Energy Efficiency Optimization for NOMA With SWIPT

Tang, Jie; Luo, Jingci; Liu, Mingqian; So, Daniel K. C.; Alsusa, Emad; Chen, Gaojie; Wong, Kai-Kit; Chambers, Jonathon A.

doi:10.1109/jstsp.2019.2898114

Cited by 183 publications

(162 citation statements)

References 49 publications

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“…Power domain Resource allocation [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] Energy harvesting and transfer [36][37][38][39][40][41][42][43][44][45][46][47][48][49] Interference cancellation techniques [50][51][52][53][54][55] Sleep/wake modes [56][57][58][59][60] Code domain Sparse code multiple access (SCMA) [61,62] Space time block coding (STBC) [56,63] Polar codes [64][...…”

Section: Domain Technology Citationsmentioning

confidence: 99%

“…It is an emerging research area in wireless networks in enhancing energy efficiency and the sustainability of the network [79]. The concept of simultaneous wireless information and power transfer was first addressed in [90] which led to many research works related to SWIPT [43,49]. The work of [90] deals with the fundamental trade-off between transmitting energy and information over a single noisy line simultaneously.…”

Section: Radio Frequency (Rf) Energy Harvestingmentioning

confidence: 99%

“…Here, the near users with strong channels act as energy harvesting relays that support the far users with weak channels. Furthermore, [49] addresses energy efficiency optimization using NOMA under combined power allocation and time switching techniques.…”

Section: Radio Frequency (Rf) Energy Harvestingmentioning

confidence: 99%

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A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

et al. 2020

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Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed.

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Section: Domain Technology Citationsmentioning

confidence: 99%

Section: Radio Frequency (Rf) Energy Harvestingmentioning

confidence: 99%

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A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

et al. 2020

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“…The Equation is quasiconcave . We use the Dinkelbach method to turn a quasiconcave objective function into a concave one, as indicated in Table to solve problem Equation , where U R = MR and

U_{T} = ϱ \sum_{j = 1}^{M} β_{j} P + M P_{c}

.…”

Section: Noma Optimizationmentioning

confidence: 99%

Nonorthogonal multiple access systems optimization to ensure maximum fairness to users

Jacob

Abrão

2020

Trans Emerging Tel Tech

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In this contribution, the optimization of power proportion allocated for each user in the downlink (DL) nonorthogonal multiple access (NOMA) systems have been developed. Successive interference cancellation technique recovers users' signal with high difference between channel gains, to find the lowest optimum power proportion required to guarantee an equal data rate for all active users.Following the same approach, the optimum power proportion for each user and also the minimum total power to achieve the same rate for all users (maximum fairness) were obtained as a design goal. Moreover, the same design methodology was developed seeking to maximize the NOMA system energy efficiency (EE). It was possible to find the maximum EE point and the respective power distribution among the users for a certain circuitry power consumption. For all NOMA users, in which the optimal operation point for EE maximization was parameterized, it was possible to find the total power, power ratio, and the equal rate values. As a result, one can find the trade-off point between EE and sum rate for each system scenario, as well as the best resource efficiency operation point. By considering the same rate for all users, the system attains maximum fairness among the users.Abbreviations: BS, base station; DL, downlink; EE, energy efficiency; NOMA, nonorthogonal multiple access; OMA, orthogonal multiple access; QoS, quality of service; RF, radio frequency; SE, spectral efficiency; SIC, successive cancellation of interference; SINR, signal-to-interference-plus-noise power ratio; SQP, sequential quadratic programming.Trans Emerging Tel Tech. 2020;31:e3875.wileyonlinelibrary.com/journal/ett

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“…Commonly available sources of energy are radio frequency (RF) and thermal energy that can be used for generating electrical energy in low-powered IoT devices. Recent studies on the energy harvesting of wireless devices have incorporated a number of aspects of such networks that range from physical layer security [9,10] to cognitive radio networks [11] and non-orthogonal multiple access [12,13]. However, the most focused source of energy harvesting in such works has been on thermal and vibration (mechanical) types of energy harvesters.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks

Saraereh

Alsaraira

Khan

et al. 2020

Sensors

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The Internet-of-things (IoT) has been gradually paving the way for the pervasive connectivity of wireless networks. Due to the ability to connect a number of devices to the Internet, many applications of IoT networks have recently been proposed. Though these applications range from industrial automation to smart homes, healthcare applications are the most critical. Providing reliable connectivity among wearables and other monitoring devices is one of the major tasks of such healthcare networks. The main source of power for such low-powered IoT devices is the batteries, which have a limited lifetime and need to be replaced or recharged periodically. In order to improve their lifecycle, one of the most promising proposals is to harvest energy from the ambient resources in the environment. For this purpose, we designed an energy harvesting protocol that harvests energy from two ambient energy sources, namely radio frequency (RF) at 2.4 GHz and thermal energy. A rectenna is used to harvest RF energy, while the thermoelectric generator (TEG) is employed to harvest human thermal energy. To verify the proposed design, extensive simulations are performed in Green Castalia, which is a framework that is used with the Castalia simulator in OMNeT++. The results show significant improvements in terms of the harvested energy and lifecycle improvement of IoT devices.

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Energy Efficiency Optimization for NOMA With SWIPT

Abstract: Index Terms-Energy efficiency (EE), non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), time switching (TS).

Cited by 183 publications

References 49 publications

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

Nonorthogonal multiple access systems optimization to ensure maximum fairness to users

A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks

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