A Novel Power Allocation Method for Non-orthogonal Multiple Access in Cellular Uplink Network

Sheng, Ziqi; Su, Xin; Zhang, Xuewu

doi:10.1109/ie.2017.17

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…In [13], Di et al formulated the centralized scheduling and resource allocation problem as equivalent to a multi-dimensional stable roommate matching problem, in which the users and time/frequency resources are considered as disjoint sets of objects to be matched with each other. The particle swarm genetic algorithm allocates power to each sub-channel based on channel state information (CSI) [14], which can achieve better performance than the traditional average power allocation and water-filling algorithm. Considering the majority of resource allocation algorithms divided the entire bandwidth into sub-bands did not fully exploit the potential of NOMA.…”

Section: A Existing Research On Nomamentioning

confidence: 99%

“…(1) Adopt heuristic algorithm, such as the genetic algorithm mentioned in the literature [14], [22], particle swarm algorithm, etc. This type of algorithm does not have a strict theoretical basis, it is inspired by people's actual life experience and rules of things.…”

Section: B Optimization Problem Formulationmentioning

confidence: 99%

“…Constraint (13) indicates that the sum of power levels allocated by all users in the entire bandwidth cannot exceed the total power P total transmitted by the BS. Constraint (14) indicates that the maximum number of users multiplexed on each sub-channel cannot exceed M u . Constraint ( 15) ensures each user can only select one power level on each sub-channel.…”

Section: A Optimization Problem Conversionmentioning

confidence: 99%

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Spectrum Resource and Power Allocation With Adaptive Proportional Fair User Pairing for NOMA Systems

Long

Wang

et al. 2019

IEEE Access

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In this paper, we investigate the spectrum resource and power allocation problem for the tradeoff between maximizing the sum rate and minimum rate requirements of users in non-orthogonal multiple access (NOMA) system. First, we formulate the NOMA techniques, basic principles, and double-objective optimization (DOO) problem. Then, the non-convexity of the DOO problem is converted into a single-objective optimization (SOO) problem by power discretization method. Global optimal search (GOS) algorithm is applied to solve the user-subchannel matching and power allocation problem. Due to its high complexity and unfairness among users, it is only suitable for determining the upper bound of users throughput performance. Finally, yet importantly, a spectrum resource and power allocation algorithm with adaptive proportional fair (APF) user pairing is proposed to convert the original optimization problem into user pairing, sub-channel, and power allocation. The users paired on the sub-channel are determined by the scheduling priority which is based on the equivalent channel gain. The BS dynamically adjusts the forgetting factor in the APF algorithm based on the variance of all the users' scheduling priorities so as to influence the update of users' scheduling weights. The power allocation stage proposes three power allocation schemes to ensure the users' minimum data rate requirements under the condition that effectively guarantees the correct execution of successive interference cancellation (SIC). The simulation results demonstrate that it can not only approach the throughput performance compared with the global optimal search and the classical water-filling (WF) power allocation using matching theory but also can improve the fairness of the users.INDEX TERMS Non-orthogonal multiple access (NOMA), spectrum resource and power allocation, global optimal search (GOS), adaptive proportional fair (APF) user pairing, fairness.

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Section: A Existing Research On Nomamentioning

confidence: 99%

Section: B Optimization Problem Formulationmentioning

confidence: 99%

Section: A Optimization Problem Conversionmentioning

confidence: 99%

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Spectrum Resource and Power Allocation With Adaptive Proportional Fair User Pairing for NOMA Systems

Long

Wang

et al. 2019

IEEE Access

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“…In order to solve the resource allocation problem, studies have been conducted using optimization algorithms. One of the studies addressing the resource allocation problem proposes particle swarm optimization to maximize signal-to-interference-plus-noise ratio (SINR) and increase total user capacity [30]. Particle swarm optimization is one of the evolutionary computation methodologies that is used to find the approximate optimal solutions for non-convex problems using the idea of inertia and acceleration which are constantly adjusted by measuring how far current values are to the best solution.…”

