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OVERVIEW
Our laboratory formulates, examines, and develops algorithmic
solutions to a wide spectrum of problems of fundamental interest
involving the manipulation of signals and information in diverse
settings. Our work is strongly motivated by and connected
with emerging applications and technologies.
In pursuing the design of efficient algorithm structures,
the scope of research within the lab extends from the analysis
of fundamental limits and development of architectural principles,
through to implementation issues and experimental investigations.
Of particular interest are the tradeoffs between performance,
complexity, and robustness.
In our work, we draw on diverse mathematical tools—from
the theory of information, computation, and complexity; statistical
inference and learning, signal processing and systems; coding
and communication; and networks and queuing—in addressing
important new problems that frequently transcend traditional
boundaries between disciplines.
We have many joint
projects and collaborate closely with faculty, staff, and
students in a variety of other labs on campus, including the
Laboratory for Information and Decision Systems, the Microsystems
Technologies Laboratories, and Computer Science and Artificial
Intelligence Laboratory.
Much of our activity over the last few years has centered
around a variety of different types of problems arising naturally
in the context of wireless, sensor, multimedia, and broadband
networks.
CURRENT INTERESTS
Some of the topics of current interest (in no particular order)
include:
- cross-layer design techniques and architectural considerations
for resource-efficient wireless networks
- coding for multiple-element antenna arrays in wireless
networks, and interactions with other layers; advanced antenna
designs
- new classes of source and channel codes, and decoding
algorithms, particularly for new applications
- diversity techniques and interference suppression and
management algorithms for wireless networks
- distributed algorithms and robust architectures for wireless
networks, especially ad-hoc networks and sensor networks
- algorithms and fundamental limits for multimedia security
problems, including digital watermarking, encryption, and
authentication of multimedia content
- algorithms and architectures for multimedia and streaming
media networks
- algorithmic and coding techniques for generating reliable
advanced systems from aggressively scaled devices, circuits,
and microsystems.
- information-theoretic and algorithmic aspects of learning,
inference, and perception; universal algorithms
- sensing and imaging technologies
- information-theoretic and signal processing aspects of
neuroscience, and computational and systems biology
EXAMPLES
OF RECENT RESEARCH INVESTIGATIONS
Some representative recent research investigations are described
below.
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Self-Calibrating Time-Interleaved Analog-to-Digital Converters
Vijay Divi and Gregory W. Wornell
One popular method for achieving very high-speed analog-to-digital conversion is to use several slower speed converters in a round-robin fashion. However, in practice there are gain differences among the constituent converters due to component variation, and the overall sampling is nonuniform due to disparities in converter output path lengths on-chip.
As a result, the effective converter resolution can easily be several bits per sample less than that of the constituent converters. A traditional approach to addressing this problem has been to calibrate the converter by feeding it a training signal and using the output to adjust its parameters. However, this requires taking the converter off-line periodically, which is unacceptable in many applications. In this work, we show, somewhat counterintuitively, that by using more such imperfect converters so that the input is oversampled relative to its Nyquist rate, it is possible to implement accurate calibration on-line in blind manner, i.e., without requiring knowledge of converter input. In particular, we design iterative algorithms for learning the converter parameters on-the-fly, which are subsequently used to perform correction in either a feedback mode, whereby the converter parameters are directly adjusted, or in a feedforward mode, whereby the converter output is digitally resampled. Such blind calibration is an example of a growing trend toward digitally-enhanced analog circuit designs.
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Rateless Coding for Wireless Channels: Efficient ARQ
Uri Erez, Mitchell D. Trott, and Gregory W. Wornell
In wireless networks, there is much variation in the signal-to-noise ratio (SNR) on individual links. As a result, it is common for communication to be preceded by a training phase, whereby the receiver estimates the channel and conveys this channel state information (CSI) back to the transmitter. However, in highly dynamic networks typical of mobile applications, there is often a serious mismatch between the actual and last-measured states of the channel during transmission, which ends up overwhelming the automatic repeat-request (ARQ) mechanism in the network and dramatically reducing throughput relative to what capacity analysis would promise. In this work, we show that a suitable cross-layer architecture can avoid this problem. In particular, we develop a joint physical-layer/link-layer design in the form of a rateless code. In this design, no CSI is required at the transmitter. Rather, a message is encoded into a sequence of incremental redundancy blocks. The receiver attempts decoding after receiving each such block, and when successful informs the transmitter to terminate transmission. We show that a construction based on simple linear combinations of submessages can: i) achieve the (a priori unknown) capacity of the channel; and ii) be decoded with extremely low complexity when the generator matrix is appropriately chosen. The resulting code can be interpreted as a maximally efficient hybrid ARQ scheme.
