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A joint PDA data detection algorithm with MMSE channel estimation for uplink transmission of massive MU-MIMO system

机译:带有MMSE信道估计的联合PDA数据检测算法,用于大规模MU-MIMO系统的上行链路传输

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Massive multiple-input-multiple-output (MIMO), also known as a large-scale antenna system has been adopting by many 4G and 5G wireless communication standards due to its high data rate and outstanding link reliability. This paper considers a joint data detection scheme for uplink transmission of an L-cell massive multiple-user MIMO (MU-MIMO) system. In each MIMO cell, one base station with a large number of antennas communicates with multiple single-antenna users. A mathematical model is first proposed for received signals at a base station, and then a pilot-based minimum mean square error (MMSE) scheme is derived. A zero-forcing (ZF) data detection method is used to recover the transmitted signal, and categorize the interference by using the estimated channel information. The power of signal, interference, and noise are analyzed respectively. Then a more sophisticated probabilistic data association (PDA) detection algorithm with MMSE channel estimation is applied to jointly detect data with high accuracy. Finally, simulation results are presented to demonstrate that the proposed joint MMSE-PDA data detection algorithm outperforms the MMSE-ZF scheme.
机译:大规模多输入多输出(MIMO),也称为大型天线系统,由于其高数据速率和出色的链路可靠性,已被许多4G和5G无线通信标准采用。本文考虑了一种用于L小区大规模多用户MIMO(MU-MIMO)系统的上行链路传输的联合数据检测方案。在每个MIMO小区中,一个带有大量天线的基站与多个单天线用户进行通信。首先针对基站的接收信号提出数学模型,然后推导基于导频的最小均方误差(MMSE)方案。迫零(ZF)数据检测方法用于恢复传输的信号,并通过使用估计的信道信息对干扰进行分类。分别分析信号的功率,干扰和噪声。然后,将一种具有MMSE信道估计功能的更复杂的概率数据关联(PDA)检测算法应用于高精度联合检测数据。最后,仿真结果表明,提出的联合MMSE-PDA数据检测算法优于MMSE-ZF方案。

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