In this paper, a new approach is proposed for implementing an adaptive decision feedback equalizer (ADFE) for the 5G channel. The proposed equalizer works in two phases. In the first phase, a least-squares (LS) algorithm with a variable-length training sequence is used to estimate the coefficients of the channel and the equalizer. In the second phase, the recursive least-squares algorithm estimates the channel and adapts the equalizer, jointly. According to the channel quality, a variable-length training sequence is used to estimate the channel vector and the coefficients of the equalizer. The feed-forward equalizer (FFE) compensates the effects of the transmitting filter and the channel filter. No matched filter is used in the receiver. The noise samples at the input of the proposed FFE are independent. The noise enhancement of the proposed FFE is less than the noise enhancement of its corresponding one in the conventional ADFE. The overall filtering response (OFR) from the input of the transmitting filter to the output of the FFE is calculated and used to estimate the coefficients of the feedback equalizer (FBE). The channel model, the FFE coefficients, the OFR vector, and the FBE coefficients are continuously updated every symbol period. Using a variable training sequence increases the bandwidth efficiency of the transmitted signal. Simulation results and real-time implementation measurements show that the convergence time and the steady-state error at the output of the proposed equalizer are smaller than their corresponding values in the conventional ADFE.

本文提出了一种新的方法来为5G信道实施自适应决策反馈均衡器（ADFE）。拟议的均衡器分两个阶段工作。在第一阶段，使用具有可变长度训练序列的最小二乘（LS）算法来估计信道和均衡器的系数。在第二阶段，递归最小二乘算法估计信道并联合调整均衡器。根据信道质量，使用可变长度训练序列来估计信道向量和均衡器的系数。前馈均衡器（FFE）补偿发射滤波器和信道滤波器的影响。接收器中未使用匹配的滤波器。拟议的FFE输入端的噪声样本是独立的。所提出的FFE的噪声增强小于常规ADFE中其对应噪声增强的噪声增强。计算从发射滤波器的输入到FFE的输出的总滤波响应（OFR），并将其用于估算反馈均衡器（FBE）的系数。信道模型，FFE系数，OFR矢量和FBE系数在每个符号周期中不断更新。使用可变的训练序列可以增加发射信号的带宽效率。仿真结果和实时实现测量结果表明，所提出的均衡器输出处的收敛时间和稳态误差小于常规ADFE中的相应值。计算从发射滤波器的输入到FFE的输出的总滤波响应（OFR），并将其用于估算反馈均衡器（FBE）的系数。信道模型，FFE系数，OFR矢量和FBE系数在每个符号周期中不断更新。使用可变的训练序列可以增加发射信号的带宽效率。仿真结果和实时实现测量结果表明，所提出的均衡器输出处的收敛时间和稳态误差小于常规ADFE中的相应值。计算从发射滤波器的输入到FFE的输出的总滤波响应（OFR），并将其用于估算反馈均衡器（FBE）的系数。信道模型，FFE系数，OFR矢量和FBE系数在每个符号周期中不断更新。使用可变的训练序列可以增加发射信号的带宽效率。仿真结果和实时实现测量结果表明，所提出的均衡器输出处的收敛时间和稳态误差小于常规ADFE中的相应值。FFE系数，OFR向量和FBE系数在每个符号周期内不断更新。使用可变的训练序列可以增加发射信号的带宽效率。仿真结果和实时实现测量结果表明，所提出的均衡器输出处的收敛时间和稳态误差小于常规ADFE中的相应值。FFE系数，OFR向量和FBE系数在每个符号周期内不断更新。使用可变的训练序列可以增加发射信号的带宽效率。仿真结果和实时实现测量结果表明，所提出的均衡器输出处的收敛时间和稳态误差小于常规ADFE中的相应值。