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.

本文考虑了由地面站管理的无人飞行器（UAV）群。这些UAV在传输到地面站时可能会遇到变化很大的信道增益和冲突。为此，我们介绍了一种适用于多速率无人机的新型学习媒体访问控制（L-MAC），并为地面站配备了连续干扰消除（SIC）功能。地面站使用L-MAC来学习时分多址（TDMA）计划/帧长度，以产生最高的吞吐量。另一方面，无人机使用L-MAC来学习给定帧长度的最佳传输时隙和数据速率。我们广泛的仿真结果表明，与众所周知的Aloha协议相比，L-MAC的吞吐量高出五倍。特别，与Aloha的100 kbps相比，L-MAC的吞吐量达到了500 kbps。相比之下，具有SIC的Aloha在相同的网络情况下可实现300 kbps的吞吐量。另一方面，L-MAC的吞吐量是地面站具有完善的信道状态信息时的吞吐量的一半。我们的结果还表明，帧长始终设置为无人机总数的60–75％。