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Analysis of spatial correlation of precoding indoor MIMO visible light communication system
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摘要:
为了解决多用户MIMO(MU-MIMO)室内可见光通信中存在用户间干扰问题及对角化(BD)算法所产生的子信道强弱的问题，利用子流选择BD算法，对室内MU-MIMO可见光通信系统的误码率进行优化。建立了MU-MIMO室内可见光通信的信道模型，利用控制变量法并采用不同LED与PD距离的参数，对比了在4×4 MIMO与8×8 MIMO两种不同的室内系统布局方式下的信道空间相关性，分析对比子流选择BD算法及BD算法的系统容量及误码率性能。结果表明，随着空间相关的不断增强，误码率性能下降，子流选择BD算法相对于BD算法可以带来4 dB以上的增益。
Abstract:In order to solve the problem of multi-user interference and the subchannel strength generated by the block diagonalization (BD) algorithm in multi-user MIMO (MU-MIMO) indoor visible light communication, the bit error rate of the indoor MU-MIMO visible light communication system is optimized by using the substream selected BD algorithm. This paper establishes the channel model for MU-MIMO indoor visible light communication and compares the channel spatial correlation between the 4×4 MIMO and 8×8 MIMO in different indoor system layout modes by using the control variable method and taking different parameters of LED and PD distance, the system capacity and bit error rate performance of substream selected BD algorithm and BD algorithm are compared and analyzed. The results show that with the continuous enhancement of spatial correlation, the bit error rate performance decreases, and the substream selected BD algorithm can bring a gain of more than 4 dB compared with BD algorithm.
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Overview: Visible light communication is a kind of wireless communication, which can solve the problem of serious electromagnetic radiation or limited spectrum resources in hospitals, mines, military, etc. It's a new communication technology with green, high efficiency and energy saving. In the actual application scenario, there are multiple users and multiple sets of LEDs in the room, which can effectively reduce the communication link interruption caused by indoor displays and personnel walking. There are many researches on indoor MIMO visible light communication, most of which are mainly to solve the problem of indoor layout, diversity reception and so on. However, the receiver can receive interference from others. Precoding technology is mainly used to reduce the inter-user interference now, but the spatial correlation research of precoding for visible light communication is relatively rare. In this paper, two indoor MIMO visible light communication system models are established, namely 4×4 and 8×8. The substream selected BD algorithm is applied to the indoor MIMO visible light communication system. By optimizing the singular value of the singular value decomposition caused by the BD algorithm in the equivalent channel matrix, the purpose of reducing inter-user interference is realized. At the same time, under different indoor system models and the distribution of LED and PD, the channel capacity and bit error rate performance of BD algorithm and substream selected BD algorithm are studied. The indoor MIMO visible light communication system with substream selected BD algorithm in the above figure mainly includes three parts: the transmitter, the receiver and channel. The transmitter mainly performs serial-to-parallel conversion of data, controls the parallel data modulation by on-off keying modulation and processes substream selected BD algorithm, and to add the DC offset and use the high frequency flickering characteristic of the LED to perform data transmission; at the receiver, the received signal is decoded and demodulated by the optical detector to restore the original data and complete the information transmission. The simulation results show that in terms of channel capacity, the spatial correlation of the channel is stronger and the channel capacity is increased. Meanwhile, under the indoor channel of 4×4, the channel capacity of the BD algorithm is higher than the substream selected BD algorithm under different spatial correlations, but under the indoor 8×8 channel, BD algorithm and substream selected BD algorithm have little difference in capacity under different spatial correlation; in terms of the bit error rate of the system, the bit error rate of the substream selected BD algorithm can bring a gain of more than 4 dB compared with the BD algorithm, the spatial correlation is continuously enhanced, and the system error rate performance is degraded.
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图 1 子流选择BD算法MU-MIMO室内VLC系统模型
Figure 1. Substream selected BD algorithm MU-MIMO indoor VLC system model
图 2 室内MIMO VLC系统4×4的空间分布。
Figure 2. Indoor MIMO VLC system spatial distribution of 4×4.
图 3 室内MIMO VLC系统8×8的空间分布。
Figure 3. Indoor MIMO VLC system spatial distribution of 8×8.
图 4 四种空间相关性下SNR与信道容量的曲线。
Figure 4. Curve between SNR and channel capacity under four spatial correlation.
图 5 不同信道相关性下SNR与BER的曲线。
Figure 5. Curve between SNR and BER under different channel correlation.
表 1 仿真参数
Table 1. Simulation parameters
参数 数值 房间尺寸/(m3) 5×5×3 光检测器的面积/(cm2) 1.0 噪声带宽因子 0.562 反射系数 1.5 LED半功率角/(°) 70 传输速率/(Mbit/s) 100 参数 数值 光滤波器增益 1.0 调制指数 0.2 背景光电流/mA 5100 光检测器响应度/(A/W) 0.4 光检测器的视场角/(°) 60 LED阵列 3600(60×60) 
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