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A soft-input/soft-output dequantizer for cloud-based mobile networks

机译:用于基于云的移动网络的软输入/软输出反量化器

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The use of soft information instead of hard bits has been widely adapted in signal processing for digital communication to improve the reliability of data transmission by techniques like turbo equalization, turbo decoding, or LDPC codes. For future mobile networks employing a centralized architecture in which the antenna and the baseband processing are separated by an additional fronthaul channel that forwards digitalized samples, we have identified another process that can be redesigned to embrace the concept of soft information: the dequantizer. A dequantizer transforms a vector of bits into amplitudes representing digitalized samples. However, if the bits were transmitted through a lossy fronthaul channel, the soft information that can be extracted from this channel's detection process is lost in a classical dequantizer. In this work, we propose a soft-input/soft-output dequantizer that passes this information through to the subsequent signal processing steps and can thereby improve the overall reliability of centralized, cloud-based mobile networks.
机译:通过诸如turbo均衡,turbo解码或LDPC码之类的技术,软信息代替硬位已广泛用于数字通信的信号处理中,以提高数据传输的可靠性。对于未来采用集中式架构的移动网络,其中天线和基带处理被转发数字化样本的附加前传信道分隔开,我们已经确定了可以重新设计以包含软信息概念的另一个过程:反量化器。反量化器将位向量转换为代表数字化样本的幅度。但是,如果这些比特是通过有损耗的前传信道发送的,则可以从该信道的检测过程中提取的软信息会在经典的解量化器中丢失。在这项工作中,我们提出了一种软输入/软输出反量化器,该信息将这些信息传递到后续的信号处理步骤,从而可以提高基于云的集中式移动网络的整体可靠性。

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