Optimal power allocation and user selection in non-orthogonal multiple access systems

Non-Orthogonal Multiple Access (NOMA) has been proposed recently as an emerging radio access technology for the Fifth Generation (5G) to achieve high spectral efficiency (SE). In addition, simultaneous wireless information and power transfer (SWIPT) has been receiving exceptional attention because of its role in increasing energy efficiency (EE). In this paper, the performance of the downlink SWIPT-NOMA system has been evaluated. In this paper, signal to interference and noise ratio (SINR) is derived for near and far users with outage probability for each user, where the near user acts as an energy harvesting (EH) node. The Genetic algorithm (GA) is used as an optimization technique for the power splitting ratio and power allocation coefficients to maximize the EE under eligible SE. The outage probability for the near and far user is taken into consideration for the optimization process. In this work, the results from the SE-EE metric show that the maximum EE reached 0.325 Mbits/J at SE of 9 bits/sec/Hz.On the other hand, the use of radio-frequency (RF) signals for the Simultaneous Wireless Information and Power Transfer (SWIPT) has become a valuable source of energy harvesting (EH) because it is able to simultaneously carry both energy and information [17]. Another alternative power source from the wireless transmission that can be exploited by the use of near-field wireless power transfer (WPT) is presented in [18]. EH brings more improvement in energy efficiency compared to conventional cooperative relaying by decreasing the energy consumption. On the other hand, the use of SWIPT may reduce spectral efficiency (SE) [19] because the maximization of the total data rate will achieve higher SE for the next wireless generation.

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“…In Ref. [14], the authors looked at power and channel allocation of downlink cellular systems. Authors in Ref.…”

Section: Related Workmentioning

confidence: 99%

“…After substitute (14) and (15) into (12) and after mathematical simplification, assuming σ sm 2 = σ 2 sn = . σ 2 sn = σ 2 , the SINR from the near to far user can be written as: where γ = E s σ 2 I represents the interference and can be written as:…”

Section: Of 19mentioning

confidence: 99%

Energy-Efficient Downlink for Non-Orthogonal Multiple Access with SWIPT under Constrained Throughput

2019

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“…Iterative and noniterative water filling algorithms are proposed to allocate the power among NOMA users sharing the same resource block. In our methods, we use a modified version of the optimum power allocation strategy presented in Datta and Kalyanasundaram to take nonfull buffer user traffic model into account.…”

Section: Related Workmentioning

confidence: 99%

“…K is the total number of users, and

N_{\max}

is the maximum number of users that can be assigned to a single resource block. The power allocation between the selected users can be either fixed for all combinations or selected optimally to maximize the PF metric for a given user set …”

Section: User Demand–based Resource Allocation For Noma Systemsmentioning

confidence: 99%

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Gemici

Kara

Hökelek

et al. 2018

Int J Communication

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Nonorthogonal multiple access (NOMA) is one of the key technologies for 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The most of the proportional fairness (PF)-based resource allocation studies for NOMA systems assumes full buffer traffic model, while the traffic in real-life scenarios is generally nonfull buffer. In this paper, we propose User Demand-Based Proportional Fairness (UDB-PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for user scheduling and power allocation in NOMA downlink systems when traffic demands of the users are limited and time-varying. UDB-PF extends the PF-based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network-wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource, while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the genetic algorithm (GA) approach is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB-PF yields better sum rate (throughput) while PUSF provides better network-wide user satisfaction results compared with the PF-based user scheduling. We also observed that the GA-based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search.

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“…For the case without instantaneous CSI, a sum power minimization problem was resolved in [25] subject to outage probabilistic constraints and the optimal decoding order. The work of [26] provided an optimal power allocation solution to maximize the weighted sum rate of all users subject to a total power constraint.…”

Section: A Related Workmentioning

confidence: 99%

Joint Rate Control and Power Allocation for Non-Orthogonal Multiple Access Systems

Bao

Chen

et al. 2017

IEEE J. Select. Areas Commun.

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Abstract-This paper investigates the optimal resource allocation of a downlink non-orthogonal multiple access (NOMA) system consisting of one base station and multiple users. Unlike existing short-term NOMA designs that focused on the resource allocation for only the current transmission timeslot, we aim to maximize a long-term network utility by jointly optimizing the data rate control at the network layer and the power allocation among multiple users at the physical layer, subject to practical constraints on both the short-term and long-term power consumptions. To solve this problem, we leverage the recently-developed Lyapunov optimization framework to convert the original long-term optimization problem into a series of online rate control and power allocation problems in each timeslot. The power allocation problem, however, is shown to be non-convex in nature and thus cannot be solved with a standard method. However, we explore two structures of the optimal solution and develop a dynamic programming based power allocation algorithm, which can derive a globally optimal solution, with a polynomial computational complexity. Extensive simulation results are provided to evaluate the performance of the proposed joint rate control and power allocation framework for NOMA systems, which demonstrate that the proposed NOMA design can significantly outperform multiple benchmark schemes, including orthogonal multiple access (OMA) schemes with optimal power allocation and NOMA schemes with non-optimal power allocation, in terms of average throughput and data delay.

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Optimal power allocation and user selection in non-orthogonal multiple access systems

Cited by 31 publications

References 4 publications

Energy-Efficient Downlink for Non-Orthogonal Multiple Access with SWIPT under Constrained Throughput

Energy-Efficient Downlink for Non-Orthogonal Multiple Access with SWIPT under Constrained Throughput

User scheduling and power allocation for nonfull buffer traffic in NOMA downlink systems

Joint Rate Control and Power Allocation for Non-Orthogonal Multiple Access Systems

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