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A hybrid MAC for non-orthogonal multiple access Unmanned Aerial Vehicles networks

机译:非正交多次访问无人航空车辆网络的混合MAC

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摘要

This paper considers a swarm of Unmanned Aerial Vehicles (UAVs) managed by a ground station. These UAVs may experience highly varying channel gains and collisions when they transmit to the ground station. To this end, we introduce a novel Learning Medium Access Control (L-MAC) for multi-rate UAVs and equip the ground station with Successive Interference Cancellation (SIC) capability. The ground station uses L-MAC to learn a Time Division Multiple Access (TDMA) schedule/frame length that yields the highest throughput. UAVs, on the other hand, use L-MAC to learn the best transmission slot and data rate for a given frame length. Our extensive simulation results show that L-MAC achieves up to five times higher throughput as compared to the well-known Aloha protocol. Specifically, L-MAC achieves a throughput of 500 kbps as compared to 100 kbps for Aloha. In comparison, Aloha with SIC achieves a throughput of 300 kbps for the same network scenario. On the other hand, the throughput of L-MAC is as most half that of the case when the ground station has perfect channel state information. Our results also show that the frame length is always set to around 60-75% of the total number of UAVs.
机译:本文考虑了由地面站管理的无人驾驶飞行器(无人机)。当它们传输到地面站时,这些无人机可能会经历高度变化的渠道增益和碰撞。为此,我们为多速率无人机提供了一种新的学习介质访问控制(L-MAC),并配备了连续干扰消除(SIC)能力的地面站。地面站使用L-MAC学习时间划分多址(TDMA)计划/帧长度,从而产生最高吞吐量。另一方面,无人机使用L-MAC学习给定帧长度的最佳传输插槽和数据速率。我们广泛的仿真结果表明,与众所周知的Aloha方案相比,L-MAC达到吞吐量越高,吞吐量高达五倍。具体而言,L-MAM达到500kbps的产量,而Aloha的100kbps相比。相比之下,对于同一网络场景,Aloha达到了300 kbps的吞吐量。另一方面,L-MAC的吞吐量是当地站具有完美频道状态信息时的大多数情况。我们的结果还表明,帧长始终设置为UAV总数的约60-75%。

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