Over-the-air computation (AirComp) has been recognized as a low-latency solution for wireless sensor data fusion, where multiple sensors send their measurement signals to a receiver simultaneously for computation. Most existing work only considered performing AirComp over a single frequency channel. However, for a sensor network with a massive number of nodes, a single frequency channel may not be sufficient to accommodate the large number of sensors, and the AirComp performance will be very limited. So it is highly desirable to have more frequency channels for large-scale AirComp systems to benefit from multi-channel diversity. In this letter, we propose an $M$-frequency AirComp system, where each sensor selects a subset of the $M$ frequencies and broadcasts its signal over these channels under a certain power constraint. We derive the optimal sensors' transmission and receiver's signal processing methods separately, and develop an algorithm for joint design to achieve the best AirComp performance. Numerical results show that increasing one frequency channel can improve the AirComp performance by threefold compared to the single-frequency case.
翻译:高空计算(AirComp)被公认为是无线传感器数据聚合的低纬度解决方案,其中多个传感器将其测量信号同时传送给接收器进行计算。大多数现有工作只考虑在一个单一频率频道上进行空Comp。然而,对于一个拥有大量节点的传感器网络,单频信道可能不足以容纳大量传感器,而空Comp性能将非常有限。因此,非常可取的做法是为大型空Comp系统建立更多的频率频道,以便从多频道多样性中受益。在本信中,我们提议建立一个$M$-频率空Comp系统,每个传感器选择一个小节点的美元频率,并在一定的电力限制下在这些频道上播放信号。我们分别计算最佳传感器的传输和接收信号处理方法,并开发联合设计的算法,以实现最佳空Comp性能。数字结果显示,增加一个频率频道可以比单一频率案例提高三倍的空气Comp性能。