Outage Energy Efficiency Maximization for UAV-Assisted Energy Harvesting Cognitive Radio Networks

He, Xiao; Jiang, Hong; Deng, Liping; Luo, Ying; Zhang, Qiuyun

doi:10.1109/jsen.2022.3154801

Cited by 25 publications

(24 citation statements)

References 45 publications

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“…According to Xiao et al, 24 the UAV surplus power at moment t can be employed to determine the ruin probability within a limited interval.…”

Section: Uav Ruin Theorymentioning

confidence: 99%

“…In this formulation, formulation (24) is NP-complete, and finding the optimal solution for such problems is impossible in a time-limit frameworks especially in a large-scale system. In fact, solving this problem through exhaustive search methods will result in high degrees of computational complexity and require a great deal of time.…”

Section: Formulation Of Ruin-based Problemmentioning

confidence: 99%

“…As a result, the surplus energy presented in this model can be expressed as (18):

{\rho}_u(t)={\rho}_0+\rho t-{S}_u.

According to Xiao et al, 24 the UAV surplus power at moment

t

can be employed to determine the ruin probability within a limited interval.Remark The limited ruin probability is equivalent to the probability of having under‐zero surplus energy at any given operational time

s

within the limited time

t

. This ruin probability is formulated as below within the limited time:

$$ \psi \left({\rho}_0,t\right)=\Pr \left[{\rho}_u(s)<0,\kern0.5em \mathrm{if}\kern0.5em 0<s<t\right].

…”

Section: Ruin‐based Approach For Cell Association and Resource Optimi...mentioning

confidence: 99%

“…Therefore, many energy-efficient solutions have been proposed in recent years to solve this problem in UAV-based communication networks. 24 That is, the researchers in Reference 25 proposed game theory for energy consumption optimization within the image coverage intervals of urban roads through the non-cooperative periodic flights of UAVs. Their proposed method managed to optimize energy consumption in distributed single UAVs.…”

Section: Introductionmentioning

confidence: 99%

“…A serious problem with the use of UAVs is their limited energy for providing services for cellular users. Therefore, many energy‐efficient solutions have been proposed in recent years to solve this problem in UAV‐based communication networks 24 . That is, the researchers in Reference 25 proposed game theory for energy consumption optimization within the image coverage intervals of urban roads through the non‐cooperative periodic flights of UAVs.…”

Section: Introductionmentioning

confidence: 99%

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A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

Mirzaei

2022

Concurrency and Computation

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The dense deployment of small cells is a key feature of the next-generation cellular networks aimed at providing the necessary capacity increase. But in such networks the problem of green networking will be of great importance, because the uncontrolled installation of too many cells may increase operational costs and emit more carbon dioxide. Nowadays, unmanned aerial vehicles (UAVs) offer an efficient approach to improve the quality, data rate, and meet the demanding performance requirements of applications in ultra-dense cellular networks. This article proposes a dynamic optimization model which minimizes the overall energy consumption of UAV cellular networks in addition to guarantying the essential coverage and capacity. The proposed model optimizes user association and power utility to meet users' QoS requirements with the highest level of energy efficiency (EE). For this purpose, the surplus energy pattern of UAVs is first mathematically formulated and then applied to calculate its ruin probability. In fact, the ruin probability denotes the vulnerability of a UAV when it runs out of energy. The ruin probability is used in the next step to efficiently connect every user to the UAVs. Also, power allocation is implemented for the applications to achieve the optimal value of the accessible network's data rate through the water-filling method. This model also performs coded routing in the multi-hop backhauls to efficiently use the existing infrastructure of the cooperative networks for coding dual-hop transmissions. The simulation results exhibit considerable network throughput and EE increase by 42% and 30%, respectively, for the proposed ruin-based energy-efficient approach in comparison with the conventional signal-to-interference/noise ratio-based schemes.

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“…According to Xiao et al, 24 the UAV surplus power at moment t can be employed to determine the ruin probability within a limited interval.…”

Section: Uav Ruin Theorymentioning

confidence: 99%

Section: Formulation Of Ruin-based Problemmentioning

confidence: 99%

“…As a result, the surplus energy presented in this model can be expressed as (18):

{\rho}_u(t)={\rho}_0+\rho t-{S}_u.

According to Xiao et al, 24 the UAV surplus power at moment

t

s

within the limited time

t

. This ruin probability is formulated as below within the limited time:

$$ \psi \left({\rho}_0,t\right)=\Pr \left[{\rho}_u(s)<0,\kern0.5em \mathrm{if}\kern0.5em 0<s<t\right].

…”

Section: Ruin‐based Approach For Cell Association and Resource Optimi...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

Mirzaei

2022

Concurrency and Computation

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Outage and throughput performance analysis of smart UAV‐assisted full‐duplex NOMA‐based energy harvesting cognitive radio networks

Kumar Bag,

Samanta,

Kumar De

et al. 2023

Int J Communication

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SummaryIn this paper, the throughput and outage performance for an unmanned aerial vehicle (UAV)‐assisted non‐orthogonal multiple access (NOMA)‐based hybrid cognitive radio (CR) network are examined under m‐Nakagami fading channel. To be more specific, a secondary source transmitter () broadcasts a NOMA‐enabled mixed signal to secondary destinations via UAV relay, which operates in full‐duplex (FD) mode and employs decode‐and‐forward protocol. In our approach, an energy harvesting (EH) circuit is employed at both and UAV to harvest energy from the PU radio frequency (RF) signals. These secondary transmitters are also incorporated with energy detector (ED) circuit as well, which detects the activity of the primary user (PU). The status of PU to be busy or idle is confirmed on the basis of the energy detector's results. In turn, this drives and UAV to switch between underlay and overlay protocols in an adaptive manner to increase spectrum efficiency (SE). The closed form mathematical expressions of the secondary outage probability for NOMA‐based UAV equipped CR networks under imperfect successive interference cancellation (i‐SIC) conditions have been evaluated. The administration of the power allocation policy at the and UAV is assessed while maintaining the PU quality of service (QoS). Finally, MATLAB simulation testbed has been used to verify all the analytical closed form expressions.

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On the performance of uplink NOMA‐based satellite‐aerial‐terrestrial integrated networks

Yuan

Ouyang

Liu

et al. 2023

Trans Emerging Tel Tech

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In this article, we study the performance for a satellite-aerial-terrestrial integrated network with imperfect successive interference cancellation (SIC), where the combination of uplink non-orthogonal multiple access (NOMA) technology with beamforming (BF) scheme is implemented. First, to maximize the ergodic sum rate of the uplink NOMA-based satellite network, a BF scheme is proposed with statistical channel state information. Then, assuming that the terrestrial-UAV links undergo correlated Rayleigh fading and the UAV-satellite link experiences correlated Shadowed-Rician fading respectively, the derivation processes of the exact expressions are provided for our system sum rate and energy efficiency with imperfect SIC. Eventually, results together with simulation and analysis are given to validate the correctness of our study. In addition, our proposed scheme has superiority in system performance with comparison to the benchmark schemes.

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Outage Energy Efficiency Maximization for UAV-Assisted Energy Harvesting Cognitive Radio Networks

Cited by 25 publications

References 45 publications

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

Outage and throughput performance analysis of smart UAV‐assisted full‐duplex NOMA‐based energy harvesting cognitive radio networks

On the performance of uplink NOMA‐based satellite‐aerial‐terrestrial integrated networks

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