Performance Enhancement of UAV-Assisted Wireless Communication Using the MVC Channel Estimation Algorithm in a Diamond-Shaped Network Topology

Snehasish Basu, Sagnik Banerjee, R. Arya, Sarita Nanda, Samarpit Mohanty, S. Patnaik
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Abstract

Amalgamation of coding and spatial diversity have led to new aspects in the field of wireless communications, with a focus on Unmanned Aerial Vehicles (UAVs), and can provide impactful solutions for wireless communication channels. The use of Alamouti Space-Time Block Codes (STBCs) with diversity and many antennas improves performance in fading wireless channels. The demand for UAVs is rising day by day as they can easily reach at places where humans reach with utmost difficulty, and hence they are highly useful in military applications and disaster management. In this paper, we perform routing in a diamond-shaped network topology having four UAVs in a heterogeneous channel condition- we consider Rayleigh channel as ‘bad state model’ and Ricean channel as ‘good state model’. At first, routing is performed in the aforementioned scenario without using any channel estimation algorithm and next, we perform routing in the same scenario but this time using a channel estimation algorithm for BPSK using the STBC codes and multiple-antenna system. Eventually, we compare and analyze the results obtained and find that the routing performance gets enhanced when the maximum Versoria criterion (MVC) channel estimation algorithm is used.
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在菱形网络拓扑下利用MVC信道估计算法增强无人机辅助无线通信性能
编码和空间分集的融合为无线通信领域带来了新的发展方向,其中以无人机为重点,可以为无线通信信道提供有影响力的解决方案。具有分集和多天线的Alamouti空时分组码(stbc)的使用提高了衰落无线信道的性能。对无人机的需求日益增加,因为它们可以很容易地到达人类最难到达的地方,因此它们在军事应用和灾害管理方面非常有用。在本文中,我们在一个具有四架无人机的异质信道条件下的菱形网络拓扑中执行路由-我们将瑞利信道视为“坏状态模型”,将赖斯信道视为“好状态模型”。首先,在上述场景中执行路由而不使用任何信道估计算法,接下来,我们在相同的场景中执行路由,但这次使用使用STBC编码和多天线系统的BPSK信道估计算法。最后,对得到的结果进行了比较分析,发现采用最大Versoria准则(MVC)信道估计算法后,路由性能得到了提高。
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