Energy-Efficient and Fair Power Allocation Approach for NOMA in Ultra-Dense Heterogeneous Networks

Xiang, Lanhua; Chen, Hongbin

doi:10.1109/cyberc.2017.54

Cited by 15 publications

(18 citation statements)

References 17 publications

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“…The results show that the proposed offloading scheme enormously decreases the outage probability and enhances the ergodic rate of offloaded MBS users. Considering an ultra dense heterogeneous (SCMT) network, the authors in [125] proposed an optimal fair power allocation scheme which aims to maximize the overall energy efficiency of the considered network. The simulation results are presented in terms of energy efficiency for the considered network which demonstrate superior performance over conventional OMA based SCMT CNs.…”

Section: Noma In Single-cell Multi-tier Cellular Networkmentioning

confidence: 99%

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

et al. 2019

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The fifth generation (5G) wireless systems are anticipated to meet unprecedented capacity and latency requirements. In order to resolve these challenges in 5G, non-orthogonal multiple access (NOMA) is considered as a promising technique due to its ability to enhance spectrum efficiency and user access. As opposed to conventional orthogonal multiple access (OMA) which relies on orthogonal resource sharing, NOMA has a potential of supporting a higher number of users by multiplexing different users in the same resource in a non-orthogonal manner. With advanced receiver techniques, such as successive interference cancellation (SIC), the intra-user interference can be minimized at the NOMA receiver. To date, there are comprehensive surveys on NOMA, which describe the integration of NOMA with different communication technologies and discuss different NOMA classifications. However, the existing literature is scarce in reviewing state-of-the-art applications of NOMA from the perspective of its application to cellular networks (CNs), device-to-device (D2D) communications, and wireless sensor networks (WSNs). Therefore, the purpose of this survey is to fill this gap in knowledge. Specifically, NOMA with its underlying concepts are elaborated in detail. In addition, detailed system model of different NOMA-based wireless networks is presented. Furthermore, irrespective of the underlying spatial topology of the considered NOMA-based wireless network, general analytical expressions are presented to characterize the network performance. Finally, some challenges related to NOMA design are highlighted and potential research directions are pointed out to address these issues.

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Section: Noma In Single-cell Multi-tier Cellular Networkmentioning

confidence: 99%

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

et al. 2019

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“…One of the main objectives of QoS is the fairness. To grant the fairness and quality of service for all users, fair power allocation (FPA) [5] scheme is adopted to see each user's power need properly attended then the user's rate is calculated to check whether rate constraint is fulfilled. Algorithm 1 explains the mechanism of our proposed power allocation scheme.…”

Section: Utility Functionmentioning

confidence: 99%

“…Initialization: σ, P t , R th , t = 0, initial bid b c (0) = λ, Calculate p c (0) for all clusters using (11) for all c ∈ ℵ Calculate p c (t + 1) using (12) Calculate b c (t + 1) through (13) Perform user's power allocation using FPA as in Reference [5] end for for all users in cluster c if R m,i,l ≥ R th p c = p c (t + 1) else t = t + 1 end if end for if converge (no change in bidding status) break end if…”

Section: Algorithm 1 Auction-based Power Allocation Schemementioning

confidence: 99%

“…In Reference [4], the authors introduced an energy efficient power allocation for a multi-carrier NOMA (MC-NOMA) system, with the proportional rate constraints to guarantee fairness among users. The authors of Reference [5] put fairness as a priority in designing an energy efficient power allocation scheme for NOMA in ultra-dense heterogeneous networks. The study in Reference [6] considered designing the power allocation algorithm under imperfect channel state information.…”

Section: Introductionmentioning

confidence: 99%

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Clustering and Auction-Based Power Allocation Algorithm for Energy Efficiency Maximization in Multi-Cell Multi-Carrier NOMA Networks

Adam

Wang

2019

Applied Sciences

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In this paper, we investigate the energy efficiency (EE) maximization in multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks. To achieve this goal, an optimization problem is formulated then the solution is divided into two parts. First, we investigate the inter-cell interference mitigation and then we propose an auction-based non-cooperative game for power allocation for base stations. Finally, to guarantee the rate requirements for users, power is allocated fairly to users. The simulation results show that the proposed scheme has the best performance compared with the existing NOMA-based fractional transmit power allocation (FTPA) and the conventional orthogonal frequency division multiple access (OFDMA).

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“…The research studies in [15]- [18] are mainly focused on solving the resource allocation problem based on overall energy efficiency without considering the transmitting and receiving power consumption in the optimization process. This leads to unfairness among users because such designs favor the stronger channel gain users over the weaker channel gain users [19].…”

Section: Introductionmentioning

confidence: 99%

Fair Energy-Efficient Resource Allocation for Downlink NOMA Heterogeneous Networks

et al. 2020

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The increasing in energy consumptions of the current wireless networks, leads towards designing energy-efficient 5G networks. The application of non-orthogonal multiple access (NOMA) in the heterogeneous networks (HetNets) improves the spectrum utilization with the cost of efficient resource allocation. Hence, this paper proposes optimal user-pairing and power allocation solutions towards achieving fair energy-efficient resource allocation in downlink femtocell NOMA-HetNets. In the proposed optimization process, the considered constraints are the user's transmission rate, transmit power budget at the base station (BS), and the interference. The energy consumption of both the transmitter and the receiver are considered to simulate the real system design. The Greedy Algorithm (GA) is used to achieve a low-complex optimal solution during the user-pairing process. Simultaneously, the max-min energy efficiency optimization approach is employed to maximize the minimum energy efficiency of the femtocell users to achieve the optimal power allocation solution. The mathematical formulation of the max-min energy efficiency is a nonconvex fractional programming problem and is intractable. Thus, the fractional programming theory is adopted to transform the problem into a sequence of subtractive form, followed by the Sequential Convex Programming (SCP) approach to determine the optimal solution. Simulation results show that the proposed NOMA with optimal power allocation method using SCP and GA (NOMA-SCP-GA) achieves fair energy efficiency performance with lower complexity compared to the benchmark methods. Moreover, the minimum energy efficiency of the femtocell user is 38.22% higher than NOMA with Difference of Convex programming (NOMA-DC). The NOMA-SCP-GA method can assure 5G capability demands.

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Energy-Efficient and Fair Power Allocation Approach for NOMA in Ultra-Dense Heterogeneous Networks

Cited by 15 publications

References 17 publications

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

Clustering and Auction-Based Power Allocation Algorithm for Energy Efficiency Maximization in Multi-Cell Multi-Carrier NOMA Networks

Fair Energy-Efficient Resource Allocation for Downlink NOMA Heterogeneous Networks

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