Wu Tingyao, Bie Hongxia, Wen Jinfang
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
School of Electronic Information, Wuhan University, Wuhan 430072, China.
Sensors (Basel). 2022 May 23;22(10):3937. doi: 10.3390/s22103937.
Compared with orthogonal frequency division multiplexing (OFDM) systems, orthogonal time frequency space systems based on bi-orthogonal frequency division multiplexing (OTFS-BFDM) have lower out-of-band emission (OOBE) and better robustness to high-mobility scenarios, but suffer from a higher peak-to-average ratio (PAPR) in large data packets. In this paper, one-iteration clipping and filtering (OCF) is adopted to reduce the PAPR of OTFS-BFDM signals. However, the extra noise introduced by the clipping process, i.e., clipping noise, will distort the desired signal and increase the bit error rate (BER). We propose a message passing (MP)-assisted iterative cancellation (MP-AIC) method to cancel the clipping noise based on the traditional MP decoding at the receiver, which incorporates with the (OCF) at the transmitter to keep the sparsity of the effective channel matrix. The main idea of MP-AIC is to extract the residual signal fed to the MP detector by iteratively constructing reference clipping noise at the receiver. During each iteration, the variance of residual signal and channel noise are taken as input parameters of MP decoding to improve the BER. Moreover, the convergence probability of the modulation alphabet after MP decoding in the current iteration is used as the initial probability of MP decoding in the next iteration to accelerate the convergence rate of MP decoding. Simulation results show that the proposed MP-AIC method significantly improves MP-decoding accuracy while accelerating the BER convergence in the clipped OTFS-BFDM system. In the clipped OTFS-BFDM system with rectangular pulse shaping, the BER of MP-AIC with two iterations can be reduced by 72% more than that without clipping noise cancellation.
与正交频分复用（OFDM）系统相比，基于双正交频分复用的正交时频空系统（OTFS - BFDM）具有更低的带外发射（OOBE）以及对高移动性场景更好的鲁棒性，但在大数据包中会面临更高的峰均比（PAPR）。本文采用一次迭代限幅与滤波（OCF）来降低OTFS - BFDM信号的PAPR。然而，限幅过程引入的额外噪声，即限幅噪声，会使期望信号失真并增加误码率（BER）。我们提出一种基于消息传递（MP）辅助的迭代消除（MP - AIC）方法，在接收机端基于传统的MP解码来消除限幅噪声，该方法与发射机端的（OCF）相结合以保持有效信道矩阵的稀疏性。MP - AIC的主要思想是通过在接收机端迭代构建参考限幅噪声来提取馈送到MP检测器的残余信号。在每次迭代中，将残余信号和信道噪声的方差作为MP解码的输入参数以改善BER。此外，将当前迭代中MP解码后调制星座的收敛概率用作下一次迭代中MP解码的初始概率，以加快MP解码的收敛速度。仿真结果表明，所提出的MP - AIC方法在加速限幅OTFS - BFDM系统中BER收敛的同时，显著提高了MP解码精度。在具有矩形脉冲整形的限幅OTFS - BFDM系统中，经过两次迭代的MP - AIC的BER比不进行限幅噪声消除时可降低72%以上。
