重噪声和衰落下的DoA检测

F. Morab, Rajeshwari Hegde, Veena Hegde
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引用次数: 0

摘要

进入的电磁信息信号由天线几何形状设置为均匀线性阵列(ULA)配置的基站(BS)接收,并通过计算其到达方向(DoA)来检测所需用户。衰落和噪声的存在使检测过程更具挑战性。为此,提出了三角分解DoA (TD)方法,并将其建模为向量子空间方法。无论用户之间的空间距离是远还是近,也无论系统使用的天线单元是多还是少,所提出的TD方法都能提供对所需用户的最佳检测。针对不同用例,将现有方法与所提方法进行了比较。所提出的TD方法可以非常高分辨率地检测到用户之间2度的间隔,而现有方法在信道不稳定的情况下只能检测到5度的间隔。通过计算时间复杂度和检测误差等性能参数,验证了算法的鲁棒性和准确性。与现有方法相比,所提出的TD方法具有一致性最好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DoA Detection Under Heavy Noise and Fading
Incoming electromagnetic message signals are received by the Base Station (BS) with antenna geometry setup as a Uniform Linear Array (ULA) configuration, and the desired users are detected by computing their Direction of Arrival (DoA). The presence of fading and noise makes the detection process more challenging. Thus to accomplish this, Triangular Decomposition DoA (TD) Method has been proposed, which is modeled as a vector subspace method. Whether the spatial distance between the users is far or near, or when the system is using either large or fewer antenna elements, the proposed TD method provides optimal detection of the desired users. The existing methods were compared with the proposed method for different use cases. The proposed TD Method detected the desired users with a very high-resolution detection of 2-degree spacing between the users whereas, existing methods could detect only up to 5-degree spacing under the erratic conditions of the channel. The different performance parameters were computed such as Time Complexity and Detection Error to test the robustness and accuracy of these algorithms. The proposed TD method delivered the best results consistently as compared to the existing methods.
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