318 research outputs found
BASEBAND RADIO MODEM DESIGN USING GRAPHICS PROCESSING UNITS
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
Design Of Multi-Modulation Baseband Modulator And Demodulator For Software Defined Radio
In contrast to hardware-based radio that only delivers single communication service using particular standard, the software defined radio (SDR) provides a highly
reconfigurable platform to integrate various functions for multi-modulation, multiband and multi-standard wireless communication systems. However, this project is only based on multi-modulation SDR, such as 4-PAM, BPSK, QPSK and 16-QAM.The configurable multi-modulation baseband modulator (MMBM) and demodulator (MMBD) are designed using digital signal processing (DSP) algorithms based on common features shared by single-modulation structures, and then implemented into Xilinx Virtex-4 FPGA. Comparing the real-time and simulation results shows that the timings are equivalent, and the sign and magnitude changes are significant
RAPID CLOCK RECOVERY ALGORITHMS FOR DIGITAL MAGNETIC RECORDING AND DATA COMMUNICATIONS
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN024293 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Enhancing Usability, Security, and Performance in Mobile Computing
We have witnessed the prevalence of smart devices in every aspect of human life. However, the ever-growing smart devices present significant challenges in terms of usability, security, and performance. First, we need to design new interfaces to improve the device usability which has been neglected during the rapid shift from hand-held mobile devices to wearables. Second, we need to protect smart devices with abundant private data against unauthorized users. Last, new applications with compute-intensive tasks demand the integration of emerging mobile backend infrastructure. This dissertation focuses on addressing these challenges. First, we present GlassGesture, a system that improves the usability of Google Glass through a head gesture user interface with gesture recognition and authentication. We accelerate the recognition by employing a novel similarity search scheme, and improve the authentication performance by applying new features of head movements in an ensemble learning method. as a result, GlassGesture achieves 96% gesture recognition accuracy. Furthermore, GlassGesture accepts authorized users in nearly 92% of trials, and rejects attackers in nearly 99% of trials. Next, we investigate the authentication between a smartphone and a paired smartwatch. We design and implement WearLock, a system that utilizes one\u27s smartwatch to unlock one\u27s smartphone via acoustic tones. We build an acoustic modem with sub-channel selection and adaptive modulation, which generates modulated acoustic signals to maximize the unlocking success rate against ambient noise. We leverage the motion similarities of the devices to eliminate unnecessary unlocking. We also offload heavy computation tasks from the smartwatch to the smartphone to shorten response time and save energy. The acoustic modem achieves a low bit error rate (BER) of 8%. Compared to traditional manual personal identification numbers (PINs) entry, WearLock not only automates the unlocking but also speeds it up by at least 18%. Last, we consider low-latency video analytics on mobile devices, leveraging emerging mobile backend infrastructure. We design and implement LAVEA, a system which offloads computation from mobile clients to edge nodes, to accomplish tasks with intensive computation at places closer to users in a timely manner. We formulate an optimization problem for offloading task selection and prioritize offloading requests received at the edge node to minimize the response time. We design and compare various task placement schemes for inter-edge collaboration to further improve the overall response time. Our results show that the client-edge configuration has a speedup ranging from 1.3x to 4x against running solely by the client and 1.2x to 1.7x against the client-cloud configuration
Enabling 5G Technologies
The increasing demand for connectivity and broadband wireless access is leading to the fifth generation (5G) of cellular networks. The overall scope of 5G is greater in client width and diversity than in previous generations, requiring substantial changes to network topologies and air interfaces. This divergence from existing network designs is prompting a massive growth in research, with the U.S. government alone investing $400 million in advanced wireless technologies. 5G is projected to enable the connectivity of 20 billion devices by 2020, and dominate such areas as vehicular networking and the Internet of Things. However, many challenges exist to enable large scale deployment and general adoption of the cellular industries. In this dissertation, we propose three new additions to the literature to further the progression 5G development. These additions approach 5G from top down and bottom up perspectives considering interference modeling and physical layer prototyping. Heterogeneous deployments are considered from a purely analytical perspective, modeling co-channel interference between and among both macrocell and femtocell tiers. We further enhance these models with parameterized directional antennas and integrate them into a novel mixed point process study of the network. At the air interface, we examine Software-Defined Radio (SDR) development of physical link level simulations. First, we introduce a new algorithm acceleration framework for MATLAB, enabling real-time and concurrent applications. Extensible beyond SDR alone, this dataflow framework can provide application speedup for stream-based or data dependent processing. Furthermore, using SDRs we develop a localization testbed for dense deployments of 5G smallcells. Providing real-time tracking of targets using foundational direction of arrival estimation techniques, including a new OFDM based correlation implementation
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