Joint Resources Allocation of Device-To-Device Communications Underlaying Cellular Networks

Hashad, Omnia; ElHalawany, Basem M.; Fouda, Mostafa M.; Eldien, Adly S. Tag

doi:10.1109/jac-ecc48896.2019.9051283

Cited by 5 publications

(13 citation statements)

References 9 publications

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“…2. Specifically, at an equal number of UEs and the accessed D2D pairs, the proposed power minimization algorithm achieves, approximately, 0.71 times the total power consumption of our proposed EE maximization algorithm and the throughput maximization algorithm in [28], and 0.4 times the total power consumption of the throughput maximization algorithm in [23]. However, its performance is limited by the noise, specifically, in the low SNR regime.…”

Section: Performance Analysis and Numerical Resultsmentioning

confidence: 88%

“…On the other hand, interestingly, the proposed EE maximization algorithm reduces the total power consumption at high SNR more than the proposed power minimization algorithm. Specifically, at an equal number of UEs and the accessed D2D pairs, the proposed EE maximization algorithm achieves, approximately, 0.66 times the total power consumption of our proposed power minimization algorithm, 0.42 times the total power consumption of the energy-efficient D2D algorithm in [24], 0.23 times the total power consumption of the throughput maximization algorithm in [28], and 0.18 times the total power consumption of the throughput maximization algorithm in [23].…”

Section: Performance Analysis and Numerical Resultsmentioning

confidence: 88%

“…The authors in [24] adopt the same model except that they do not assume a fully-loaded cell and they use the extra available RBs to be reused by D2D devices in addition to the used RBs. Further, we compare the performance of our proposed algorithms with the sum throughput maximization algorithms in [28] and in [23], which outperforms the algorithms in [6], [20], [21]. Interestingly, the proposed algorithms have a substantially enhanced performance when the noise power spectral density is decreased, which reflects the design criteria that is based on the high SINR assumption.…”

Section: Performance Analysis and Numerical Resultsmentioning

confidence: 92%

“…We propose a non-linear fractional programming algorithm based on primal-dual update equations for finding the optimal solution. • The simulations results show that the proposed algorithms provide substantial power minimization and EE maximization compared to previous state-of-the-art algorithms in [6], [20], [21], [23], [24], [28].…”

Section: Introductionmentioning

confidence: 94%

“…The channel assignment matrix is ∈ {0, 1} × , and = [ , ], and are the UE and the D2D transmit powers. It is worth noting that in [28], we proposed a primal-dual algorithm to maximize the sum-throughput.…”

Section: Letmentioning

confidence: 99%

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Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

et al. 2020

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Device-to-Device (D2D) communications underlaying cellular networks have emerged as a necessity for a substantial increase in the system throughput and the number of active devices for the future cellular networks. In underlay D2D networks, it is conventional to use different interference management (IM) techniques to allow D2D transmitters to reuse the cellular users' subcarriers. Conventionally, those IM techniques pair a specific number (one or more) of D2D transmitters to each subcarrier and/or allow each D2D transmitter to transmit on a specific number of subcarriers simultaneously in order to achieve the target rates. Due to the mixed-integer nature of those IM techniques, convex optimization techniques can not be used, and usually complex heuristic or game-theoretic approaches are exploited. In this paper, we introduce a reduced-constraints approach to seek sub-optimal joint power allocation and channel assignment solutions for two non-convex, mixed-integer, and non-linear programs (MINLP). Specifically, via the reduced-constraints approach and variable transformation techniques, we can exploit primal-dual algorithms to solve system power minimization and energy-efficiency maximization problems. Extensive numerical simulation results show that the proposed approach outperforms state-of-the-art techniques.

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Section: Performance Analysis and Numerical Resultsmentioning

confidence: 88%

Section: Performance Analysis and Numerical Resultsmentioning

confidence: 88%

Section: Performance Analysis and Numerical Resultsmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 94%

Section: Letmentioning

confidence: 99%

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Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

et al. 2020

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An Optimal Balanced Energy Harvesting Algorithm for Maximizing Two-Way Relaying D2D Communication Data Rate

et al. 2022

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Combining energy harvesting (EH) and device-to-device (D2D) communication underlaying 5G cellular networks is a very promising direction to improve both energy and spectral efficiencies. Unlike conventional relay-aided D2D communication that assumes one-way relaying (OWR) protocols, this paper proposes a two-way relaying (TWR) model. It aims to maximize the TWR D2D link rate that shares the uplink (UL) resources of the conventional cellular user (CU) considering the quality of service (QoS) constraints of all users. Besides, the relays are considered to harvest renewable energy (RE) from the ambient environment by relying on an attached solar panel. Also, they can harvest radio frequency (RF) energy from the received signal based on the power splitting (PS) EH protocol. Assuming that the UL resource allocation (RA) is already performed, the paper's objective is to jointly optimize the transmission power of all users in addition to the PS factor of relays based on the well-known meta-heuristic algorithm particle swarm optimization (PSO). Also, the best relay is selected by relying on the delimited area (DA) mechanism and the balanced residual energy (BRE) leading to TWR D2D link rate maximization and better energy efficiency (EE). The performance of the proposed algorithm is investigated through the results as well as comparing its performance to two of the most recent relay-aided D2D algorithms.INDEX TERMS Device-to-device, two-way relaying, energy harvesting, power splitting, particle swarm optimization, power allocation, decode-and-forward, relay selection.

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RF Energy Harvesting Effectiveness in Relay-based D2D Communication

Salim

El-Sayed

Abdalzaher

et al. 2023

2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)

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Joint Resources Allocation of Device-To-Device Communications Underlaying Cellular Networks

Cited by 5 publications

References 9 publications

Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

An Optimal Balanced Energy Harvesting Algorithm for Maximizing Two-Way Relaying D2D Communication Data Rate

RF Energy Harvesting Effectiveness in Relay-based D2D Communication

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