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Blind LTV shortening of doubly selective OFDM channels for UAS applications

机译：用于UAS应用的双选OFDM信道的LTV盲目缩短

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This paper deals with the synthesis of a blind channel shortening algorithm for orthogonal frequency-division multiplexing (OFDM) systems operating over doubly selective wireless channels, a challenging scenario that is likely to happen in modern unmanned aircraft systems (UASs) data links. When the length of the OFDM cyclic prefix (CP) is smaller than the channel order, we propose to employ a blind linear time-varying (LTV) time-domain equalizer, which shortens the channel impulse response of the channel in the minimum mean-output energy (MMOE) sense, requiring only estimation of the second-order statistics of the received data. The equalizer design leverages on the complex-exponential (CE) basis expansion model (BEM) for the doubly selective channel, which naturally leads to a frequency-shift (FRESH) filter implementation. Monte Carlo computer simulations are carried out to assess the effectiveness of the proposed FRESH-MMOE channel shortener.
机译：本文涉及在双选无线信道上运行的正交频分复用（OFDM）系统的盲信道缩短算法的综合，这是一种有挑战性的情况，很可能会在现代无人机系统（UAS）数据链路中发生。当OFDM循环前缀（CP）的长度小于信道阶数时，我们建议采用盲线性时变（LTV）时域均衡器，以最小均值缩短信道的信道冲激响应。输出能量（MMOE）感知，仅需要估计接收到的数据的二阶统计量即可。均衡器设计针对双选择通道利用了基于复指数（CE）的扩展模型（BEM），这自然导致了频移（FRESH）滤波器的实现。进行了蒙特卡洛计算机仿真，以评估所提出的FRESH-MMOE通道缩短器的有效性。

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