When Distributed Outperforms Centralized Scheduling in D2D-Enabled Cellular Networks

Ibrahim, Rita; Assaad, Mohamad; Sayraç, Berna; Gati, Azeddine

doi:10.1145/3242102.3242115

Cited by 9 publications

(4 citation statements)

References 32 publications

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“…D2D communication has been widely studied in the RF and mmWave bands [15] [16], and there are multiple challenges associated with using it in the THz band. Due to limited signal coverage, centralized D2D communication is challenging.…”

Section: Dense Deployment In Thzmentioning

confidence: 99%

Ultra-dense low data rate (UDLD) communication in the THz

Singh

Sicker

2020

Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication

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In the future, with the advent of the Internet of Things (IoT), wireless sensors, and multiple 5G applications yet to be developed, an indoor room might be filled with 1000s of devices. These devices will have different Quality of Service (QoS) demands and resource constraints, such as mobility, hardware, and efficiency requirements. The THz band has a massive greenfield spectrum and is envisioned to cater to these dense-indoor deployments. However, THz has multiple caveats, such as high absorption rate, limited coverage range, low transmit power, sensitivity to mobility, and frequent outages, making it challenging to deploy. THz might compel networks to be dependent on additional infrastructure, which might not be profitable for network operators and can even result in inefficient resource utilization for devices demanding low to moderate data rates. Using distributed Device-to-Device (D2D) communication in the THz, we can cater to these ultra-dense low data rate type applications in a constrained resource situation. We propose a 2-Layered distributed D2D model, where devices use coordinated multi-agent reinforcement learning (MARL) to maximize efficiency and user coverage for dense-indoor deployment. We explore the choice of features required to train the algorithms and how it impacts the system efficiency. We show that densification and mobility in a network can be used to further the limited coverage range of THz devices, without the need for extra infrastructure or resources.

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Section: Dense Deployment In Thzmentioning

confidence: 99%

Ultra-dense low data rate (UDLD) communication in the THz

Singh

Sicker

2020

Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication

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“…An iterative distributed power allocation algorithm for the two kinds of game: pure and mixed has investigated. Distributed vs. centralized MS and PC approaches have been suggested in [25] using GT tools.…”

Section: Introductionmentioning

confidence: 99%

Nash Equilibrium Study for Distributed Mode Selection and Power Control in D2D Communications

Najeh¹,

Bouallègue²

2021

Systems-of-Systems Perspectives and Applications - Design, Modeling, Simulation and Analysis (MS&A), Gaming and Decision Su

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One of the main challenges of LTE-advanced (LTE-A) is to recover the localarea services and improve spectrum effciency. In order to reach those goals technical capabilities are required. D2D is a promising techniques for the 5G wireless communications system using several applications, as: network traffic offoading, public safety, social services and applications such as gaming and military applications. In this chapter, we investigate both mode selection and distributed power control in D2D system. Indeed, the mode selection is provided while respecting a predetermined SINR threshold relative to cellular and D2D users. The amount of minimum and maximum power are then derived to fulffill the predetermined requirements, by limiting the interference created by underlaid D2D users. In order to realize our proposed power control step, a new distributed control approach is proposed using game theory tools for several cellular and D2D users. This distributed approach is based on the mode selection strategy already proposed in the previous step. Finally, simulations were established in order to compare the proposed distributed algorithm in terms of coverage probability which is based on game theory, with other conventional centralized algorithms.

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“…Besides, the CSI reporting requires additional resources, while a limited number is available for the network control [13]. It also increases the complexity and generates significant signalling overhead between the eNodeB and the connected devices [26,27].…”

Section: Introductionmentioning

confidence: 99%

Joint uplink and downlink resource allocation for device to device communications

Selmi

Bouallègue²

2021

IET Communications

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With the ever-increasing number of intelligent devices, extensive research efforts have been spent towards developing efficient resource allocation in underlying device to device communications. Centralised and distributed approaches have been proposed to improve the network performances through uplink and downlink schemes. However, the full-duplex resource allocation remains challenging. Here, a joint uplink-downlink resource block assignment for device to device communications is proposed. The device's geometric distribution via the Poisson point process is formulated and the optimization problem as a mixed strategy non-cooperative game is modelled. The proposed resource allocation scheme allows many device to device communication pairs to share the same cellular resource block but does not restrict their number in advance; it is determined dynamically according to the channel's capacity and interference condition. Inversely, a device to device communication transmitter can simultaneously be allocated many resource blocks according to its bandwidth requirement and the number of its antennas. Furthermore, the optimal amount of data and power transmitted by each device is calculated. The efficiency of this algorithm is evaluated through computer simulations, and the results demonstrate good performances in the spectral and energy efficiency with relatively low complexity and convergence time.

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When Distributed Outperforms Centralized Scheduling in D2D-Enabled Cellular Networks

Cited by 9 publications

References 32 publications

Ultra-dense low data rate (UDLD) communication in the THz

Ultra-dense low data rate (UDLD) communication in the THz

Nash Equilibrium Study for Distributed Mode Selection and Power Control in D2D Communications

Joint uplink and downlink resource allocation for device to device communications

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