張 穎，高 悅，柯熙政

預(yù)編碼室內(nèi)MIMO可見光通信系統(tǒng)空間相關(guān)性分析

張 穎1,2，高 悅1*，柯熙政1,2

1西安理工大學(xué)自動(dòng)化與信息工程學(xué)院，陜西 西安 710048；2陜西省智能協(xié)同網(wǎng)絡(luò)軍民共建重點(diǎn)實(shí)驗(yàn)室，陜西 西安 710048

為了解決多用戶MIMO(MU-MIMO)室內(nèi)可見光通信中存在用戶間干擾問題及對(duì)角化(BD)算法所產(chǎn)生的子信道強(qiáng)弱的問題，利用子流選擇BD算法，對(duì)室內(nèi)MU-MIMO 可見光通信系統(tǒng)的誤碼率進(jìn)行優(yōu)化。建立了MU-MIMO室內(nèi)可見光通信的信道模型，利用控制變量法并采用不同LED與PD距離的參數(shù)，對(duì)比了在4′4 MIMO與8′8 MIMO兩種不同的室內(nèi)系統(tǒng)布局方式下的信道空間相關(guān)性，分析對(duì)比子流選擇BD算法及BD算法的系統(tǒng)容量及誤碼率性能。結(jié)果表明，隨著空間相關(guān)的不斷增強(qiáng)，誤碼率性能下降，子流選擇BD算法相對(duì)于BD算法可以帶來4 dB以上的增益。

可見光通信；子流選擇；信道相關(guān)性；塊對(duì)角化

1 引 言

可見光通信(Visible light communication，VLC)已影響著人們的生活，為達(dá)到實(shí)際照明標(biāo)準(zhǔn)以及避免通信中斷，將多輸入多輸出(multi-input multi-output，MIMO)技術(shù)應(yīng)用于室內(nèi)VLC系統(tǒng)中形成可見光MIMO技術(shù)[1]，不僅擴(kuò)大信號(hào)的到達(dá)范圍，還提高數(shù)據(jù)傳輸速率[2]。

針對(duì)MIMO VLC系統(tǒng)的研究很多，主要集中在優(yōu)化室內(nèi)的光源布局、信號(hào)調(diào)制方式、分集接收等方面。趙黎等[3]設(shè)計(jì)了一種優(yōu)化的環(huán)形光源布局；Ishikawa等[4]使用空間調(diào)制技術(shù)對(duì)功率不平衡MIMO系統(tǒng)的容量進(jìn)行最大化；薛家豪等[5]利用分集接收技術(shù)設(shè)計(jì)了光電二極管的布局及數(shù)據(jù)選擇接收裝置，保證通信質(zhì)量。Huang等[6]設(shè)計(jì)了一種改進(jìn)型規(guī)整晶格解碼技術(shù)的MIMO VLC系統(tǒng)的收發(fā)器；Narmanlioglu等[7]采用非順序光線跟蹤對(duì)各種實(shí)際布線和布線拓?fù)溥M(jìn)行MIMO VLC信道建模。然而，接收端通常會(huì)接收到來自于其他用戶數(shù)據(jù)的干擾，從而造成系統(tǒng)性能下降。線性預(yù)編碼算法可以有效地降低來自于其他用戶的數(shù)據(jù)干擾及接收端的復(fù)雜度[8]，其中塊對(duì)角化(block diagonalization，BD)算法是一種典型的線性預(yù)編碼技術(shù)，但BD算法的研究主要用于降低用戶間的干擾及提高系統(tǒng)性能方面[9]，在室內(nèi)MIMO VLC系統(tǒng)的空間相關(guān)性研究較少。由于室內(nèi)MIMO VLC系統(tǒng)中LED光源與光電檢測(cè)器(photoelectric detector，PD)的不同位置組合會(huì)出現(xiàn)不同的子信道，同時(shí)影響MIMO信道的空間相關(guān)性及系統(tǒng)性能[10]，因此研究預(yù)編碼技術(shù)的室內(nèi)MIMO VLC系統(tǒng)信道的空間相關(guān)性具有重要意義。

論文將無線通信中的子流選擇BD技術(shù)[11]應(yīng)用到室內(nèi)多用戶MIMO(multipleuser MIMO，MU-MIMO)VLC系統(tǒng)中，討論了室內(nèi)MIMO VLC系統(tǒng)的空間相關(guān)性，同時(shí)解決了BD算法中因等效信道矩陣經(jīng)奇異值分解(singular value decomposition，SVD)后子信道強(qiáng)弱不均衡的問題，實(shí)現(xiàn)降低多用戶干擾的目的，提高系統(tǒng)傳輸速率。仿真分析驗(yàn)證了該方法的可行性。

