Power and delay optimization based uplink resource allocation for wireless networks with device-to-device communications

Ferreira, Marcus V. G.; Vieira, Flávio Henrique Teles; Cardoso, Álisson Assis

doi:10.1016/j.comcom.2022.07.040

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…In this subsection, we briefly describe the approach presented in [28] for resource allocation in multi-sharing uplink scenarios of mmWave cyclic prefix-orthogonal frequency division multiplexing (CP-OFDM) wireless networks [29], incorporating device-to-device communications. The power and delay optimization based uplink resource allocation algorithm comprises two distinct steps [28]. Initially, network resources are allocated to cellular user equipment in terms of both power and transmission rate.…”

Section: Power and Delay Optimization Based Uplink Resource Allocatio...mentioning

confidence: 99%

Optimal Power Allocation and Delay Minimization Based on Conflict Graph Algorithm for Device-to-Device Communications

de Melo,

Ferreira,

Vieira

2023

Applied Sciences

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Device-to-device (D2D) technology is a promising technique in terms of being capable of providing efficiency, decreased latency, improved data rate, and increased capacity to cellular networks. Allocating power to users in order to reduce energy consumption and maintain quality of service (QoS) remains a major challenge in D2D communications. In this paper, we aim to maximize the throughput of D2D users and cellular users subject to QoS requirements and signal-to-interference-plus-noise ratio (SINR). To this end, we propose a resource and power allocation approach called optimal power allocation and delay minimization based on the conflict graph (OP-DMCG) algorithm that considers optimal power allocation for D2D multi-users in the cellular uplink channels and minimization of the total network delay using conflict graphs. Based on the simulations presented in this paper, we show that the proposed OP-DMCG algorithm outperforms the greedy throughput maximization plus (GTM+), delay minimization conflict graph (DMCG), and power and delay optimization based uplink resource allocation (PDO-URA) algorithms in terms of both total network throughput and total D2D throughput.

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Section: Power and Delay Optimization Based Uplink Resource Allocatio...mentioning

confidence: 99%

Optimal Power Allocation and Delay Minimization Based on Conflict Graph Algorithm for Device-to-Device Communications

de Melo,

Ferreira,

Vieira

2023

Applied Sciences

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Joint Power and Delay Optimization‐Based Resource Allocation in Mu‐MIMO‐OFDM System: Deep Convolutional Red Piranha Pyramid‐Dilated Neural Network

Vijaipriya,

Nesasudha,

Michael

2024

Trans Emerging Tel Tech

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In general, Multi‐User Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MU‐MIMO‐OFDM) enables multiple users to simultaneously communicate with a single base station using multiple antennas and OFDM modulation. Nevertheless, resource allocation challenges such as power management and delay optimization arise within MU‐MIMO‐OFDM systems, requiring sophisticated solutions to ensure efficient use of resources and optimal system performance. Thus, joint power and delay optimization‐based resource allocation using a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN) with Red piranha optimization and Optimal Delay Scheduling conflict graphs Algorithm (DCPDNN‐RPO‐ODSCGA) in MU‐MIMO‐OFDM system is proposed in this presented research. The proposed mechanism is performed in two stages: power allocation and delay optimization. In the first stage, through a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN), which aims to maximize throughput, the network resources are distributed to user equipment (UEs) based on power and transmission rate. To reduce the loss function, Red Piranha Optimization (RPO) is proposed to optimize the layers of DCPDNN. In the second stage, the Optimal Delay Scheduling conflict graphs Algorithm (ODSCGA) is proposed for the optimizing delay in the MU‐MIMO‐OFDM system. The multiracial envelope procedure and service curve for traffic flows in the uplink transmission are used in the ODSCGA approach to estimate the delay‐bound value. Ideas like the maximal weight independent set and optimal conflict graph are also utilized. The simulations of DCPDNN‐RPO‐ODSCGA were conducted using MATLAB software. Thus, the proposed approach has attained higher spectral capacity, higher fairness index, and increased cumulative distribution function (CDF), 29.74%, 32.98%, and 16.46% lower loss rate, 28.05%, 24.09%, and 17.45% improved energy efficiency, 15.09%, 13.78%, and 12.05% lower processing time than other conventional approaches like MPQM‐SCA, Hyb‐BF‐DSA, and SIA‐FDBD methods, respectively.

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OR2M: a novel optimized resource rendering methodology for wireless networks based on virtual reality (VR) applications

Kiruthika,

Rajasekaran,

Gurumoorthy

et al. 2024

Wireless Netw

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Power and delay optimization based uplink resource allocation for wireless networks with device-to-device communications

Cited by 5 publications

References 13 publications

Optimal Power Allocation and Delay Minimization Based on Conflict Graph Algorithm for Device-to-Device Communications

Optimal Power Allocation and Delay Minimization Based on Conflict Graph Algorithm for Device-to-Device Communications

Joint Power and Delay Optimization‐Based Resource Allocation in Mu‐MIMO‐OFDM System: Deep Convolutional Red Piranha Pyramid‐Dilated Neural Network

OR2M: a novel optimized resource rendering methodology for wireless networks based on virtual reality (VR) applications

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