Lai-Huei Wang

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Dataflow models are widely used for expressing the functionality of digital signal processing (DSP) applications due to their useful features, such as providing formal mechanisms for description of application functionality, imposing minimal data-dependency constraints in specifications, and exposing task and data level par-allelism effectively. Due to the(More)
LIDE (the DSPCAD Lightweight Dataflow Environment) is a flexible, lightweight design environment that allows designers to experiment with dataflow-based approaches for design and implementation of digital signal processing (DSP) systems. LIDE contains libraries of dataflow graph elements (primitive actors, hierarchical actors, and edges) and utilities that(More)
Cognitive radio networks present challenges at many levels of design, including configuration, control, and cross-layer optimization. To meet requirements of bandwidth, flexibility and reconfigurability, systematic methods to model and analyze cognitive radio designs on signal processing platforms are desired. To help address these challenges, we present in(More)
The OFDM system receiver is well-performed only when the transmitter and the receiver are precisely synchronized. The sampling clock offset causes a symbol-time drift and even introduces inter-carrier and inter-symbol interference (ICI and ISI), which become not negligible in the systems with large OFDM symbol sizes, e.g. in the terrestrial digital video(More)
Multidimensional synchronous dataflow (MDSDF) provides an effective model of computation for a variety of multidimensional DSP systems that have static dataflow structures. In this paper, we develop new methods for optimized implementation of MDSDF graphs on embedded platforms that employ multiple levels of parallelism to enhance performance at different(More)
Cognitive radio networks present challenges at many levels of design including configuration, control, and cross-layer optimization. In this paper, we focus primarily on dataflow representations to enable flexibility and reconfigurability in many of the baseband algorithms. Dataflow modeling will be important to provide a layer of abstraction and will be(More)
Due to the increased complexity of dynamics in modern DSP applications, dataflow-based design methodologies require significant enhancements in modeling and scheduling techniques to provide for efficient and flexible handling of dynamic behavior. In this report, we address this problem through a new framework that is based on integrating two complementary(More)
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