Section: Ga-based Resource Allocationmentioning

confidence: 99%

Grant-Free Resource Allocation for NOMA V2X Uplink Systems Using a Genetic Algorithm Approach

et al. 2020

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While NOMA-V2V (non-orthogonal multiple accesscan-vehicle-to-vehicle) effectively achieve massive connectivity requirements in 5G network systems, minimizing communication latency is a very crucial challenge. To address the latency problem, we propose a channel allocation method called hyper-fraction, which divides the road into many zones and allocates a channel to each zone. Then, a vehicle located within the corresponding zone uses the channel allocated to the zone. Hyper-fraction will allow the system to minimize communication latency between a user equipment (UE) and a base station (BS) caused by scheduling processes and consequentially reduce the overall latency of the system. In the simulation, a novel concept of genetic algorithm (GA) is utilized, called GA with continuous pool. It is an approach to enable conventional GA to solve optimization problems for continuous situations within much less computation, especially in situations where the elements in the system keep moving such as vehicular networks. As a result, GA with continuous pool is proven to be an effective heuristic method to improve throughput rate, as well as hyper-fraction improving the latency of NOMA V2V and vehicle-to-infrastructure (V2I) systems.

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“…Unlike conventional multiple access techniques, NOMA can meet users' QoS requirements and improve fairness by allocating resource dynamically, in which users with poor channel conditions are allocated more power and considerable total throughput can be achieved. NOMA can also achieve a high gains in capacity and system throughput performance in cellular radio access network [43] so that NOMA is popular in 5G communication to meet demands of enhanced mobile broadband, low latency and massive machine type of communication. Power-splitting which is also called half-duplex operation and time-switching which is also called asynchronous transmission are two typical modes in NOMA.…”

Section: Introductionmentioning

confidence: 99%

Joint Spectrum Resource Allocation in NOMA-based Cognitive Radio Network With SWIPT

Song¹,

Wang

Liu³

et al. 2019

IEEE Access

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In a conventional cognitive radio (CR) network, only when the primary user's (PU) frequency bands are sensed to be free, secondary users (SUs) can utilize these frequency band resources. Therefore, spectrum sensing (SS) can improve spectrum utilization. Spectrum sharing means that the SUs are allowed to utilize the licensed spectrum bands belonging to the PU to transmit information with PU simultaneously. Spectrum sharing performs well under the conditions that the interference to the PU is assured to be less than a certain threshold. Non-orthogonal multiple access (NOMA) has attracted considerable interests in recent years, which is seen as an important wireless access scheme for the coming 5G wireless communication system. Simultaneous wireless information and power transfer (SWIPT) is proposed as a popular technique to extend the operation duration of power-supply-limited wireless networks. The CR-NOMA is seen as a special form of the power-domain NOMA, wherein the requirements of the SU and PU are strictly met so that excellent system performance can be achieved. In this paper, a joint frame structure is described, wherein SUs first perform SWIPT for spectrum sensing and then transmit information via an overlay and underlay mode. Moreover, the optimization problem to maximize the achievable throughput for the CR network is presented to obtain the optimal sensing slot, while the total transmission power and the minimum rate requirements of the SUs are both constrained. A joint power allocation and sensing time optimizing algorithm based on dichotomy method are proposed to achieve the optimal solution. The simulation results show that there is a maximal throughput via setting an optimal sensing time for the secondary network.

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A Novel Power Allocation Method for Non-orthogonal Multiple Access in Cellular Uplink Network

Cited by 9 publications

References 7 publications

Spectrum Resource and Power Allocation With Adaptive Proportional Fair User Pairing for NOMA Systems

Spectrum Resource and Power Allocation With Adaptive Proportional Fair User Pairing for NOMA Systems

Grant-Free Resource Allocation for NOMA V2X Uplink Systems Using a Genetic Algorithm Approach

Joint Spectrum Resource Allocation in NOMA-based Cognitive Radio Network With SWIPT

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