UAVs Assisted Delay Optimization in Heterogeneous Wireless Networks

Sharma, Vishal; Sabatini, Roberto; Ramasamy, Subramanian

doi:10.1109/lcomm.2016.2609900

Cited by 89 publications

(58 citation statements)

References 9 publications

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“…This is not realistic, as the 228 UAV has to fly up and down consuming more energy. To avoid 229 this, one must average (7), (11), (12), (14) and (15) over the 230 time t. Our study shows that the time-averaged performance 231 of the mobile UAV is almost the same as the static UAV when 232 r U is less than 1000 meters. Thus, in the following, we only 233 present results for the static UAV, unless otherwise specified.…”

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confidence: 87%

“…References [8]- [11] further explored the use of multiple 24 UAVs to cover a certain area. All these works have provided 25 very useful insights on the placement of UAV as an aerial 26 base station.…”

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confidence: 99%

“…Compared with [5]- [11], this work considers both hops 54 from the ground user to UAV and from UAV to the remote 55 station in the placement optimization, while [5]- [11] only con-56 sidered the hop from the ground user to UAV. Also, compared 57 with [12]- [14], this work uses realistic UAV channel models 58 and fixes the UAV on top of the ground user to minimize the 59 power loss for the ground user, while [12]-[14] used standard 60 wireless channel models and the UAV was placed between 61 the ground user and the remote station.…”

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confidence: 99%

“…235 In the legend, (5000,1000,10) means d = 5000 m, r A = 236 1000 m and h B = 10 m for total power loss, and (5000,1000) 237 means d = 5000 m and r A = 1000 for P L A etc. One 238 sees that the optimum h that minimizes the total power loss 239 is considerably different from that minimizes P L A only, as 240 in [5]- [11]. For example, the optimum h is around 400 meters 241 for P L A in (5000,1000), while it is around 2000 meters for 242 the total power.…”

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confidence: 99%

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Optimum Placement of UAV as Relays

2018

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Optimum Placement of UAV as Relays

2018

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“…Moreover, Mozaffari et al 23 find the optimal coverage range and hovering altitude of ABSs to minimize the transmit power of them. Sharma et al 24 find the optimal placement and optimal distribution of ABSs to minimize the overall network delays. In the work of Merwaday et al, 25 the locations of ABSs are optimized in order to maximize the network throughput over a given geographical area.…”

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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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Performance analysis of an efficient linear constellation precoded generalized frequency division multiplexing with index modulation in 5G heterogeneous wireless network

Kumar

Prasad

2021

Int J Communication

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Nowadays, wireless accesses are demanded with new applications, but they generate many technical issues. Moreover, the issues related to the beyond fifth generation (5G) wireless networks can be tackled using an orthogonal frequency division multiplexing (OFDM) schemes. Due to the huge growth of wireless users, this scheme exists with some technical challenges. An enhanced radio access technology is required to tackle the technical constraints of upcoming 5G wireless network applications. Nowadays, the generalized frequency division multiplexing (GFDM) scheme is exploited by wireless networks because of their benefits like spectral efficiency, low latency, and out-of-band (OOB) emission. In this paper, a linear constellation precoded GFDM with interleaved quadrature index modulation (LCP-GFDM-IQIM) scheme is proposed to harvest extra diversity gain by spreading the information symbols in-phase/quadrature component. Also, in-phase/quadrature (I and Q) dimensions are explored in index modulation (IM). Both theoretical and simulation analysis shows that the proposed LCP-GFDM-IQIM scheme achieves better spectral efficiency and energy efficiency as compared to the existing methods.

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UAVs Assisted Delay Optimization in Heterogeneous Wireless Networks

Cited by 89 publications

References 9 publications

Optimum Placement of UAV as Relays

Optimum Placement of UAV as Relays

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

Performance analysis of an efficient linear constellation precoded generalized frequency division multiplexing with index modulation in 5G heterogeneous wireless network

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