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Adaptive resource allocation in FSO/RF multiuser system with proportional fairness for UAV application

机译:FSO / RF多用户系统中的自适应资源分配,用于UAV应用的比例公平

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The combination of free space optic (FSO) and unmanned aerial vehicle (UAV) can be a promising solution to last mile problem because of FSO high bandwidth and flexibility of UAV. However, FSO is vulnerable to the atmospheric turbulence and transmitter configuration is limited on UAV. Therefore, in this paper, we investigate an adaptive resource allocation strategy to provide relative fair and high transmission capacity for users. In the proposed network model, the downlink scenario is considered and ground station communicates with UAV and its local users by FSO and RF links, respectively. According to the channel conditions and rate requirements from users, channel and power assignments should satisfy the capacity demand in reasonable. To this end, we decompose the original channel and power allocation problem with high computational complexity into low complexity subproblems, corresponding to channel allocation in RF transmission phase and channel matching and power allocation in FSO transmission phase. Then, a heuristic efficient resource assignment algorithm is proposed to achieve the optimal capacity distribution for users. Numerical results show that the proposed method can asymptotically achieve optimal throughput. Furthermore, system throughput is higher at low transmitting power requirement than those of other existing methods.
机译:由于FSO高带宽和无人机的灵活性,自由空间光学(FSO)和无人机航空车(UAV)的组合可以是最后一英里问题的有希望的解决方案。然而,FSO容易受到大气湍流和发射器配置限制在UAV上。因此,在本文中,我们调查了自适应资源分配策略,为用户提供了相对公平和高传输能力。在所提出的网络模型中,考虑下行方案,地面站分别与USO和RF链路与UV及其本地用户通信。根据用户的渠道条件和速率要求,通道和功率分配应满足合理的能力需求。为此,我们将具有高计算复杂性的原始信道和功率分配问题分解为低复杂性子问题,对应于RF传输阶段中的信道分配和在FSO传输阶段中的信道匹配和功率分配。然后,提出了一种启发式高效的资源分配算法来实现用户的最佳容量分配。数值结果表明,该方法可以渐近地实现最佳吞吐量。此外,系统吞吐量在低发射功率要求时比其他现有方法更高。

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