D2D Social Selection Relay Algorithm Combined with Auction Principle.

Area of Science:

• Wireless communication
• Network engineering
• Signal processing

Background:

• Device-to-device (D2D) communication offers enhanced spectral efficiency and reduced latency compared to traditional cellular networks.
• Efficient relay selection is crucial for optimizing D2D network performance.
• Existing relay selection methods often incur high detection costs and may not fully leverage user cooperation.

Purpose of the Study:

• To propose a novel relay selection strategy for D2D communication systems leveraging social perception.
• To reduce the computational and communication overhead associated with relay node discovery and selection.
• To enhance overall system performance, including throughput and reliability.

Main Methods:

• Introduction of a social threshold to filter and screen potential relay users within the D2D network.
• Implementation of an auction algorithm to incentivize relay users to increase their transmission power.
• Performance evaluation through simulations to analyze system throughput and outage probability.

Main Results:

• The proposed social perception-based relay selection strategy effectively reduces detection costs.
• The auction algorithm successfully motivates relay users, leading to increased transmission power.
• Simulation results demonstrate significant improvements in system throughput.
• A notable reduction in the probability of system outage was observed.

Conclusions:

• Social perception offers a viable approach to optimize relay selection in D2D networks.
• The combined use of a social threshold and auction algorithm enhances D2D system efficiency and reliability.
• The proposed strategy presents a promising solution for future D2D communication systems.