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Circuit-Aware Codes for Energy-Efficient OFDM Transmission
Everest Huang and Gregory W. Wornell
Orthogonal frequency-division multiplexing (OFDM) is an increasingly attractive transmission format for wireless and wireline communication standards. However, OFDM waveforms traditionally suffer from high peak-to-average power (PAPR) characteristics, so that when used with typical linear RF amplifiers, power consumption is excessive. This work explores the joint design of the transmission waveforms and RF amplifiers, i.e., the design of circuit-aware codes, and code-aware circuits. We show that in low-power applications, by using such an approach it is possible to reduce power consumption by a factor of more than three, which in wireless applications dramatically extends the operating time of mobile devices. The key ingredients of our system are the combination of novel outphasing RF amplifiers—which are are highly power efficient—and magnitude-only information encoding—which is rate-efficient in the low SNR regime of interest. In this system, the transmission phase is adjusted via a suitably designed iterative algorithm to minimize PAPR. |
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Multimedia Compression with
Encoder Side Information
Emin Martinian and Gregory W. Wornell
In many applications, there is a need for digital representations
of various kinds of content. Such content includes,
for example, video, audio, imagery, as well as various
kinds of sensor data. To develop compact representations,
one needs to take into account the semantics of the
content. In particular, the goal is not to enable an
exact
reconstruction of the content, but rather one that is
semantically indistinguishable from original for the
applications of interest. In Shannon's formulation of
the problem, the semantics are captured through a distortion
measure. When such semantic information is
shared between encoder and decoder, the fundamental
rate-distortion tradeoffs are well understood. This
work explores the corresponding tradeoffs when such
semantic information is not universally available.
We show, for example, that when only the decoder has
access to the full semantics, it provides no benefit
and may as well be ignored. By contrast, when only the
encoder has access to the full semantics, in many cases
that is sufficient to do as well as if the decoder had
it too. Moreover, we show that systems in which such
semantic information is measured at the encoder and
shared with the decoder through a side channel —
which is the basis of many perceptual coding systems,
for example — can be particularly inefficient.
As an efficient alternative, we introduce low-complexity
lattice codes in which there is a fixed codebook but
a variable partition to exploit encoder-only side information. |
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Ultralow-Complexity Iterative Interference Cancellation
Albert Chan and Gregory W. Wornell
In many communication applications, the dominant impairment
is interference. This is especially true of wireless environments.
There is typically self-interference due to multipath
propagation. When system bandwidths are large enough,
this takes the form of
intersymbol interference. However, there is also interference
from other users in the next work, as well as various
forms of extra-network interference. The degree to which
such interference can be mitigated through signal processing
within the network strongly
affects the overall capacity. Thus interference-cancellation
algorithms are of considerable interest. However, traditional
low-complexity linear interference cancellation techniques
cannot exploit enough of the structure in the interference
to be effective, while maximum-likelihood (ML) interference
cancellation are the most effective, but have exponential
complexity. We show that in fact, the performance of ML
cancellation can be approached at high SNR with a complexity
that is negligibly higher than the linear techniques.
In
particular, we develop an efficient convergent iterative
algorithm structure that alternates between generating
increasingly reliable symbol decisions and increasingly
reliable interference estimates. Combining such
decoding structures with a precoding technique at the
encoder we refer to as mode-interleaving extends their
effectiveness to a particularly broad range of channels. |
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Efficient
Codes for MIMO Communication Channels
Huan Yao and Gregory W. Wornell
As multiple-element antenna arrays
become an increasingly important ingredient of high-speed
wireless networks, there is a corresponding need for
physical-layer system designs that create fat, reliable
bit pipes from such channels. Recently, the fundamental
tradeoff between throughput and robustness has been
quantified in the form of what is referred to as the
diversity-multiplexing frontier. While it was understood
the sufficiently long and random codes code approach
arbitrary points on this frontier, it was not known
whether all such points are achievable with practical
codes. We show that suitable designed titled-QAM codes,
in which a multidimensional constellation is subjected
to a unitary transformation, can in fact achieve the
full frontier. Moreover, they achieve this frontier
even for the shortest code lengths where random codes
cannot. A key property of this new family of codes has
the property that their minimum determinant difference
is independent of the constellation size (and hence
transmission rate). Such codes can be used in conjunction
with other traditional error-correction codes and appropriately
designed iterative decoding, and are considerably more
efficient than the popular orthogonal space-time block
codes at higher spectral efficiencies. |
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Efficient
Quantization for Sensor Networks,
Stark C. Draper and Gregory W. Wornell
In many peer-to-peer sensor network
architectures, the signal measurements acquired at nodes
are quantized, and the associated bit representations
are propagated through the network to data fusion nodes
where inference is performed. From this perspective,
the quantizer design problem can be viewed as one of
coding for estimation with communication constraints.