2 系統(tǒng)模型

式中：hij為第i個(gè)LED陣列和用戶j的PD之間的信道直流增益，即：

式中：R為第個(gè)LED陣列與用戶的檢測(cè)器間信道的等效直流增益。

經(jīng)第個(gè)用戶的探測(cè)器的光電轉(zhuǎn)換和濾除直流分量后，最后輸出為

第個(gè)用戶輸出端的信噪比(signal to noise ratio，SNR)及系統(tǒng)誤碼率(bit error rate，BER)分別定義為

式中函數(shù)定義為

3 預(yù)編碼和解碼方案

3.1 子流選擇BD算法的預(yù)編碼方案

用戶的預(yù)編碼矩陣為

在接收端，用戶接收到的信號(hào)為

由式(4)和子流選擇BD預(yù)編碼矩陣可得系統(tǒng)和容量為

3.2 子流選擇BD算法的解碼方案

4 系統(tǒng)仿真結(jié)果

圖2 室內(nèi)MIMO VLC系統(tǒng)4′4的空間分布。(a) LED的空間分布；(b) PD的空間分布

圖3 室內(nèi)MIMO VLC系統(tǒng)8′8的空間分布。(a) 8個(gè)LED的空間分布；(b) 8個(gè)PD的空間分布

表1 仿真參數(shù)

取LED=2且PD=2時(shí)，分別求得4′4及8′8信道增益矩陣的條件數(shù)(1)=8.4274，(2)=1.1755E+017，8′8的信道相關(guān)性強(qiáng)于4′4。取LED=1.5且PD=1.5時(shí)，兩種信道矩陣的條件數(shù)分別為(3)=13.8906，(4)=3.2784E+017。取LED=1.0且PD=1.0時(shí)，兩種信道矩陣的條件數(shù)分別為(5)=33.2971，(6)=5.6754E+017。因此，LED、PD間隔的縮小，信道的相關(guān)性增強(qiáng)。

通過在信道空間相關(guān)性的四種取值下，信道容量與SNR的仿真如圖4所示?？梢奓ED、PD取值越小，隨著信道相關(guān)性的增強(qiáng)，信道容量上升的斜率變大。在4′4 MIMO的信道下，BD算法的信道容量受信道相關(guān)性影響小于子流選擇BD算法，但在8′8 MIMO的信道下，相關(guān)性對(duì)兩種算法信道容量的影響區(qū)別不大。

圖5為不同信道相關(guān)性下，系統(tǒng)的SNR與BER關(guān)系曲線?？梢缘玫?，子流選擇BD算法的BER性能較BD來說有4 dB以上增益，這是子流選擇BD算法在奇異值大的子流信道用于數(shù)據(jù)通信而獲得的。同時(shí)，隨著信道相關(guān)性的變強(qiáng)，系統(tǒng)的BER提升。在圖5(a)，8′8 信道的子流選擇BD算法室內(nèi)VLC系統(tǒng)中BER取10-3時(shí)所需SNR約為15.5 dB，而圖5(b)約為19.5 dB，圖5(c)則需要更大的信噪比。因此，可以看出，在8′8的MIMO信道中，不同相關(guān)性的BD算法與子流選擇BD算法的信道容量曲線趨勢(shì)大致相同；但在相同的系統(tǒng)BER性能下，子流選擇BD算法所需SNR的值比BD算法小，且空間相關(guān)性與系統(tǒng)的BER性能呈反比關(guān)系。

圖4 四種空間相關(guān)性下SNR與信道容量的曲線。

(a)LED=2，PD=2；(b)LED=1.5，PD=1.5；(c)LED=1.0，PD=1.0；(d)LED=0.5，PD=0.5

Fig. 4 Curve between SNR and channel capacity under four spatial correlation.

(a)LED=2，PD=2; (b)LED=1.5，PD=1.5; (c)LED=1.0，PD=1.0; (d)LED=0.5，PD=0.5

圖5 不同信道相關(guān)性下SNR與BER的曲線。

(a)LED=2，PD=2；(b)LED=1.5，PD=1.5；(c)LED=1.0，PD=1.0；(d)LED=0.5，PD=0.5

Fig. 5 Curve between SNR and BER under different channel correlation.

(a)LED=2，PD=2; (b)LED=1.5，PD=1.5; (c)LED=1.0，PD=1.0; (d)LED=0.5，PD=0.5

5 結(jié) 論

本文利用子流選擇BD算法，討論了在MU-MIMO室內(nèi)VLC系統(tǒng)中不同的空間相關(guān)性下對(duì)系統(tǒng)信道容量及BER的影響。結(jié)果表明：隨著空間相關(guān)性的不斷增大，信道容量上升的斜率隨之變大，同時(shí)在8′8的MIMO布局中，在不同信道空間相關(guān)性中，BD算法和子流選擇BD算法的信道容量區(qū)別不大；子流選擇BD算法的BER相對(duì)于BD算法可以帶來4 dB以上的增益。

[1] Tran T A, O'Brien D C. Performance metrics for Multi-Input Multi-Output (MIMO) visible light communications[C]//, 2012.

[2] Wang Y G, Zhang M L, Wang Y Q,. Experimental demonstration of visible light communication based on sub-carrier multiplexing of multiple-input-single-output OFDM[C]//, 2012: 745–746.

[3] Zhao L, Zhu T, Liu Z G,. An annular light source layout model for both lighting and communication reliability[J]., 2018, 45(7): 170503.

