Analysis of Joint Relay Selection and Resource Allocation Scheme for Relay-Aided D2D Communication Networks

Tian, Chunsheng; Qian, Zhihong; Wang, Xue; Hu, Liangshuai

doi:10.1109/access.2019.2944403

Cited by 26 publications

(19 citation statements)

References 35 publications

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“…Therefore, this section and Table 9 define miscellaneous techniques for efficacious channel allocation that includes stochastic geometry, greedy, and dynamic approaches. Greedy‐based joint mode selection and channel allocation (GMCA) 115 : In this scheme, Tian et al 115 aimed to enhance the transmission rate and QoS of the D2D‐R network. A combined method of relay selection and resource allocation has been studied for the D2D‐R network.…”

Section: Existing Resource Allocation Techniques In D2d Systemmentioning

confidence: 99%

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A survey on energy‐efficient resource allocation schemes in device‐to‐device communication

Jadav

Gupta

Tanwar

2022

Int J Communication

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Summary Device‐to‐device (D2D) communication is an emanating and robust technology for next‐generation wireless networks. It aims to minimize load from the centralized base station (BS) and lets the device communicate directly in the presence or absence of it. Further, to increase the spectral efficiency, it operates in an underlay mode, where D2D devices/users reuse the spectrum of cellular users (CUs), resulting in unusual intercell/intracell interferences. Managing resources efficiently can drastically reduce the effect of interference but on the cost of high energy consumption. The research community is diligently studying the optimal methods for energy‐efficient resource allocation in D2D systems. As per the literature, there exists no comprehensive survey that studied the existing energy‐efficient resource allocation schemes in the D2D environment. Motivated from this, we present a survey on recently adopted solutions for energy‐efficient power, channel, and spectrum allocation in D2D communication, which includes artificial intelligence (AI), optimization, dynamic programming, heuristic approach, game theory, and graph models. In addition, we also highlighted the open research issues and technical challenges while allocating resources to D2D users (DUs).

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Section: Existing Resource Allocation Techniques In D2d Systemmentioning

confidence: 99%

“…(i) Greedy-based joint mode selection and channel allocation (GMCA) 115 : In this scheme, Tian et al 115 aimed to enhance the transmission rate and QoS of the D2D-R network. A combined method of relay selection and resource allocation has been studied for the D2D-R network.…”

Section: Miscellaneous Approachesmentioning

confidence: 99%

A survey on energy‐efficient resource allocation schemes in device‐to‐device communication

Jadav

Gupta

Tanwar

2022

Int J Communication

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“…Though the energy allocation strategy has been used to optimise wireless network performance, as in [29], this paper emphasises the potential of using such a strategy to simultaneously improve the data rate, energy consumption and bit error rate performance in UAV networks. According to the author's knowledge, a UAV network has not been optimised using such a schema previously.…”

Section: Introductionmentioning

confidence: 99%

Balanced Performance Between Energy-Delay and Bit Error Rate in UAV Relay Networks

Khalil¹

2022

Preprint

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This paper presents a new strategy for simultaneously reducing energy consumption, transmission delays, and bit error rate in Unmanned Aerial Vehicle (UAV) networks. A UAV is fitted with a wireless Bidirectional Relay (BR) to enable coverage network extension and increase transmission throughput. The downside of the BR advantages is the delay in data transmission caused by the UAV's movement. A consequence of this delay is increased total energy consumption, causing further degradation in bit error rate performance, especially at high SNR levels. In wireless communication, the trade-off between delay and energy consumption is, fortunately, possible to improve performance. Therefore, this study aims to enhance UAV network performance by reducing energy consumption, data transmission delay, and bit error rate. A multi-objective algorithm is employed to generate an adaptive optimal energy allocation strategy based on the balance between energy consumption and transmission delays. The results of theoretical analysis are illustrated with several examples. As herein demonstrated, the proposed solution effectively balances delay and energy efficiency in a customised system design and improves the bit error rate in UAV networks.

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“…The joint relay selection and power allocation can more effectively maximize the network potential performance and QoS. In Reference [ 11 ], Tian et al proposed a joint relay selection and resource allocation scheme to maximize the total transmission data rates for the D2D network. In this scheme, a social-aware relay selection algorithm was first proposed to select relay.…”

Section: Introductionmentioning

confidence: 99%

Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Han

2020

Sensors

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Cooperative transmission is a promising technology for underwater acoustic sensor networks (UASNs) to ensure the effective collection of underwater information. In this paper, we study the joint relay selection and power allocation problem to maximize the cumulative quality of information transmission in energy harvesting-powered UASNs (EH-UASNs). First, we formulate the process of cooperative transmission with joint strategy optimization as a Markov decision process model. In the proposed model, an effective state expression is presented to better reveal interactive relationship between learning and environment, thereby improving the learning ability. Then, we further propose a novel reward function which can guide nodes to adjust power strategy adaptively to balance instantaneous capacity and long-term quality of service (QoS) under the dynamic unpredictable energy harvesting. More specifically, we propose a deep Q-network-based resource allocation algorithm for EH-UASNs to solve the complex coupled strategy optimization problem without any prior underwater environment information. Finally, simulation results verify the superior performance of the proposed algorithm in improving the cumulative network capacity and reducing outages.

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Analysis of Joint Relay Selection and Resource Allocation Scheme for Relay-Aided D2D Communication Networks

Cited by 26 publications

References 35 publications

A survey on energy‐efficient resource allocation schemes in device‐to‐device communication

A survey on energy‐efficient resource allocation schemes in device‐to‐device communication

Balanced Performance Between Energy-Delay and Bit Error Rate in UAV Relay Networks

Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

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