Massive MIMO opens up attractive possibilities for next generation wireless systems with its large number of antennas offering spatial diversity and multiplexing gain. However, the fronthaul link that connects a massive MIMO Remote Radio Head (RRH) and carries IQ samples to the Baseband Unit (BBU) of the base station can throttle the network capacity/speed if appropriate data compression techniques are not applied. In this paper, we propose an iterative technique for fronthaul load reduction in the uplink for massive MIMO systems that utilizes the convolution structure of the received signals. We use an alternating minimisation algorithm for blind deconvolution of the received data matrix that provides compression ratios of 30-50. In addition, the technique presented here can be used for blind decoding of OFDM signals in massive MIMO systems.
翻译:大型MIMO为下一代无线系统开辟了有吸引力的可能性,其大量天线具有空间多样性和多轴增益,然而,连接大型MIMO远程无线电台长(RRH)并将IQ样本送到基地站基地波段股(BBU)的正面连接可不采用适当的数据压缩技术,从而在网络能力/速度方面造成障碍。本文建议对大型MIMO系统利用所接收信号的卷变结构的上行链路进行迭接技术,以降低其前厅负荷。我们使用一种交替最小化算法将接收的数据矩阵盲目变异,提供30-50的压缩比率。此外,这里介绍的技术可用于在大型MIMO系统中盲目解码DM信号。