetic Algorithm

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