趙黎, 朱彤, 劉智港, 等. 一種兼顧照明與通信的環(huán)形光源布局模型[J]. 光電工程, 2018, 45(7): 170503.

[4] Ishikawa N, Sugiura S. Maximizing constrained capacity of power-imbalanced optical wireless MIMO communications using spatial modulation[J]., 2015, 33(2): 519–527.

[5] Xue J H, Li Q, Xu S N,. Diversity reception system for indoor LED visible light communication[J]., 2016, 36(9): 15–18, 22.

薛家豪, 李琪, 徐勝男, 等. 室內(nèi)LED可見光通信的分集接收系統(tǒng)[J]. 物理實(shí)驗(yàn), 2016, 36(9): 15–18, 22.

[6] Huang N, Wang X, Chen M. Transceiver Design for MIMO VLC Systems With Integer-Forcing Receivers[J]., 2018, 36(1): 66–77.

[7] Narmanlioglu O, Kizilirmak R C, Miramirkhani F,. Effect of Wiring and Cabling Topologies on the Performance of Distributed MIMO OFDM VLC Systems[J]., 2019: 52743–52754.

[8] Chen J X, Wang Q, Wang Z C. Leakage-based precoding for MU-MIMO VLC systems under optical power constraint[J]., 2017, 382: 348–353.

[9] Hong Y, Chen J, Wang Z X. Multi-user MIMO indoor visible light communication system based on BD precoding algorithm[J]., 2013, 42(11): 1277–1282.

洪陽(yáng), 陳健, 王子雄. 基于BD預(yù)編碼的多用戶MIMO室內(nèi)可見光通信系統(tǒng)[J]. 光子學(xué)報(bào), 2013, 42(11): 1277–1282.

[10] Liu Q F, Xiao S F, Huang K Z,. A SVD-based optical MIMO precoding scheme in indoor visible light communication[J]., 2014, 3(6): 421–426.

[11] Zhu K, Wang L, Hu H Y. Improved BD precoding algorithms for multi-user MIMO systems[J]., 2010, 11(1): 7–10.

祝鍇, 王麗, 胡捍英. 基于BD的改進(jìn)多用戶MIMO預(yù)編碼算法[J]. 信息工程大學(xué)學(xué)報(bào), 2010, 11(1): 7–10.

[12] Ding J P, Huang Z T, Ji Y F. Evolutionary algorithm based power coverage optimization for visible light communications[J]., 2012, 16(4): 439–441.

Analysis of spatial correlation of precoding indoor MIMO visible light communication system

Zhang Ying1,2, Gao Yue1*, Ke Xizheng1,2

1School of Automation and Information Engineering, Xi￠an University of Technology, Xi￠an, Shaanxi 710048, China;2Shaanxi Civil-Military Integration Key Laboratory of Intelligence Collaborative Networks, Xi￠an, Shannxi 710048, China

Substream selected BD algorithm MU-MIMO indoor VLC system model

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.

Citation: Zhang Y, Gao Y, Ke X ZAnalysis of spatial correlation of precoding indoor MIMO visible light communication system[J]., 2020, 47(3): 190666

Analysis of spatial correlation of precoding indoor MIMO visible light communication system

Zhang Ying1,2, Gao Yue1*, Ke Xizheng1,2

1School of Automation and Information Engineering, Xi￠an University of Technology, Xi￠an, Shaanxi 710048, China;2Shaanxi Civil-Military Integration Key Laboratory of Intelligence Collaborative Networks, Xi￠an, Shannxi 710048, China

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.

visible light communication; substream selected; channel correlation; block diagonalization

TN929.1

A

10.12086/oee.2020.190666

: Zhang Y, Gao Y, Ke X Z. Analysis of spatial correlation of precoding indoor MIMO visible light communication system[J]., 2020,47(3): 190666

2019-11-02；

2019-11-29

陜西省重點(diǎn)產(chǎn)業(yè)創(chuàng)新鏈工程(2017ZDCXL-GY-06-01)；陜西省教育廳自然科學(xué)基金(17JK0569)；陜西省教育廳科研計(jì)劃項(xiàng)目(18JK0341)；西安市科技創(chuàng)新引導(dǎo)項(xiàng)目(201805030YD8CG14(12))

張穎(1982-)，女，博士，講師，主要從事可見光通信及Ad Hoc網(wǎng)絡(luò)拓?fù)涞难芯俊-mail：zhangying@xaut.edu.cn

高悅(1993-)，女，碩士研究生，主要從事可見光通信多用戶預(yù)編碼技術(shù)的研究。E-mail：yuegao56510@163.com

張穎，高悅，柯熙政. 預(yù)編碼室內(nèi)MIMO可見光通信系統(tǒng)空間相關(guān)性分析[J]. 光電工程，2020，47(3): 190666

Supported by Key Industry Innovation Chain Project of Shaanxi Province (2017ZDCXL-GY-06-01), Natural Science Foundation of Shaanxi Provincial Department of Education (17JK0569), Scientific Research Project of Education Department of Shaanxi Province (18JK0341), and Xi'an Science and Technology Innovation Guidance Project (201805030YD8CG14(12))

* E-mail: yuegao56510@163.com