Signal processing for LED lighting systems : illumination rendering and sensing

Solid state lighting, employing high brightness light emitting diodes (LEDs), is becoming increasingly widely used. The advantages of LEDs include high radiative efficiency, long lifetime, limited heat generation and superior tolerance to humidity. Another important advantage of LED lighting systems is the ability to create colorful, dynamic and localized lighting effects. This ability is enabled by three features of LED lighting systems: a large number, e.g. hundreds, of spatially distributed LEDs, a wide range, e.g. thousands, of illumination levels per LED through pulse width modulation (PWM) dimming, and the colorful nature of LEDs. These three properties create many degrees of freedom to render appealing lighting effects. Consequently, many new lighting applications are possible, e.g. creating a localized lighting effect that follows the movement of a user to increase energy efficiency. Due to these strong advantages, LEDs will largely replace the conventional lighting sources, such as incandescent and fluorescent lamps, in the years to come. Associated with these advantages, many research challenges emerge in LED lighting systems. In particular, the primary role of such systems, named illumination rendering, is to provide desired illumination effects. A research challenge is thus how to design and configure the system components and parameters for the purpose of illumination rendering. Specifically, each LED, when fully switched on, renders a three dimensional illumination distribution in space. This distribution is characterized by a so-called basic illumination pattern. The total illumination pattern rendered by all the LEDs is a weighted combination of these basic illumination patterns, where the weighting coefficients are the illumination levels of the LEDs. As such, three main system parameters for illumination rendering are the illumination level, basic illumination pattern and spatial location of each LED. The total number of possible target illumination patterns is very large due to the many degrees of freedom in these parameters. Among the numerous possible illumination patterns, a spatially uniform pattern is the most widely used, and is therefore of particular interest in this thesis. With respect to illumination rendering, a mathematical framework is provided in this thesis. In this framework, a mean squared error (MSE) based cost function to measure the performance of illumination rendering is proposed with consideration of human perception properties. All of the three system parameters introduced in the previous paragraph are then studied to minimize the proposed cost function for uniform illumination rendering. First, this thesis proves that the optimum uniformity can be achieved by setting the LED illumination levels to be identical. Secondly, it is found that a weighted combination of Gaussian and raised-cosine functions as the basic illumination pattern yields the best uniformity among the considered basic illumination patterns with identical beam widths. Moreover, with respect to the spatial locations of LEDs, a regular array of LEDs is desirable for the purpose of uniform illumination. Three basic regular grid shapes for an LED array are compared. The results show that significantly better uniformity can be achieved through employing the hexagonal instead of the rectangular and triangular grids, for the identical LED densities. Besides the selection of the system parameters of LED lighting systems, another key research challenge lies in the control of the LEDs in practical application scenarios. Specifically, there has to be a control mechanism for each of the LEDs, e.g. for switching on and off a particular LED, or for adjusting the illumination level of that LED. Due to the large number of LEDs, it is no longer feasible to associate a manual switch to each LED. Instead, an intelligent lighting control mechanism is considered in this thesis. In this mechanism, a sensor is placed at the location where a particular lighting effect is desired. The illumination contribution of every LED is then estimated via sensor signal processing. This estimation process is named illumination sensing. Based on the estimation results, a controller can determine and automatically set the appropriate illumination level of each LED to obtain the desired lighting effect. In practical applications, key requirements on illumination sensing include a high estimation accuracy as well as a short response time. Given that these two requirements are satisfied, the research target is then to accommodate as many LEDs as possible to provide as many degrees of freedom as possible in illumination rendering. Since the light from all the LEDs simply superimposes at the sensor, it is important to distinguish the light signals from different LEDs and measure the individual signal strength. To this end, the light signals of different LEDs must be modulated differently. Due to the role of illumination rendering for LED lighting systems, the modulation method should be compatible to PWM dimming and should not cause any visible flicker. There are two types of possible modulation methods, namely synchronous and asynchronous modulation. In synchronous modulation, different LEDs use a synchronized clock. For this modulation type, a code and time division multiple access approach is studied. In this approach, the light signal of each LED is tagged by a unique combination of an allocated time slot and an orthogonal code such as Walsh-Hadamard code. For the sensor signal processing, least squares and minimum mean square error estimators are applied and their performances are analyzed. The influence of timing errors, including fixed timing offsets and random timing jitter, on the estimation performances is also analyzed in this thesis. Numerical results reveal that the signals from a large number, e.g. thousands, of LEDs can be distinguished and measured simultaneously with adequate accuracy in illumination sensing. In order to avoid the complexity of maintaining synchronism among the spatially distributed LEDs, this thesis also considers a much simpler asynchronous modulation approach based on frequency division multiplexing (FDM). In this approach, all LEDs are operated at different frequencies. A low complexity filter-bank based sensor signal processing method is developed that exploits only the fundamental frequency component of the sensor signal. It is shown that around one hundred LEDs can be supported for the considered system parameters. In many practical lighting applications, however, a significantly larger number of LEDs needs to be supported. To this end, a low complexity successive estimation approach exploiting multiple harmonics is proposed. It is shown that the number of LEDs can be increased by at least five times, compared to the estimation approach based on using only the fundamental harmonic, at the same estimation accuracy. In summary, this thesis provides an initial study of two emerging signal processing applications for LED lighting systems, namely illumination rendering and sensing. Many interesting and important research challenges still remain, such as non-uniform illumination rendering and more advanced asynchronous illumination sensing approaches