Device-to-device (D2D) communication has captured the researchers attention working in data-intensive applications. It has various benefits, such as low communication latency, load balancing, high spectral efficiency, and many more. However, despite these benefits, it has significant issues like efficient resource allocation, device discovery, and interference mitigation. Various solutions have given by the researchers to tackle these issues and the research community accepts them well. Here, we are targeting the issues associated with the device discovery, i.e., the base station assisted discovery. The initial step for D2D communication is the device discovery that the base station can perform. But, if the channel indicator parameters of the base station are not good, then the device discovery and further data sharing will be affected. Thus, there is a need for the best base station selection that improves the efficiency of the overall network. Many network selection solutions (for cellular networks) are available in the literature, but none of it talked about in the D2D communication scenario. So, motivated by this, this paper proposes an AI-based intelligent and efficient network selection scheme for D2D users to improve the device discovery experience and overall system’s sum rate. We then evaluate the performance of the proposed scheme using various evaluation metrics, such as accuracy, precision, recall, receiver operating curve (ROC), computation time, and sum rate.

设备到设备 (D2D) 通信已经吸引了研究人员在数据密集型应用程序中工作的注意力。它具有各种优点，例如低通信延迟、负载平衡、高频谱效率等等。然而，尽管有这些好处，但它也存在诸如有效的资源分配、设备发现和干扰缓解等重大问题。研究人员提出了各种解决方案来解决这些问题，研究界也很好地接受了它们。在这里，我们针对与设备发现相关的问题，即基站辅助发现。D2D 通信的初始步骤是基站可以执行的设备发现。但是，如果基站的信道指标参数不好，则会影响设备发现和进一步的数据共享。因此，需要最佳的基站选择，以提高整个网络的效率。文献中提供了许多网络选择解决方案（针对蜂窝网络），但没有一个在 D2D 通信场景中提及。因此，受此启发，本文针对 D2D 用户提出了一种基于 AI 的智能高效网络选择方案，以提高设备发现体验和整体系统的和率。然后，我们使用各种评估指标评估所提出方案的性能，例如准确度、精确度、召回率、接收器操作曲线 (ROC)、计算时间和总和率。但在 D2D 通信场景中都没有谈到。因此，受此启发，本文针对 D2D 用户提出了一种基于 AI 的智能高效网络选择方案，以提高设备发现体验和整体系统的和率。然后，我们使用各种评估指标评估所提出方案的性能，例如准确度、精确度、召回率、接收器操作曲线 (ROC)、计算时间和总和率。但在 D2D 通信场景中都没有谈到。因此，受此启发，本文针对 D2D 用户提出了一种基于 AI 的智能高效网络选择方案，以提高设备发现体验和整体系统的和率。然后，我们使用各种评估指标评估所提出方案的性能，例如准确度、精确度、召回率、接收器操作曲线 (ROC)、计算时间和总和率。