湍流信道下差分索引移位键控直流偏置光OFDM

Differential Index Shift Keying DC Bias Optical OFDM in Turbulent Channels

针对现有光无线正交频分复用(OFDM)索引调制均需接收端已知信道状态信息的问题,通过构建满足差分运算的时频弥散矩阵进行索引映射,提出了一种差分索引移位键控光OFDM方案。推导出了该方案在最大似然准则下的平均误码率上界,并与子载波索引移位键控直流偏置光OFDM(SISK-DCO-OFDM)系统进行了性能对比。其次,依据差分信号的特点,构造了一种适用于机器学习的差分信号特征向量,并结合径向基神经网络提出了一种多分类检测器,有效降低了译码复杂度。结果表明,所提差分索引方案有效避免了复杂的信道估计,同时在高信噪比下获得了近似SISKDCO-OFDM的误码性能。所提检测器取得了近似差分最大似然检测算法的误码性能,而且复杂度大大降低,例如当子载波块长度为2和4时,所提检测器的复杂度分别降低了16.67%和70%。

Objective Optical OFDM index modulation(O-OFDM-IM)is a new multicarrier modulation technique that can achieve remarkable improvements in transmission rate and bit error rate(BER)performance by carrying additional information through the index of subcarriers.Currently,in the field of optical communication,O-OFDM-IM has triggered a research boom for potential improvements in system error performance and spectrum efficiency.However,existing O-OFDM-IM schemes require complex channel estimation at the receiver to obtain channel state information,which not only increases the complexity of the receiver but also brings a large spectrum resource overhead.This study proposes a differential index shift keying DC-bias optical OFDM(DISK-DCO-OFDM)scheme that avoids complex channel estimation while ensuring BER performance.Additionally,a multiclassification detector based on radial basis function(RBF)neural network is suggested to address the high complexity of the receiver.Methods By considering a single subcarrier block as an example at the transmitter side,an initial transmission matrix that does not carry information is first prepared at the transmitter before the differential operation is performed.Then,the input binary bits are mapped into a time-frequency dispersion matrix that satisfies the difference operation,i.e.,the matrix has only one non-zero element in each row and column.For difference operation,the time-frequency dispersion matrix of the current moment is multiplied with the transmission matrix of the previous moment to obtain the true signal matrix of the current moment.Next,the real signal matrix is transmitted by the laser after the Hermitian symmetry and inverse Fourier transform.On the receiver side,the received signal matrix of the previous moment was first inverted and then multiplied with the received signal matrix of the current moment,and the characteristic matrix of the received signal can be obtained.Then,the real and imaginary parts of the feature matrix were used to construct a one-dimensional feature vector,which was used as the input of the RBF neural network.Finally,the trained neural network was used as a multiclassification detector to complete the decoding work at the receiver side.The proposed scheme completely avoids complex channel estimation.Results and DiscussionsThe DISK-DCO-OFDM system was established in this study and the BER performance of the system was simulated under different turbulence intensity and received aperture conditions.First,we derived an upper bound of the average bit error rate(ABER)of the system and compared the simulated BER with the ABER(Fig.2).The two curves asymptotically coincided at high signal-to-noise ratios,which demonstrated the accuracy of the derived ABER.Then,we compared the BER performance of the proposed scheme with that of the conventional subcarrier index shift keying DCO-OFDM(SISK-DCO-OFDM)system,and the corresponding results are shown in Fig.3.The BER performance of the proposed scheme is substantially better than that of the SISK-DCO-OFDM system when the subcarrier block length is 2 under weak turbulence condition.When the subcarrier block length is 4,the BER curves of the proposed scheme and the SISK-DCO-OFDM system coincided at high SNR.Therefore,the proposed scheme guarantees the BER performance while effectively avoiding the channel estimation.The computational complexity reduction rate and BER performance of the proposed multiclassification detector for the receiver side compared with the differential maximum likelihood(DML)detection algorithm are shown in Fig.6 and Fig.7,respectively.The computational complexity of the proposed detector is reduced by 16.67%and 70%for subcarrier block lengths of 2 and 4,respectively,compared with the DML.The difference in the BER performance between the two detection algorithms does not exceed 2 dB under weak turbulence.Conclusions This study proposes a DISK-DCO-OFDM scheme.The main feature of this scheme is the use of a timefrequency dispersion matrix that satisfies the differential process.Simulation results show that the proposed scheme not only effectively avoids the channel estimation process but also guarantees better BER performance than all current optical OFDM index modulation systems in a weak turbulence environment.Meanwhile,the proposed multiclassification detector can considerably reduce the decoding complexity at the receiver side,and the difference in BER performance compared with DML does not exceed 2 dB.In particular,the method of constructing the received signal feature vector provides an effective reference for future decoding using machine learning or deep learning methods at the receiver side for differentialtype systems.Therefore,the proposed scheme can provide a reference for the application of optical OFDM index modulation in complex channel environments,and the proposed multiclassification detector can contribute to future research on reducing the decoding complexity at the receiver side.