Cheng-Chun Chang

Interference Rejection Using Filter-Based Sensor Array in VLC Systems

With the recent development of solid-state lighting (SSL) technologies, visible light communication (VLC) systems using light-emitting diodes (LEDs) has been a promising technology to complement wireless communication. While LEDs offers advantageous properties such as high brightness, lower power consumption, long lifetime, and short transient time for high transmission rates, few researches have been exploited on the receiver side. Conventionally, photoelectric-diodes are implemented to convert optical signals into electronic signals. Since conventional photoelectric-diodes cannot distinguish inputs of different spectra, using conventional photoelectric-diodes have the disadvantage that the system is vulnerable to interference, and that it is hard to achieve wavelength-division-multiplexing (WDM) for light sources of different wavelengths. In this work, a spectrum sensor array is proposed to be implemented on the receiver side to achieve interference rejection. Due to recent advances in semiconductor technologies, spectrum sensors with different spectral transmission properties can be integrated into a chip-scale sensor-array. By proper design of the weightings for individual spectrum sensor, the effective output signal-to-interference ratio (SIR) can be maximized. Following the concept of coherent multi-antenna communication systems, signal fusion algorithms are presented. Our simulation is conducted based on the specification of a prototype filter-array spectrum sensor from nanoLambda. Simulation results demonstrate that robust interference rejection is possible using the low-cost spectrum sensor array.

Spectrum reconstruction for filter-array spectrum sensor from sparse template selection

In recent years, miniature spectrometers have been found to be useful in many applications to resolve spectrum signatures of materials. In this paper, algorithms are proposed to realize a miniature spectrometer using a low-cost filter-array spectrum sensor. Conventionally, the filter-array spectrum sensor can be modeled as an overdetermined problem, and the spectrum can be reconstructed by solving a set of linear equations. In this paper, we instead model the spectrum reconstruction process as an underdetermined problem, and bring up the concept of template-selection by sparse representation. l1 − norm minimization is introduced to achieve a high reconstruction resolution. Both simulation and experimental results show that a superior quality of spectrum reconstruction can be made possible from the presented underdetermined approach.

High-throughput GPU-based LDPC decoding

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Spectrum Reconstruction for On-Chip Spectrum Sensor Array Using a Novel Blind Nonuniformity Correction Method

Filter-array spectrum sensors have been a promising structure that can be used to realize miniature spectrometers or spectrometers on-a-chip. By using multiple spectrum sensors with different spectral responses, the spectrum of a measurement object can be characterized. However, due to the low-cost and miniature design of the input optic interfaces, the intensity of the input light shining onto the imager of the sensor array may not be uniform. This unmodeled input nonuniformity could lead to a severe distortion in the spectrum measurement. Although the input nonuniformity can be alleviated by introducing dedicated input optic interface, we are interested in tackling this issue from an algorithmic perspective because 1) dedicated optics could still render 5%-10% intensity variation, and 2) the cost of computation power in electronics is potentially much lower than the cost of optics nowadays. Accordingly, we propose an iterative blind correction algorithm to solve the input light nonuniformity issue. The algorithm is based on the assumption that variation of input light intensity shall change smoothly, and hence requires no additional information. With the proposed iterative blind correction algorithm, significant improvement on the quality of spectrum reconstruction is obtained in both simulation and experimental studies.

Design of GPU-based platform for LDPC decoder

The needs for reliable and flexible downlink communications incorporated with high volume of satellite images in the ground station have inspired the demands for high performance and flexibility computing in the field of Earth remote sensing. Low-density parity-check (LDPC) codes have had a strong impact on achieving reliable communication links. Finding a fast and reconfigurable developing platform for designing high throughput LDPC decoders has become important. In this paper, a graphic processing unit (GPU) platform is proposed to realize this practical implementation. Experimental results show that the proposed GPU-based platform is compatible to serve as a high-throughput LDPC decoder.

A low-cost mobile device for skin tone measurement using filter array spectrum sensor

Skin tone measurement has a proven market and has many identified and potential applications. In this work, we use an innovative filter array spectrum sensor to achieve a low-cost mobile device for skin-tone and skin-spectrum measurement. The core technology of this spectrum sensor on-a-chip is based on nano-optical filter array which can be integrated onto a regular photo-detector such as CMOS imager. It is expected that the potential low price under mass production would make chip-scale color/spectrum sensing instrument suitable to be integrated into commercial-grade gadgets, while providing professional-grade color/spectrum information. We demonstrated an innovative method for skin tone (skin spectrum) measurement using this innovative filter array spectrum sensor. Experimental results shows spectral aggregated relative error (ARE) = 0.0118 and Δxy = 0.0037 can be achieved by this proposed approach.

Water velocimeter and turbidity-meter using visible light communication modules

Traditionally, water turbidity can be measured based on the absorption or scattering effects. Water flow velocity can be measured based on Doppler frequency shift (DFS) estimation. In this work, we aim to provide a simple, robust, low-cost and accurate method for both measurements by using visible light communication (VLC) modules. Signal processing methods to extract the water turbidity and water flow speed based on the VLC transceiver modules are designed and implemented.

Monitor color sensing using low-cost filter array spectrum sensor

We aim to use 12 channel filter array spectrum sensor for monitors CIE tristimulus color sensing. Although low-cost RGB color sensors are available for monitors color sensing, however their spectral response functions are usually different from the CIE XYZ color matching functions, and hence cannot deliver an accurate color sensing. Alternatively, our proposed filter array spectrum sensor using plasmonic filter technology can supply a low-cost and highly accurate solution. In this work, partial least squares (PLS) and nonlinear iterative partial least squares (NIPLS) are adopted to associate 12 sensor outputs to the CIE XYZ values. Preliminary experimental results show Δxy = 0.0023 has been achieved by this proposed approach.

A sensor array approach for robust wavelength division multiplexing in VLC systems

Visible light communication (VLC) systems have been a promising technology to complement wireless communication. In this work, a spectrum sensor array is proposed to convert optical signals into electronic signals on the receiver side to achieve robust wavelength division multiplexing (WDM). By proper design for the weightings of individual spectrum sensor, the effective output signal to interference ratio (SIR) can be maximized. Both simulation results and experimental results demonstrate that a robust WDM is achievable using the proposed approach.

Spectrum reconstruction from MIMO perspectives for realizing low-cost on-chip spectrometers

In this paper, we initiate to introduce signal detection techniques from multiple-input-multiple-output (MIMO) wireless communication systems to tackle the challenge of spectrum reconstruction for using ultra low-cost filter array spectrum sensors. We introduce the mathematical model of MIMO communication systems and show the similarity to that of the ultra low-cost filter-array spectrum sensors. Spectrum reconstruction from MIMO perspectives is demonstrated in both simulation and real-world experiment.