Throughput maximization in poisson aerial base station–based networks with coverage probability and power density constraints

Saeedi, A H; Azizi, Arman; Mokari, Nader

doi:10.1002/ett.3456

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…Rupasinghe et al 38 find the efficient location of a single ABS to maximize the throughput. Saeedi et al 39 find efficient transmit power and density of ABSs to maximize the network throughput considering coverage probability and power density constraints. A joint subcarrier and power allocation scheme is proposed in the work of Guan et al 40 for orthogonal frequency division multiple access (OFDMA)-based ABS-assisted network.…”

Section: Related Workmentioning

confidence: 99%

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Azizi

Mokari

2019

Trans Emerging Tel Tech

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In this paper, a novel method for joint resource allocation, three-dimensional placement, and user association as a predominant problem in the internet of things (IoTs) networks is proposed. We consider two kinds of channel models for the links between users and aerial base stations (ABSs), namely (a) line of sight (LoS) model and (b) generalized model. In the LoS case, all the ABSs should establish LoS communications path toward IoT users. In the generalized case, the ABSs channels toward the IoT users could be LoS or nonline of sight. We propose four different scenarios, namely interference-free (IF)-LoS, IF-Generalized, interference-included (II)-LoS, and II-Generalized. The IF-LoS and IF-Generalized cases consider subcarrier and modulation order as the resources while the II-LoS and II-Generalized cases consider transmit power, subcarrier, and modulation order as the resources. Our objective function is minimizing the overall transmit power of the IoT users while satisfying some quality of service constraints in the uplink. To solve the resulting nonconvex optimization problem, we convert the main problem with high complexity into the subproblems with low complexities. We compare the performance of our joint proposed scenario with other joint and disjoint cases for the IF-LoS, IF-Generalized, II-LoS, and II-Generalized cases. Moreover, we evaluate the performance of the proposed schemes for different numbers of ABSs, environment types, target areas, and numbers of IoT users.Trans Emerging Tel Tech. 2019;30:e3632.wileyonlinelibrary.com/journal/ett

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Section: Related Workmentioning

confidence: 99%

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Azizi

Mokari

2019

Trans Emerging Tel Tech

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“…In Reference 16, the authors minimize mean packet transmission delay in multilayer ABS‐assisted network by considering resource allocation optimization mechanism. In Reference 17, the authors find efficient values of the transmit power and density of ABSs to maximize the network throughput considering coverage probability and power density constraints thanks to the stochastic process 18,19 …”

Section: Introductionmentioning

confidence: 99%

Multiple input single output aerial base station‐assisted networks: Joint 3D beam‐forming, aerial base station assignment, 3D placement, and radio resource allocation

Azizi

Mokari

2020

Trans Emerging Tel Tech

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In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We aim to maximize the instantaneous data rate subject to some practical constraints. In light of the fact that our optimization problem is mixed‐integer nonlinear programming (MINLP) with high computational complexity, we propose a low complex and practical approach. Therefore, we resort to an alternate method by which the main optimization problem decomposes into three subproblems. Then we solve the resulting subproblems via linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. In order to shed light on our proposed approach, we decompose the proposed scenario into some cases with fewer optimization variables and compare them with our main problem. Our proposed approach boosts the instantaneous data rate compared to the decomposed cases with fewer optimization variables. Via simulation, we study the effect of various parameters like numbers of users, ABSs, and maximum transmission powers on the network performance. Finally, we analyze the network performance for suburban and urban environments considering various number of ABSs.

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Maximum Channel Access Probability Based on Post-Disaster Ground Terminal Distribution Density

Guo

et al. 2020

Computational Data and Social Networks

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Throughput maximization in poisson aerial base station–based networks with coverage probability and power density constraints

Cited by 3 publications

References 28 publications

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Multiple input single output aerial base station‐assisted networks: Joint 3D beam‐forming, aerial base station assignment, 3D placement, and radio resource allocation

Maximum Channel Access Probability Based on Post-Disaster Ground Terminal Distribution Density

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