Distance-Aware Relay Selection in an Energy-Efficient Discovery Protocol for 5G D2D Communication

Anamuro, Cesar Vargas; Varsier, Nadège; Schwoerer, Jean; Lagrange, Xavier

doi:10.1109/twc.2021.3058636

Cited by 27 publications

(5 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the analysis of throughput and AoI performance metrics using this method in an IoT network was presented [32], where the throughput was characterized when the IoT devices were in D2D mode and the latter was considered in cellular fashion. In [33], a distributed relay selection scheme was proposed to reduce the total energy consumption for massive machine-type communications (mMTC) devices, which was to use a contention process based on a truncated geometric distribution.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Distance-Based D2D Matching Mechanism

Liu

Wang

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

The traditional cellular architecture where devices connect to their service base station (BS) may cause poor performance especially for edge users. Device-to-device (D2D) communication enables nearby user as a relay to help BS forward information, thereby improving the network coverage and quality of service (QoS) of edge users. This paper proposes a distance-based D2D matching mechanism for general cellular networks, where a relay user who successfully connects to its targeted BS can transmit data to its closest user for D2D communication. A link of BS to D2D pair contains two sublinks, which occur at different time phases in each cell. Assuming a nonsynchronous system, we consider that there exists cross-layer interference for D2D links. Based on the techniques of stochastic geometry, we develop the performance of coverage probability and ergodic rate of the D2D network. A key intermediate step in this analysis is the derivation of the interference expressions for D2D links caused by BSs and cochannel D2D users. Then, we derive the meta distribution of the signal-to-interference ratio (SIR) to capture the performance changes of individual links. Simulation results demonstrate that our matching mechanism based on the appropriate time resource allocation favors the edge users with a higher probability of successful communication and transmission rate.

show abstract

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Distance-Based D2D Matching Mechanism

Liu

Wang

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…With the increase research on 5G features, authors in [8] examined relay discovery and selection for 5G D2D communications and proposed a distributed energy-efficient D2D relaying mechanism.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of timers related to ProSe-based UE-to-network relays

Mosbah¹,

Gamboa²,

Rouil³

2021

View full text Add to dashboard Cite

User Equipment (UE)-to-Network Relay functionality was introduced in Release 13 of the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) to extend and improve user connectivity. In this architecture, a UE connected to the network (relay UE) provides network access to another UE (remote UE) by establishing a direct one-toone connection with it using the sidelink (SL) channels over the PC5 interface. The PC5 signalling is used for the establishment and maintenance of this direct connection, and different procedures and timers are linked to these processes. In this paper, we focus on describing and evaluating the PC5 signalling protocol performance through system-level simulations to provide some insights on minimum timer values that may increase the probability of successfully establishing and maintaining the connection between a remote UE and a relay UE.

show abstract

“…Various studies have been conducted on relay selection for D2D communication. These include a relaying mechanism that enhances energy efficiency [15], channel status feedback for dynamic channels to improve relay selection [16], a relay selection scheme that considers data rate, battery time, and transmission delay on the D2D link [17], and a method that considers the signal and battery power to identify the most suitable relay [18]. Furthermore, various optimization algorithms have been proposed for relay selection in D2D communication.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Relay Selection in D2DCommunication for Next-Generation WirelessNetworks Using Multi-Agent ReinforcementLearning: A Novel Approach

SIRMA,

KAVAK,

INNER

2024

Preprint

View full text Add to dashboard Cite

Device-to-device (D2D) communication offering a direct communication channel between devices has been introduced as an alternative communication technique for next generation wireless networks, which aims to alleviate the workload traditionally shouldered by base stations (BS) in cellular systems. However, D2D pairs encountering connectivity issues or requiring extended communication ranges will necessitate the involvement of a relay node (RN) to facilitate communication. For the cases wherein an efficient communication with the target device is only possible over a relay device, finding the candidate relay among source-relay-destination devices with the best link availability and optimized end-to-end throughput are challenges to be considered in relay assisted D2D communication. Despite the plethora of studies on relay selection in D2D communication, there persists a need for a method that systematically integrates multiple disruptive factors inherent in wireless channels. While Reinforcement Learning (RL) has primarily found application in resource management tasks like power control, resource block (RB) availability, and spectrum allocation, its utilization for relay selection in D2D communication within dynamic wireless environments remains largely unexplored. In this paper, we propose to use multi-agent reinforcement learning based relay selection (MARS) in which the source device and/or pairing devices act as learning agents. The resource selection agent (RSA), the link agent (LA), and the transmission agent (TA) are involved cooperatively in the MARS method to find the optimum relay. Source nodes in D2D pairs iteratively update their strategies through interactions with the wireless environment and other devices in order to maximize its cost function to select the most convenient relay in the multi hop D2D communication scenario. The MARS method takes into account the combined effect of SINR, link reliability, and throughput values for the estimation of cost function order to select the optimum relay node. We have performed extensive simulations for different device density scenarios in wireless environment and compared the performance of our MARS method with SINR based relay selection approach. The findings show that our relay selection approach for D2D communication outperforms SINR-based methods in terms of end-to-end link reliability and throughput performance.

show abstract

Distance-Aware Relay Selection in an Energy-Efficient Discovery Protocol for 5G D2D Communication

Cited by 27 publications

References 33 publications

Performance Analysis of Distance-Based D2D Matching Mechanism

Performance Analysis of Distance-Based D2D Matching Mechanism

Evaluation of timers related to ProSe-based UE-to-network relays

Optimizing Relay Selection in D2DCommunication for Next-Generation WirelessNetworks Using Multi-Agent ReinforcementLearning: A Novel Approach

Contact Info

Product

Resources

About