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A low complexity channel estimation scheme for Massive MIMO systems

机译:用于大规模MIMO系统的低复杂度信道估计方案

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It is well-known that Massive MIMO systems (Multiple-input multiple-output) have high potential for future wireless broadband systems. Massive MIMO (m-MIMO) relies on spatial multiplexing, and for that reason the base station needs a precise channel knowledge at uplink and downlink. Pilots can be used for channel state information (CSI) estimation, but common estimation processes imply a matrix inversion which can be a heavy computational process for m-MIMO system where the number of antennas used in the communication is very high. To alleviate computational requirements, reduce latency and to improve battery life capacity of mobile devices matrix inversion operations should be avoided. Having in mind these constrains, a new channel estimation method based on Zadoff-Chu (ZC) sequences is presented here, that achieves similar or better performance than least squares (LS) or minimum mean-Square Error (MMSE) channel estimators. It is also presented a set of performance results that sustain our assumption.
机译:众所周知,大规模MIMO系统(多输入多输出)在未来的无线宽带系统中具有很高的潜力。大规模MIMO(m-MIMO)依赖于空间复用,因此,基站需要在上行链路和下行链路上具有精确的信道知识。可以将导频用于信道状态信息(CSI)估计,但是常见的估计过程意味着矩阵求逆,对于在通信中使用的天线数量非常高的m-MIMO系统,这可能是繁重的计算过程。为了减轻计算要求,减少等待时间并提高移动设备的电池寿命容量,应避免矩阵求逆操作。考虑到这些限制,此处介绍了一种基于Zadoff-Chu(ZC)序列的新信道估计方法,该方法与最小二乘(LS)或最小均方误差(MMSE)信道估计器相比,具有相似或更好的性能。它还提出了一组性能结果,可以支持我们的假设。

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