Uplink and Downlink NOMA Based on a Novel Interference Coefficient Estimation Strategy for Next-Generation Optical Wireless Networks
Uplink and Downlink NOMA Based on a Novel Interference Coefficient Estimation Strategy for Next-Generation Optical Wireless Networks
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DOI：
10.3390/photonics10050569
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发表时间：
2023-05
期刊：
影响因子：
2.4
通讯作者：
S. Mohsan;Yanlong Li;Zejun Zhang;Amjad Ali;Jing Xu
中科院分区：
文献类型：
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作者：
S. Mohsan;Yanlong Li;Zejun Zhang;Amjad Ali;Jing Xu
非正交多址(NOMA)已被广泛认为是提高无线光通信系统传输容量的一种很有前途的技术。NOMA考虑连续干扰消除(SIC)的原理，以在接收端分离用户的信号。为了提高光信号的检测能力，我们开发了一种结合多输入单输出(MISO)的量子点(QD)荧光集中器，实现了基于NOMA的上行链路光无线系统。然而，在接收端使用SIC检测算法对多个用户进行不准确的干扰评估可能会导致更突出的错误传播问题，并影响系统的误码率性能。针对NOMA可见光通信系统，提出了一种基于递归神经网络的导频干扰系数估计算法。与传统的SIC检测算法相比，该算法通过引入干扰系数，提高了干扰估计的精度。它为逐层干扰消除提供了更准确的重建可能性，并减弱了误差传播的影响。此外，我们还设计了上行链路和下行链路NOMA-VLC通信系统进行了实验验证。当功率分配比在0.8~0.97时，下行链路的实验结果验证了最小二乘(LS)-SIC和长短期记忆递归神经网络(LSTM)-SIC检测策略的两个用户的误码率性能都满足前向纠错(FEC)极限。此外，对于所有用户，当功率分配比在0.92~0.93范围内时，LSTM-SIC算法的误码率性能优于LS-SIC算法。特别是，我们提出的系统在1.5m的空闲空间上使用量子点提供了2cm2的大检测面积和高达40 Mbps的聚合数据速率，并成功地实现了两个用户的平均误码率为2.3x10−3。
Non-orthogonal multiple access (NOMA) has been widely recognized as a promising technology to improve the transmission capacity of wireless optical communication systems. NOMA considers the principle of successive interference cancellation (SIC) to separate a user’s signal at the receiver side. To improve the ability of optical signal detection, we developed a quantum dot (QD) fluorescent concentrator incorporated with multiple-input and single-output (MISO) to realize an uplink NOMA-based optical wireless system. However, inaccurate interference assessment of multiple users using the SIC detection algorithm at the receiver side may lead to more prominent error propagation problems and affect the bit error rate (BER) performance of the system. This research aims to propose a novel recurrent neural network-based guided frequency interference coefficient estimation algorithm in a NOMA visible light communication (VLC) system. This algorithm can improve the accuracy of interference estimation compared with the traditional SIC detection algorithm by introducing interference coefficients. It provides a more accurate reconstruction possibility for level-by-level interference cancellation and weakens the influence of error propagation. In addition, we designed uplink and downlink NOMA-VLC communication systems for experimental validation. When the power allocation ratio was in the range of 0.8 to 0.97, the experimental results of the downlink validated that the BER performance of both users satisfied the forward error correction (FEC) limit with the least squares (LS)-SIC and the long short-term memory recurrent neural networks (LSTM)-SIC detection strategy. Moreover, the BER performance of the LSTM-SIC algorithm was better than that of the LS-SIC algorithm for all users when the power allocation ratio was in the range of 0.92 to 0.93. In particular, our proposed system offered a large detection area of 2 cm2 and corresponding aggregate data rate up to 40 Mbps over 1.5 m of free space by using QDs, and we successfully achieved a mean bit error rate (BER) of 2.3 × 10−3 for the two users.