摘要
预失真器(PD)的系数辨识是预失真系统的核心,最小均方(LMS)算法是自适应参数辨识的基本方法之一。在实际系统设计中,因射频信号采集造成的量化噪声的影响通常被忽略,短波发信系统非线性对数字通信误码率的影响研究不够充分。针对以上问题,理论分析并仿真LMS预失真器在维纳收敛条件下的抗量化噪声性能及误码率改善指标。结果表明:针对典型的短波功放,在预失真多项式阶数为7的条件下,LMS预失真能够使发射机互调指标改善44.7 dB;针对8PSK和16QAM调制的信噪比改善量分别达到1.6 dB和2.6 dB;非线性性能改善存在由射频信号采样量化噪声决定的MSE性能平板。
The identification of PD coefficient is the core of predistortion system,while the LMS algorithm is one of the basic methods in adaptive parameter identification. In actual system design, the effect of quantization noise caused by RF signal sampling is usually neglected, and the study of the influence on digital communication BER (bit error rate) caused by the nonlinearity of shortwave transmitting system is not enough. In view of the above problems, theoretical analysis and simulation are done on the anti- noise performance and the BER indicator improvement of the LMS predistortor under the condition of wiener convergence. The theoretical analysis and simulation results indicate that for typical shortwave PA, intermodulation performance improvement of 44.7dB can be achieved with PIPD applied when the order of PD polynomial is set at 7; and 1.6 dB and 2.6 dB SNR improvement can be achieved respectively for 8PSK and 16QAM modulation at the same time; the nonlinear performance improvements have MSE performance platform decided by the radio-frequency signal sample quantization noise.
出处
《通信技术》
2017年第3期410-415,共6页
Communications Technology
关键词
LMS算法
基带预失真
系数辨识
量化噪声
误码率
LMS algorithm
base-band predistortion
coefficient identification
quantization noise
BER