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Temporal Synchronization of MIMO Wireless Communication in the Presence of Interference

机译:存在干扰时MIMO无线通信的时间同步

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摘要

In wireless communications systems that potentially operate in interference, acquisition and temporal alignment of a transmitted signal by a receiver can be the most fragile component of the link. In this paper, synchronization detection in the presence of interference for multiple-input multiple-output (MIMO) communication is discussed. Here, synchronization indicates signal acquisition and timing estimation at the receiver, and is formulated as a binary statistical hypothesis test. Transmit sequences from multiple antennas are received by multiple antennas in noisy environments with spatially correlated noise (interference). Flat-fading and frequency-selective channel models for both the interference and signal of interest are considered. By applying well-known multiple antenna approaches to the MIMO synchronization problem, a number of new synchronization test statistics are introduced. These test statistics are motivated by minimum-mean-square-error (MMSE) beamformers, generalized-likelihood ratio test (GLRT), least-squared (LS) channel estimation, and spatial invariance. Test statistics appropriate for orthogonal-frequency-division-multiplexing (OFDM) systems are considered, including test statistics that take advantage of cyclic prefixes and of pilot sequences within an OFDM symbol. Performances of various test statistics in terms of probability of missing detection for some probability of a false detection are shown to vary by multiple orders of magnitude in the presence of interference.
机译:在可能以干扰方式工作的无线通信系统中,接收机对发射信号的捕获和时间对准可能是链路中最脆弱的部分。在本文中,讨论了在存在干扰的情况下进行多输入多输出(MIMO)通信的同步检测。在此,同步表示接收器处的信号采集和时序估计,并被公式化为二进制统计假设检验。在嘈杂的环境中,多个天线会接收来自多个天线的发射序列,这些发射具有空间相关的噪声(干扰)。考虑了针对干扰和感兴趣信号的平坦衰落和频率选择性信道模型。通过将众所周知的多天线方法应用于MIMO同步问题,引入了许多新的同步测试统计数据。这些测试统计数据受最小均方误差(MMSE)波束形成器,广义似然比测试(GLRT),最小二乘(LS)信道估计和空间不变性的驱动。考虑适合于正交频分复用(OFDM)系统的测试统计信息,包括利用OFDM符号内循环前缀和导频序列的测试统计信息。在存在干扰的情况下,对于某些误检测的概率,就丢失检测的概率而言,各种测试统计数据的性能显示变化了多个数量级。

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