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Trajectory Design and Power Allocation for Drone-Assisted NR-V2X Network With Dynamic NOMA/OMA

机译:具有动态NOMA / OMA的无人机辅助NR-V2X网络的轨迹设计和功率分配

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In this paper, we find trajectory planning and power allocation for a vehicular network in which an unmanned-aerial-vehicle (UAV) is considered as a relay to extend coverage for two disconnected far vehicles. We show that in a two-user network with an amplify-and-forward (AF) relay, non-orthogonal-multiple-access (NOMA) always has better or equal sum-rate in comparison to orthogonal-multiple-access (OMA) at high signal-to-noise-ratio (SNR) regime. However, for the cases where i) base station (BS)-to-relay link is weak, or ii) two users have similar links, or iii) BS-to-relay link is similar to relay-to-weak user link, applying NOMA has negligible sum-rate gain. Hence, due to the complexity of successive-interference-cancellation (SIC) decoding in NOMA, we propose a dynamic NOMA/OMA scheme in which OMA mode is selected for transmission when applying NOMA has only negligible gain. Also, we show that OMA always has better min-rate than NOMA at high SNR regime. Further, we formulate two optimization problems which maximize the sum-rate and min-rate of the two vehicles. These problems are non-convex, and hence we propose an iterative algorithm based on alternating-optimization (AO) method which solves trajectory and power allocation sub-problems by successive-convex-approximation (SCA) and difference-of-convex (DC) methods, respectively. Finally, the above-mentioned performance is confirmed by simulations.
机译:在本文中,我们发现了一种车辆网络的轨迹规划和功率分配,其中无人机车辆(UAV)被认为是延长两个断开的远车辆的覆盖范围的继电器。我们表明,在具有放大和前进(AF)继电器的双用户网络中,与正交 - 多址(OMA)相比,非正交 - 多址(NOMA)始终具有更好或等于的总和速率以高信噪比(SNR)制度。然而,对于I)基站(BS)-To-Relay链路的情况较弱,或ii)两个用户具有类似的链路,或者III)BS-to-中继链路类似于中继到弱用户链接,应用NOMA具有可忽略的总和增益。因此,由于NOMA中的连续干扰消除(SIC)解码的复杂性,我们提出了一种动态的NOMA / OMA方案,其中在应用NOMA时选择用于传输的OMA模式仅具有可忽略的增益。此外,我们表明OMA始终与高SNR制度的NOMA具有比NOMA更好。此外,我们制定了两个优化问题,最大化了两个车辆的总和和最小值。这些问题是非凸的,因此我们提出了一种基于交替优化(AO)方法的迭代算法,该方法通过连续凸 - 近似(SCA)和凸(DC)来解决轨迹和功率分配子问题。方法分别。最后,通过模拟确认上述性能。

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