D2D Multi-hop Multi-path Communications in B5G Networks: A Survey on Models, Techniques, and Applications

Tran, Quang-Nhat; Vo, Nguyen-Son; Nguyen, Quynh-Anh; Bui, Minh-Phung; Phan, Thanh-Minh; Lam, Van-Viet; Masaracchia, Antonino

doi:10.4108/eai.7-1-2021.167839

Cited by 18 publications

(10 citation statements)

References 82 publications

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“…As shown in Fig. 7, it can be observed that the transmission models of UAVs are established in the same manner with D2D transmission models [115], [116], but more disruptive interference mitigation techniques.…”

Section: ) Uav Channel and Transmissionmentioning

confidence: 95%

“…Recently, UAV-enabled radio access has been also considered as a key mechanism that can expand the coverage and the number of EUs in 6G networks [66]. In this context, the UAVs can Relay networks [59], [63], [77]- [79], [87], [94], [95] Data collection and content delivery [19], [24], [30], [39], [55], [67], [71], [72], [81], [85], [93], [96], [120] Mobile edge computing [25]- [27], [56]- [58], [71], [84], [89], [101] Natural disasters and emergency communications [114], [114], [116], [121], [121], [122], [122] Safety public and management [29], [123], [124] Civil and military [11], [19], [23], [39], [118], [120], [125]-…”

Section: Uav Caching-enabled Mechanismsmentioning

confidence: 99%

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UAV caching in 6G networks: A Survey on models, techniques, and applications

Duong

Kim

Kaleem

et al. 2022

Physical Communication

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Section: ) Uav Channel and Transmissionmentioning

confidence: 95%

Section: Uav Caching-enabled Mechanismsmentioning

confidence: 99%

UAV caching in 6G networks: A Survey on models, techniques, and applications

Duong

Kim

Kaleem

et al. 2022

Physical Communication

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“…To meet the benefits of all the ISPs, CPs, mobile cellular network carriers, and MUs, on the one hand, it is necessary to propose new network architecture modifications and upgrades. On the other hand, B5G/6G networks have placed a higher priority on soft and intelligent solutions without any architecture changes for low cost deployment [7]. This in turn stimulates the need for designing a proper resource-efficient solution, i.e., a better spectrum, energy, and storage management for VASs in B5G/6G networks.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sharing and Power Allocation Optimised Multihop Multipath D2D Video Delivery in Beyond 5G Networks

Tran

Bui

et al. 2022

IEEE Trans. Cogn. Commun. Netw.

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In this paper, we propose a joint spectrum and power optimisation (SPO) for multi-hop multi-path (MHMP) device-to-device (D2D) video delivery in beyond 5G (B5G/6G) networks, where the system resources such as spectrum, energy, storage, and content of mobile users (MUs), are taken into account. Particularly, the downlink spectrum resources of the sharing users (SUs) are reused by the transmitters (TXs) of D2D hops and the energy resources of the TXs are utilised for D2D communications. We further exploit the videos stored in the caching users (CUs) located more than one D2D hop far away from the requesting users (RUs) to establish MHMP D2D video delivery sessions from the CUs to the RUs. Then, the SPO problem is formulated for the optimal spectrum sharing pairs of SUs and TXs and the optimal transmission powers allocated to the TXs. Genetic algorithms (GAs) are developed to solve the SPO problem with respect to both binary variable (spectrum sharing) and real variable (power allocation). The SPO solution allows the RUs to alternately request the videos not only from the macro base station over conventional cellular networks but also from the CUs over MHMP D2D communications at the highest quality of service, i.e., maximum video delivery capacity and low power consumption. Simulation results are analysed to demonstrate the feasibility of GAs and the benefits of the proposed SPO solution in comparison with other conventional schemes.

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“…Also, the authors have investigated priority communication in cognitive IoT network. Tran et al 35 have discussed D2D multi‐hop multi‐path communications in beyond 5G networks. The cognitive D2D communication is studied in terms of block error rate and system goodput in the finite blocklength regimen 36…”

Section: Introductionmentioning

confidence: 99%

Performance of a cognitive device‐to‐device network in disaster situation under a collision constraint

Ghosh

Bhowmick

Chandra

et al. 2022

Int J Communication

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Summary In this paper, a multi‐hop cognitive radio (CR) enabled device‐to‐device (D2D) network is considered to extend the communication from a functional area (FA) to a non‐functional area (NFA). A D2D user utilizes a cellular user (CU) band in the cognitive mode for information transmission while maintaining the service quality of CUs by satisfying a collision constraint. It transmits with full power in overlay mode, while the power is controlled in underlay mode. We derive the outage probability of the considered D2D network. The main challenge in CR communications lies in the system robustness to uncertainties. In this paper, we also show the impact of the noise power uncertainty in a multi‐hop D2D network. The expressions for throughput and energy efficiency are also developed under collision constraint and noise uncertainty. The outage probability, throughput, and energy efficiency are investigated for several network parameters such as collision probability, sensing time, noise uncertainty, etc. It is observed that the collision constraint and noise uncertainty have significant impacts on network performance. A simulation test‐bed is developed in MATLAB, and the results obtained in the simulation are verified with the analytical results.

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D2D Multi-hop Multi-path Communications in B5G Networks: A Survey on Models, Techniques, and Applications

Cited by 18 publications

References 82 publications

UAV caching in 6G networks: A Survey on models, techniques, and applications

UAV caching in 6G networks: A Survey on models, techniques, and applications

Spectrum Sharing and Power Allocation Optimised Multihop Multipath D2D Video Delivery in Beyond 5G Networks

Performance of a cognitive device‐to‐device network in disaster situation under a collision constraint

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