深度学习辅助的超奈奎斯特速率光空间脉冲位置调制  

Deep Learning-Aided Faster-Than-Nyquist Rate Optical Spatial Pulse Position Modulation

作　　者：张悦 叶翔文 曹明华[1] 王惠琴[1] Zhang Yue;Ye Xiangwen;Cao Minghua;Wang Huiqin(School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,Gansu,China)

机构地区：[1]兰州理工大学计算机与通信学院,甘肃兰州730050

出　　处：《光学学报》2024年第5期49-59,共11页Acta Optica Sinica

基　　金：国家自然科学基金(62265010,61875080,62261033);兰州理工大学博士基金(14062101)。

摘　　要：针对现有光空间调制传输速率和频谱效率低的问题,提出了一种超奈奎斯特速率光空间脉冲位置调制(OSPPM-FTN)方案。推导了Gamma-Gamma湍流信道下该方案最大似然检测时的平均误码率上界,并与已有光空间脉冲位置调制(OSPPM)系统进行了性能对比。在此基础上,针对OSPPM-FTN发送信号的特点,提出了一种多分类神经网络(MNN)信号译码器,以大幅降低计算复杂度。最后,采用蒙特卡罗方法进行了仿真。结果表明,随着加速因子的减小,所提系统的频谱效率和传输速率有明显提升,其代价是信噪比(SNR)损失。当加速因子为0.9时,相比于传统(4,4,4)-OSPPM,所提系统的频谱效率和传输速率分别提升了17%和5.5%,SNR损失仅为1 dB。同时,采用MNN译码器可逼近最大似然最优译码性能并降低其计算复杂度,当探测器数目为8和16时,计算复杂度分别降低了69.75%和89.95%。Objective As an innovative multiple-input-multiple-output(MIMO)technology,optical spatial modulation(OSM)resolves antenna interference and synchronization challenges in MIMO systems by selecting a single antenna to carry information and collectively transmits the antenna index as additional information.However,existing OSM research predominantly adheres to the orthogonal transmission criterion,and imposes limitations on enhancing the transmission rate of the system although the research is effective in avoiding inter-symbol interference.To this end,the introduction of nonorthogonal transmission via Faster-Than-Nyquist(FTN)technology compresses symbol intervals during pulse shaping,enabling an increase in transmission rate within the same bandwidth per unit time.As a result,we propose a novel FasterThan-Nyquist rate optical spatial pulse position modulation scheme that combines OSM with FTN to further enhance the transmission rate and spectrum efficiency of the system.Additionally,in response to the highly complex receiver issue,a multiclassification neural network(MNN)decoder is proposed to significantly reduce computational complexity and achieve approximate optimal detection.Methods At the transmitting end,the input binary bit stream is divided into two groups of data blocks after serial/parallel transformations.The first group of data blocks is mapped to the index of the selected lasers for each symbol period,while the second group is mapped to pulse position modulation(PPM)symbols.An FTN shaping filter is employed to compress the PPM symbols.Then,the compressed PPM-FTN signals are loaded onto the chosen lasers for transmission.The signal traverses the Gamma-Gamma channel,and it is received by photodetectors(PDs)and converted into an electrical signal for further signal processing at the receiving end.Initially,downsampling is conducted to obtain a signal with the same dimensionality as the input signal.The downsampled signal is then classified based on its effective features,with each class being assigned the

关 键 词：光通信 光空间调制 超奈奎斯特 深度学习 误码率 

分 类 号：TN929.12[电子电信—通信与信息系统]