The new generation telecommunications is growing at a spectacular pace and Device-to-Device (D2D) communication networks plays major role to meet the growing demands by billions of connected devices over the globe. Generally, indoor based D2D communication networks relays on distributed small cell solutions for better connectivity. This research proposes Signal-to-Interference-plus-Noise Ratio (SINR) based – Device Association Vector Algorithm (S-DAVA) for maximum network connectivity by efficiently discovering the neighbors and its D2D link based on network sum rate and SINR. The algorithm uses Rician model for Line-of-Sight (LoS) component to investigate the D2D network performance. The algorithm when evaluated with other conventional methods showed an improvement of 18.85% in throughput, and 10% of efficiency in energy with reduced network delay of 19%. This paper also checks its performance over traffic load, outage probability and network sum rate.

新一代电信正以惊人的速度增长，设备对设备（D2D）通信网络在满足全球数十亿连接设备不断增长的需求方面发挥着重要作用。通常，基于室内的D2D通信网络在分布式小型小区解决方案上进行中继，以实现更好的连接性。这项研究提出了一种基于信号干扰加噪声比（SINR）的设备关联矢量算法（S-DAVA），可以通过基于网络总速率和SINR有效地发现邻居及其D2D链路来实现最大的网络连通性。该算法使用Rician模型作为视线（LoS）组件来研究D2D网络性能。与其他常规方法一起评估时，该算法的吞吐量提高了18.85％，能源效率提高10％，网络延迟降低19％。本文还检查了其在流量负载，中断概率和网络总速率方面的性能。