基于叠加训练的非合作多用户/MIMO信道估计

Uncoordinated multiuser/MIMO channel estimation using superimposed training

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的"训练序列"来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。

An iterative channel estimation and detection scheme is proposed for single carrier uncoordinated multi- user/multi-input multi-output （MIMO） system using superimposed training （ST）. At first, the multiple antennas mutual interferences are eliminated by utilizing training sequences with all-zero cross-correlation property, which are designed based on transform domain approach. The channel estimation is performed based on first-order statistics of the observations in time domain. Then a joint iterative channel estimation and symbol detection method is addressed, where the detected sequences are used as additional ＂training sequence＂ to reduce the self-interferences from information sequences. Compared to the existing ST schemes, the new proposed scheme has more flexible training sequences, better channel mean square error （NCMSE） and BER performance at low SNR, but retains a lower computation complexity. Simulation results corroborate the effectiveness of the new scheme.