A. James Clark School of Engineering

Permanent URI for this communityhttp://hdl.handle.net/1903/1654

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Subject: search.filters.subject.synchronization

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    BASEBAND RADIO MODEM DESIGN USING GRAPHICS PROCESSING UNITS
    (2015) KIM, SCOTT C.; Bhattacharyya, Shuvra S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    A modern radio or wireless communications transceiver is programmed via software and firmware to change its functionalities at the baseband. However, the actual implementation of the radio circuits relies on dedicated hardware, and the design and implementation of such devices are time consuming and challenging. Due to the need for real-time operation, dedicated hardware is preferred in order to meet stringent requirements on throughput and latency. With increasing need for higher throughput and shorter latency, while supporting increasing bandwidth across a fragmented spectrum, dedicated subsystems are developed in order to service individual frequency bands and specifications. Such a dedicated-hardware-intensive approach leads to high resource costs, including costs due to multiple instantiations of mixers, filters, and samplers. Such increases in hardware requirements in turn increases device size, power consumption, weight, and financial cost. If it can meet the required real-time constraints, a more flexible and reconfigurable design approach, such as a software-based solution, is often more desirable over a dedicated hardware solution. However, significant challenges must be overcome in order to meet constraints on throughput and latency while servicing different frequency bands and bandwidths. Graphics processing unit (GPU) technology provides a promising class of platforms for addressing these challenges. GPUs, which were originally designed for rendering images and video sequences, have been adapted as general purpose high-throughput computation engines for a wide variety of application areas beyond their original target domains. Linear algebra and signal processing acceleration are examples of such application areas. In this thesis, we apply GPUs as software-based, baseband radios and demonstrate novel, software-based implementations of key subsystems in modern wireless transceivers. In our work, we develop novel implementation techniques that allow communication system designers to use GPUs as accelerators for baseband processing functions, including real-time filtering and signal transformations. More specifically, we apply GPUs to accelerate several computationally-intensive, frontend radio subsystems, including filtering, signal mixing, sample rate conversion, and synchronization. These are critical subsystems that must operate in real-time to reliably receive waveforms. The contributions of this thesis can be broadly organized into 3 major areas: (1) channelization, (2) arbitrary resampling, and (3) synchronization. 1. Channelization: a wideband signal is shared between different users and channels, and a channelizer is used to separate the components of the shared signal in the different channels. A channelizer is often used as a pre-processing step in selecting a specific channel-of-interest. A typical channelization process involves signal conversion, resampling, and filtering to reject adjacent channels. We investigate GPU acceleration for a particularly efficient form of channelizer called a polyphase filterbank channelizer, and demonstrate a real-time implementation of our novel channelizer design. 2. Arbitrary resampling: following a channelization process, a signal is often resampled to at least twice the data rate in order to further condition the signal. Since different communication standards require different resampling ratios, it is desirable for a resampling subsystem to support a variety of different ratios. We investigate optimized, GPU-based methods for resampling using polyphase filter structures that are mapped efficiently into GPU hardware. We investigate these GPU implementation techniques in the context of interpolation (integer-factor increases in sampling rate), decimation (integer-factor decreases in sampling rate), and rational resampling. Finally, we demonstrate an efficient implementation of arbitrary resampling using GPUs. This implementation exploits specialized hardware units within the GPU to enable efficient and accurate resampling processes involving arbitrary changes in sample rate. 3. Synchronization: incoming signals in a wireless communications transceiver must be synchronized in order to recover the transmitted data properly from complex channel effects such as thermal noise, fading, and multipath propagation. We investigate timing recovery in GPUs to accelerate the most computationally intensive part of the synchronization process, and correctly align the incoming data symbols in the receiver. Furthermore, we implement fully-parallel timing error detection to accelerate maximum likelihood estimation.
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    Power Minimization in QoS Sensitive Systems
    (IEEE, 2004-06) Wong, Jennifer L; Qu, Gang; Potkonjak, Miodrag
    The majority of modern multimedia and mobile systems have two common denominators: quality-of-service (QoS) requirements, such as latency and synchronization, and strict energy constraints. However, until now no synthesis techniques have been proposed for the design and efficient use of such systems.We have two main objectives: conceptual and synthesis. The conceptual objective is to develop a generic practical technique for the automatic development of online adaptive algorithms from efficient off-line algorithms using statistical techniques. The synthesis objective is to introduce the first design technique for QoS low-power synthesis. We introduce a system of provablyoptimal techniques that minimize energy consumption of streamoriented applications under two main QoS metrics: latency and synchronization. Specifically, we study how multiple voltages can be used to simultaneously satisfy hardware constraints and minimize power consumption while preserving the requested level of QoS. The purpose of the off-line algorithm is threefold. First, it is used as input to statistical software which is used to identify important and relevant parameters of the processes. Second, the algorithm provides buffer occupancy rate indicators. Lastly, it provides a way to combine buffer occupancy and QoS metrics to form a fast and efficient online algorithm. The effectiveness of the algorithms is demonstrated on a number of standard multimedia benchmarks.