Energy-Efficient D2D Communications Underlaying NOMA-Based Networks With Energy Harvesting

Pei, Lu; Yang, Zhaohui; Pan, Cunhua; Huang, Wenhuan; Ming, Chi; Elkashlan, Maged; Nallanathan, Arumugam

doi:10.1109/lcomm.2018.2811782

Cited by 88 publications

(75 citation statements)

References 8 publications

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“…End if (10) End for (11) t nm � t nm + 1; (12) End while (13) 6 Mobile Information Systems h Bn,2 , E sum n,k , E cons n,k , and E n,k , and the output is online transmission power P d,on * nm,k , where E sum n,k � k− 1 t�1 E n,t represents the total energy harvested in the k − 1 epochs before epoch k and E cons n,k � k− 1 t�1 τ e P d * nm,t represents the total energy consumed in the k − 1 epochs before epoch k. Before training, the input parameters are normalized. Normalization can ensure that each input parameter provides the same influence in the neural network and can make the training process more stable and the convergence speed faster.…”

Section: Online Power Allocation Optimization Algorithmmentioning

confidence: 99%

“…Users can harvest energy by wireless power transfer or from the surrounding environments. Authors in [9][10][11][12][13] investigate the resource allocation issue when D2D transmitters harvest energy by wireless power transfer. However, when the distance between the users and the power station is far, the method of wireless power transfer will lead to serious energy waste due to the path loss.…”

Section: Introductionmentioning

confidence: 99%

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Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

Zhu

Wang

2020

Mobile Information Systems

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In this work, we propose a channel allocation and power control algorithm for energy harvesting (EH) device-to-device (D2D) communication based on nonorthogonal multiple access (NOMA). e algorithm considers users' quality of service (QoS) and energy causality constraint to maximize the total capacity of D2D groups. e optimal offline allocation of channel and power is realized firstly. en, the offline optimization results are taken as the training dataset to train the neural network to obtain the optimal model of the transmission power. e online power allocation optimization algorithm is further proposed. Simulation results show that the offline algorithm can improve the total capacity of D2D groups, and the performance of the online algorithm is close to the offline algorithm.

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Section: Online Power Allocation Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

Zhu

Wang

2020

Mobile Information Systems

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“…However, a conventional OMA-based paired D2D communication is considered and the system model is limited to single-cell scenario only. The authors in [162] considered a paired D2D communication underlying a NOMA-based cellular network in which a single hybrid access point is used to receive from both D2D and cellular users. In particular, they investigate the problem of resource allocation and propose a low complexity energy efficient algorithm for the D2D pair while meeting the QoS requirements of cellular users.…”

Section: Noma Applied To Device-to-device Communicationsmentioning

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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“…[25][26][27][28] The D2D communication in cellular networks is defined as a direct communication between 2 mobile users without traversing the BS or core network. [25][26][27][28] The D2D communication in cellular networks is defined as a direct communication between 2 mobile users without traversing the BS or core network.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is meaningful and possible to further improve the spectral efficiency of such 2-tier HetNets by imbedding new techniques.It is well known, among the key techniques of 5G, that device-to-device (D2D) communication technique is also a promising candidate. [25][26][27][28] The D2D communication in cellular networks is defined as a direct communication between 2 mobile users without traversing the BS or core network. 29 The advantages of D2D communications are that they can not only enhance spectral efficiency but also potentially extend cellular coverage, improve energy efficiency, delay, and fairness.…”

mentioning

confidence: 99%

Energy‐spectrum‐efficient three‐tier heterogeneous networks with D2D harvesting energy and uplink coverage analysis

Jia

Fan

et al. 2018

Int J Communication

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To guard the communication quality of cell edge users (CEUs) and simultaneously improve the energy-spectrum efficiency, a novel 3-tier heterogeneous network (HetNet) model is proposed, which consists of macro cells, femtocells, and device-to-device (D2D) networks. Specially, with a predefined cell split factor R, the macro cell users are split into as cell center users (CCUs) and CEUs, respectively. Correspondingly, the total available spectrum band consisting of N channels is divided into CCU band and CEU band with a given coefficient p m . The CCU band containing p m N subchannels is shared by CCUs and femtocell users (FUs), and the CEU band containing(1 − p m ) N subchannels is shared by D2D users and CEUs. The perfect network synchronization is assumed, and a communication round consists of downlink transmission and uplink transmission phases. The battery-free D2D terminals harvest energy from the ambient radio frequency interference in the downlink transmission phase based on inverse power control scheme and communicate in the uplink transmission phase only when they harvest enough energy to perform channel inversion toward the receiver. For such 3-tier HetNets, by modeling the network elements as independent Poisson point processes (PPPs) and using stochastic geometry method, we first investigate the sufficiency probability that a D2D transmitter harvests enough energy to establish a communication link. Then, by combining sufficiency probability and channel access probability, the thinned independent PPPs for the locations of CCUs, CEUs, FUs, and D2D users are modeled. Based on these thinned PPP models, we perform a comprehensive investigation on the coverage probabilities of CCU, CEU, and FU uplinks as well as the D2D transmission. The simulated and numerical results show that using the presented cell split strategy enhances the performance of CCUs and CEUs because of the decrease of interference. The presented comparison analysis displays that the effect of D2D networks on the macro cell or the whole HetNets is limited and can be omitted. Therefore, the energy and spectrum efficiencies of networks are enhanced, simultaneously. At the same time, our results indicate that by using our derivations, we can perform the optimal design of the HetNets. KEYWORDScell center user, cell edge user, cell split, energy harvesting, heterogeneous networks 1 | INTRODUCTION Nowadays, with the proliferation of smart phones, tablets, and data-hungry multimedia applications, there has been exponential growth in mobile data and traffic. In recent report, 1 Cisco predicts that mobile data traffic will hit an annual run rate of 367.2 exabytes by 2020. More specifically, a compound annual growth rate to the data traffic from 2015 to 2020 is 53%. The fast and continuous growing mobile data traffic causes the deficiency of cellular network capacity. To mitigate this problem and meet the exponential growth of mobile traffic, the network operators have already started to devise new solutions. An advanced approach is strongly required ...

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Energy-Efficient D2D Communications Underlaying NOMA-Based Networks With Energy Harvesting

Cited by 88 publications

References 8 publications

Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

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

Energy‐spectrum‐efficient three‐tier heterogeneous networks with D2D harvesting energy and uplink coverage analysis

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