论文标题
关于在干扰存在下使用MRC使用MRC进行合作NOMA的性能
On the Performance of Cooperative NOMA Using MRC at Road Intersections in the Presence of Interference
论文作者
论文摘要
随着交通安全的最大意义,对智能运输系统(ITS),尤其是对车辆通信(VCS)的关注。此外,所有撞车事故中有50%发生在道路交叉口,这使主题成为关键领域。在本文中,我们研究了使用道路交叉口的非正交多访问方案(NOMA)在合作VCS传输方案中实施最大比率组合(MRC)时的改进。我们认为,源在继电器的帮助下向两个目的地传达信息。传输经历了道路上的一组车辆产生的干扰。我们获得了封闭形式的中断概率表达式,并扩展了涉及K目的地节点和多个道路车道的场景的推导。将MRC合作NOMA的性能与标准合作NOMA进行了比较,我们表明,使用NOMA实施MRC对标准合作NOMA有了显着改善。另外,我们比较了使用NOMA与MRC合作正交多访问(OMA)的MRC的性能,并证明Noma显着胜过OMA。我们得出的结论是,即使以实施复杂性为代价,使用MRC和NOMA也总是有益的。最后,我们证明,停电概率大大提高了车辆更接近道路交叉点,并且在这种情况下,将MRC与NOMA一起使用可显着提高性能。为了验证我们的分析的正确性,进行了广泛的蒙特卡洛模拟。
As the traffic safety has become of utmost importance, much attention is given to intelligent transportation systems (ITSs), and more particularly to vehicular communications (VCs). Moreover, 50 % of all crashes happen at road intersections, which makes theme a critical areas. In this paper, we investigate the improvement when implementing maximum ratio combining (MRC) in cooperative VCs transmission schemes using non-orthogonal multiple access scheme (NOMA) at road intersections. We consider that a source transmits a message to two destinations with a aid of a relay. The transmission undergoes interference generated from a set of vehicles on the roads. We obtained closed form outage probability expressions, and we extend the derivation for a scenario involving K destination nodes and several road lanes. The performance of MRC cooperative NOMA is compared with the standard cooperative NOMA, and we show that implementing MRC with NOMA offers a significant improvement over the standard cooperative NOMA. Also, we compare the performance of MRC using NOMA with MRC cooperative orthogonal multiple access (OMA), and demonstrate that NOMA significantly outperforms OMA. We conclude that it is always beneficial to use MRC and NOMA even at the cost of implementation complexity. Finally, we demonstrate that the outage probability increases drasticallyen the vehicles are closer to the road intersection, and that using MRC with NOMA improves significantly the performance in this context. To verify the correctness of our analysis, extensive Monte-Carlo simulations are carried out.