A naive approach would have each node design its quantization
without regard for the network structure. However, a
substantially more resource efficient network results
from the quantizer taking into account that the intermediate
nodes propagating these bit representations are receiving
their own measurements as well as bit representations
from other nodes. From an information-theoretic perspective,
this these intermediate nodes have so-called side information
that can be exploited in the code design. We develop
powerful greedy coding algorithms based on this principle,
and show how they achieve or approach fundamental limits
in prototype topologies. From an architectural perspective,
the new algorithm represents the design of a network-aware
application layer for this problem, which our results
establish is substantially more resource-efficient than
a traditional layered architecture. |
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Multimedia
Content Authentication,
Emin Martinian and Gregory W. Wornell
In today's world, we find ourselves
both impressed by and uncomfortable with the ease with
which one can use digital tools to manipulate audio,
video, imagery, and other kinds of multimedia content.
One might reasonably ask whether it is possible in such
a world to make, for example, a photograph that is truly
trustworthy in some precise sense. In this work, examine
this question, develop a meaningful mathematical model
for the problem, and analyze the associated fundamental
performance limits of authentications systems that provide
a security guarantee. We further develop the structure
of systems that approach these limits, and see that
the resulting coding strategies can be viewed as rather
powerful generalizations of traditional digital signatures.
Moreover, we show that such systems can be built from
familiar ingredients put together in some rather new
ways. More generally, our investigation reveals that
such multimedia security problems are inherently highly
interdisciplinary, and that practical solutions require
jointly exploiting concepts from information theory,
coding and communication theory, signal processing and
systems theory, and cryptography and complexity theory. |
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Cooperative
Diversity for Wireless Networks,
J. Nicholas Laneman and Gregory, W. Wornell
In a typical wireless network,
users exploit their available power and bandwidth resources
to communicate their messages to their target destinations
as efficiently as possible, and ignore or avoid the
messages of other transmitting users. However, we show
this selfish strategy is, in fact, not in the collective
interest of the group: through cooperation each individual
user can experience better performance. In particular,
if each user devotes some of its resources to relaying
the transmissions it hears from other users as well
as to sending its own message, each message is received
with higher reliability because it experiences multiple
propagation paths. Indeed, with this protocol, the group
of cooperating users are forming a "virtual"
antenna array, from which there is a substantial spatial
diversity benefit. We show that, in fact, very simple
relaying schemes yield full spatial diversity: each
user's message experiences performance as if it were
sent from a physical antenna array of the same size.
