Adaptive M-PAM for Multiuser MISO Indoor VLC Systems

In multiuser multiple input single output (MISO) visible light communication (VLC) systems using LEDs with limited rise-times, it is essential to find effective M-ary modulation schemes to increase the bit rate. In this paper, we propose an adaptive M-ary pulse amplitude modulation (M- PAM) algorithm to support multiple users. The proposed algorithm can adjust the modulation constellation size for each user to maximize the bit rate under different channel environments such as shadowing, light dimming, and the impact of multiple access interference. In our MISO approach, multiple LED lamps coordinate to provide users with maximum data rates. We compare optical code division multiplexing access (OCDMA) using our adaptive M-PAM with time division multiplexing access (TDMA). The OCDMA technique can offer a higher bit rate when the number of users is larger than the length of the OCDMA code.

[1]  Jae Kyun Kwon,et al.  Capacity Analysis of M-PAM Inverse Source Coding in Visible Light Communications , 2012, Journal of Lightwave Technology.

[2]  Qi Wang,et al.  Multiuser MIMO-OFDM for Visible Light Communications , 2015, IEEE Photonics Journal.

[3]  Harald Haas,et al.  Space division multiple access in visible light communications , 2015, 2015 IEEE International Conference on Communications (ICC).

[4]  Mohammad Noshad,et al.  Multiuser MISO indoor visible light communications , 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

[5]  K. Motoshima,et al.  Forward error correction based on block turbo code with 3-bit soft decision for 10-Gb/s optical communication systems , 2004, IEEE Journal of Selected Topics in Quantum Electronics.

[6]  Harald Haas,et al.  Indoor MIMO Optical Wireless Communication Using Spatial Modulation , 2010, 2010 IEEE International Conference on Communications.

[7]  Huaping Liu,et al.  Adaptive Modulation Schemes for Visible Light Communications , 2015, Journal of Lightwave Technology.

[8]  Maite Brandt-Pearce,et al.  Distributed Power Allocation for Multiuser MISO Indoor Visible Light Communications , 2014, GLOBECOM 2014.

[9]  S. Randel,et al.  Broadband Information Broadcasting Using LED-Based Interior Lighting , 2008, Journal of Lightwave Technology.

[10]  Mohammad Noshad,et al.  Application of Expurgated PPM to Indoor Visible Light Communications—Part I: Single-User Systems , 2013, Journal of Lightwave Technology.

[11]  Francisco Delgado,et al.  Ethernet-OCDMA system for multi-user visible light communications , 2012 .

[12]  Yu-Chee Tseng,et al.  A Framework for Simultaneous Message Broadcasting Using CDMA-Based Visible Light Communications , 2015, IEEE Sensors Journal.

[13]  Yaqin Zhao,et al.  M-ary Variable Period Modulation for Indoor Visible Light Communication System , 2013, IEEE Communications Letters.

[14]  Joseph M. Kahn,et al.  Wireless Infrared Communications , 1994 .

[15]  H. Haas,et al.  A 3-Gb/s Single-LED OFDM-Based Wireless VLC Link Using a Gallium Nitride $\mu{\rm LED}$ , 2014, IEEE Photonics Technology Letters.

[16]  Zabih Ghassemlooy,et al.  Optical Wireless Communications: System and Channel Modelling with MATLAB® , 2012 .

[17]  Weiwei Hu,et al.  Experimental demonstration of femtocell visible light communication system employing code division multiple access , 2015, 2015 Optical Fiber Communications Conference and Exhibition (OFC).

[18]  Jiaheng Wang,et al.  Multiuser MISO Transceiver Design for Indoor Downlink Visible Light Communication Under Per-LED Optical Power Constraints , 2015, IEEE Photonics Journal.

[19]  Harald Haas,et al.  Indoor optical wireless communication: potential and state-of-the-art , 2011, IEEE Communications Magazine.

[20]  Maite Brandt-Pearce,et al.  Multiuser multidetector indoor visible light communication system , 2015, 2015 Opto-Electronics and Communications Conference (OECC).

[21]  Mauro Biagi,et al.  Trace-Orthogonal PPM-Space Time Block Coding Under Rate Constraints for Visible Light Communication , 2015, Journal of Lightwave Technology.

[22]  Anja Feldmann,et al.  Understanding Signal-Based Speech Quality Prediction in Future Mobile Communications , 2010, 2010 IEEE International Conference on Communications.