Illumination Sensing in LED Lighting Systems Based on Frequency-Division Multiplexing

Recently, light emitting diode (LED) based illumination systems have attracted considerable research interest. Such systems normally consist of a large number of LEDs. In order to facilitate the control of such high-complexity system, a novel signal processing application, namely illumination sensing, is thus studied. In this paper, the system concept and research challenges of illumination sensing are presented. Thereafter, we investigate a frequency-division multiplexing (FDM) scheme to distinguish the signals from different LEDs, such that we are able to estimate the illuminances of all the LEDs simultaneously. Moreover, a filter bank sensor structure is proposed to study the key properties of the FDM scheme. Conditions on the design of the filter response are imposed for the ideal case without the existence of any frequency inaccuracy, as well as for the case with frequency inaccuracies. The maximum number of LEDs that can be supported for each case is also derived. In particular, it is shown that, among all the other considered functions, the use of the triangular function is able to give a better tradeoff between the number of LEDs that can be supported and the allowable clock inaccuracies within a practical range. Moreover, through numerical investigations, we show that many tens of LEDs can be supported for the considered system parameters. Remark on the low-cost implementations of the proposed sensor structure is also provided.

[1]  Norman C. Beaulieu,et al.  Parametric construction of Nyquist-I pulses , 2004, IEEE Transactions on Communications.

[2]  Jean-Paul M. G. Linnartz,et al.  Communications and Sensing of Illumination Contributions in a Power LED Lighting System , 2008, 2008 IEEE International Conference on Communications.

[3]  Ian Ashdown,et al.  Adapting radio technology to LED feedback systems , 2007, SPIE Optical Engineering + Applications.

[4]  J. O. Scanlan,et al.  Pulses satisfying the Nyquist criterion , 1992 .

[5]  A. E. Iverson,et al.  Mathematical modeling of photoconductor transient response , 1987, IEEE Transactions on Electron Devices.

[6]  U. Bapst,et al.  Wireless in-house data communication via diffuse infrared radiation , 1979, Proceedings of the IEEE.

[7]  D. Wood Optoelectronic Semiconductor Devices , 1994 .

[8]  Chi-Ho Chan,et al.  LED wireless , 2002 .

[9]  Jean-Paul M. G. Linnartz,et al.  Code Division-Based Sensing of Illumination Contributions in Solid-State Lighting Systems , 2009, IEEE Transactions on Signal Processing.

[10]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[11]  W. Guggenbuhl,et al.  Large signal circuit model for LED's used in optical communication , 1981, IEEE Transactions on Electron Devices.

[12]  Masao Nakagawa,et al.  Fundamental analysis for visible-light communication system using LED lights , 2004, IEEE Transactions on Consumer Electronics.

[13]  Robert Bregovic,et al.  Multirate Systems and Filter Banks , 2002 .

[14]  M. Pashley,et al.  Red, green, and blue LEDs for white light illumination , 2002 .

[15]  Petre Stoica,et al.  Spectral Analysis of Signals , 2009 .

[16]  L. Franks,et al.  Further Results on Nyquist's Problem in Pulse Transmission , 1968 .

[17]  Jeffrey B. Carruthers,et al.  Wireless infrared communications , 2003, Proc. IEEE.

[18]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[19]  U. Bapst,et al.  Wireless in-house data communication via diffuse infrared radiation , 1979 .

[20]  Martin Stopford,et al.  Human Factors in Lighting , 2003 .