These lead naturally to novel and efficient distributed
space-time codes for networks, which are equally applicable
to cellular and ad-hoc architectures. From an architectural
perspective, such protocols require only a relatively
small violation of the traditional abstraction rules
that impose a separation of the physical, link, and
network layers. |
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Smart
Buffers for Multimedia Content,
Stark C. Draper, Mitchell D. Trott, and Gregory W. Wornell
Buffers find application in a
wide range of contexts, from digital hardware and software
systems to broadband packet-switched networks like the
Internet. Traditionally, such buffers are designed without
regard for the characteristics of the content they will
hold. For example, with a simple first-in/first-out
(FIFO) buffer, if during some interval of time the number
of bits that needs to be stored exceeds the memory resources,
some are simply dropped. When those bits represent some
multimedia content of interest, the dropped bits correspond
to a loss of fidelity. In this work, we examine the
design of a smart buffer that takes into account how
each bit contributes to the fidelity of the content
stored in memory, and develop a buffering algorithm
that optimizes end-to-end fidelity. In particular, we
develop a greedy algorithm is sample-path optimal: regardless
of the pattern of arrivals to and departures from memory,
no other algorithm, greedy or not, can achieve better
performance. This algorithm ensures that most-significant
bits are both stored in memory first and depart memory
first, with the resource allocation managed by an easily
implemented waterpouring strategy. The smart buffer
achieves a given end-to-end fidelity target with considerably
less storage and communication resources than traditional
designs. From a system or network architecture perspective,
the resulting design shows how increasing lower layer
awareness of the application layer in relatively simple
ways can substantially improve resource efficiency. |
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Scheduling
for Multiple Antenna Wireless Transmission,
Michael J. Lopez and Gregory W. Wornell
It is well known that the use
of multiple antennas can enhance the capacity of wireless
links delivering messages to geographically dispersed
receivers. Moreover, in applications where the channel
state information is available at the transmitter, efficient
precoding strategies (based on information embedding
concepts) exist for multiplexing the different messages
to be delivered to different users. In particular, this
precoding performs an interference pre-cancellation
operation that ensures the different target receivers
can ignore interference effects when decoding their
messages. However, in typical networks, the collection
of messages to be transmitted can be quite large, and
a scheduler selects a subset to be multiplexed in any
particular transmission interval. When the scheduler
and multiplexor operate independently, the scheduler
complexity is very low, but the multiplexor can require
substantial complexity. We show that by having the scheduler
make efficient use of a latency window and take into
account the implications of its decisions for multiplexing,
the overall system can be much more efficient. In particular,
the complexity of multiplexing is significantly reduced
while requiring only a small increase in the complexity
of scheduling. In addition to highlighting the role
of delay as a resource, this work is another compelling
illustration of how a modest amount of lower-layer awareness
at the networking layers can substantially improve overall
resource efficiency from a network architecture perspective. |
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Information
Embedding and Digital Watermarking,
Brian Chen and Gregory W. Wornell
In a variety of emerging applications,
there is a need to hide a sequence of bits in some host
signal like a photograph or a radio transmission. Applications
range from digital rights management and copyright notification
and enforcement, to backwards-compatible upgrades to
existing communication infrastructure, broadcasting,
and covert communication. In such problems, there is
an inherent tradeoff between the number of bits embedded,
the robustness with which they are embedded, and the
distortion the embedding incurs on the host signal.
In this research, we show this problem is equivalent
to an information theoretic problem of channel coding
with side information at the encoder, and use the equivalence
to characterize the tradeoff and develop the associated
fundamental limits. We further introduce a practical
and efficient encoding scheme we refer to as quantization
index modulation (QIM), and a distortion-compensation
techniques (DC-QIM), for achieving the fundamental limits.
The key to the effectiveness of QIM is the way it ensures
that the host signal is not a source of interference
at the decoder. Indeed, data hiding systems based on
DC-QIM are orders of magnitude more efficient than the
more familiar data hiding systems based on spread-spectrum
methods, in which there is host signal interference.
This research underscores the importance of careful
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The
"Dirty Paper" Codec Project:
A Real-Time, Capacity-Approaching Information Embedding
System,
Laboratory Partnership with Chinook Communications
The foundations of information
embedding were laid more than twenty years ago with
early information-theoretic work on the problem of channel
coding with side information at the encoder. One of
those early papers was Costa's whimsically titled "Writing
on Dirty Paper". In recent years, four key advances
have made possible the development of practical information
embedding systems. First is the recognition that the
information embedding problem can be cast as a problem
of "writing on dirty paper". Second is the
development of practical code constructions in the form
of distortion-compensated quantization index modulation
(DC-QIM). Third is the development of capacity-approaching
turbo codes with very low complexity iterative decoding
algorithms. And fourth is the maturation of VLSI technology
and the associated development tools. In this project,
all four of these advances are exploited together in
the design of the world's first real-time, capacity-approaching
information embedding system: the "dirty paper"
coder/decoder (codec). This system transparently embeds
a bitstream at 6 Mb/s into an arbitrary analog NTSC
television signal so that it can be reliably transmitted
through, for example, any FCC-compliant cable network.
Such systems could be used to add roughly 300Mb/s additional
downstream capacity to cable infrastructure without
requiring plant upgrades or affecting existing services.
The system operates within a couple of dB of capacity,
and the reference design is complete with analog front
end, 400k gate FPGA codec, full DSP-based software equalization,
and an embedded linux controller. Other emerging applications
of this technology include multi-antenna downlink transmission
in wireless systems. |
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