Performance Analysis of Device Discovery Algorithms for D2D Communication

The device-to-device (D2D) communication is a candidate technology to implement 5G standards commercially. To initiate D2D, device discovery is a primary issue and very few algorithms have been proposed for device discovery. A discovery algorithm has many parameters to discover the accurate position of the devices in walking and velocity scenarios. Due to rapid changes in the environment, LOS and NLOS algorithms become complex and accurate discovery ventures. Therefore, it is needed to evaluate the performance of the discovery algorithms. In this paper, a methodological approach is introduced for the performance evaluation of discovery algorithms. The performance evaluation for discovery estimation errors and complexity is evaluated using metrics and parameters, and analysis is made for range-based RSS technique using performance metrics. Discussion of performance evaluation metrics and criteria is analyzed followed by numerical/experimental, simulation models, and the parameters which affect performance and assessment. The metrics and criteria are defined in terms of a discovery signal success ratio, average residual energy, accuracy, and root-mean-square error (RMSE). Two differentiating discovery studies, Hamming and Cosine, are given and contrasted with reference RMSE for evaluation. This paper concludes with a discovery algorithm improvement cycle overview from simulation to implementation. It decreases discovery error and enhances RMSE accuracy by an average of 21%. It also reduces the complexity of 12 pairs by Euclidean distance by 29%.