[论文解读] Multi-Beam UAV Communication in Cellular Uplink: Cooperative Interference Cancellation and Sum-Rate Maximization

Liang Liu, Shuowen Zhang+1 more|arXiv (Cornell University)|Aug 1, 2018

UAV Applications and Optimization参考文献 20被引用 45

一句话总结

这篇论文提出了一种在蜂窝网络中多波束无人机上行的协同干扰消除策略，在干扰约束下最大化无人机总速率并保护被占用的基站，同时分析高信噪比下的自由度DoF。

ABSTRACT

Integrating unmanned aerial vehicles (UAVs) into the cellular network as new aerial users is a promising solution to meet their ever-increasing communication demands in a plethora of applications. Due to the high UAV altitude, the channels between UAVs and the ground base stations (GBSs) are dominated by the strong line-of-sight (LoS) links, thus severe interference may be generated to/from the GBSs in the uplink/downlink, which renders the interference management with coexisting terrestrial and aerial users a more challenging problem to solve. In this paper, we study the uplink communication from a multi-antenna UAV to a set of GBSs in its signal coverage region. Among these GBSs, we denote available GBSs as the ones that do not serve any terrestrial users at the assigned resource block (RB) of the UAV, and occupied GBSs as the rest that are serving their respectively associated terrestrial users in the same RB. We propose a new cooperative interference cancellation strategy for the multi-beam UAV uplink communication, which aims to eliminate the co-channel interference at each of the occupied GBSs and in the meanwhile maximize the sum-rate to the available GBSs. Specifically, the multi-antenna UAV sends multiple data streams to selected available GBSs, which in turn forward their decoded data streams to their backhaul-connected occupied GBSs for interference cancellation. To draw useful insights, the maximum degrees-of-freedom (DoF) achievable by the multi-beam UAV communication for sum-rate maximization in the high signal-to-noise ratio (SNR) regime is first characterized, subject to the stringent constraint that all the occupied GBSs do not suffer from any interference in the UAV's uplink transmission. Then, based on the DoF-optimal design, the achievable sum-rate at finite SNR is maximized, subject to given maximum allowable interference power constraints at each occupied GBS.

研究动机与目标

• 为了满足无人机载荷和控制信号对高数据速率的需求，动机化蜂窝型无人机上行。
• 开发一种利用相邻GBS之间的回传连接的协同干扰消除策略。
• 在干扰约束下表征无人机上行的最大自由度（DoF）。
• 使用DoF引导的波束设计，在有限SNR下最大化无人机总速率。
• 将性能与认知波束成形、NOMA和CoMP等基准进行对比。

提出的方法

• 对具有M个天线的无人机进行建模，向N个GBS发送信号，将GBS分为占用组和可用组。
• 提出协同干扰消除，其中可用GBS解码无人机流并将其转发给连接的占用GBS以实现干扰消除。
• 在干扰温度约束下建立总速率最大化问题，联合设计数据流J、关联Λj、波束成形向量wj和速率Rj。
• 在高SNR下通过零强制约束进行DoF分析，以在回传辅助的消除条件下最大化可行的J。
• 通过后续凸逼近在有限SNR下开发波束成形算法，并以DoF最优的关联为指导。
• 提供数值结果，与认知波束成形、NOMA和CoMP基准进行对比。

实验结果

研究问题

• RQ1 如何在通过协同干扰消除保护驻扎基站上行的同时最大化无人机上行总速率？
• RQ2 在干扰约束和回传辅助消除下，多波束无人机上行可达到的最大DoF是多少？
• RQ3 数据流应如何与可用GBS关联以实现回传基础的干扰消除？
• RQ4 在干扰温度约束下，哪种有限SNR波束成形策略能实现接近最优的总速率？

主要发现

• 协同干扰消除策略使在干扰约束下能传输的数据信号流数量超过认知波束成形或NOMA。
• DoF分析表明，在占用GBS实现零干扰的前提下，所提策略的DoF高于基准。
• 一个DoF最优的数据流关联引导在后续凸逼近的有限SNR波束成形设计。
• 有限SNR波束成形算法在仿真中相比认知波束成形取得显著的总速率提升。
• 数值结果验证了DoF洞见，并展示了相对于基准方案的性能提升。