5,174 research outputs found
Authentication with Distortion Criteria
In a variety of applications, there is a need to authenticate content that
has experienced legitimate editing in addition to potential tampering attacks.
We develop one formulation of this problem based on a strict notion of
security, and characterize and interpret the associated information-theoretic
performance limits. The results can be viewed as a natural generalization of
classical approaches to traditional authentication. Additional insights into
the structure of such systems and their behavior are obtained by further
specializing the results to Bernoulli and Gaussian cases. The associated
systems are shown to be substantially better in terms of performance and/or
security than commonly advocated approaches based on data hiding and digital
watermarking. Finally, the formulation is extended to obtain efficient layered
authentication system constructions.Comment: 22 pages, 10 figure
Statistical Mechanics of Broadcast Channels Using Low Density Parity Check Codes
We investigate the use of Gallager's low-density parity-check (LDPC) codes in
a broadcast channel, one of the fundamental models in network information
theory. Combining linear codes is a standard technique in practical network
communication schemes and is known to provide better performance than simple
timesharing methods when algebraic codes are used. The statistical physics
based analysis shows that the practical performance of the suggested method,
achieved by employing the belief propagation algorithm, is superior to that of
LDPC based timesharing codes while the best performance, when received
transmissions are optimally decoded, is bounded by the timesharing limit.Comment: 14 pages, 4 figure
Uniformity of Point Samples in Metric Spaces using Gap Ratio
Teramoto et al. defined a new measure of uniformity of point distribution called the \emph{gap ratio} that measures the uniformity of a finite point set sampled from , a bounded subset of . We attempt to generalize the definition of this measure over all metric spaces. While they look at online algorithms minimizing the measure at every instance, wherein the final size of the sampled set may not be known a priori, we look at instances in which the final size is known and we wish to minimize the final gap ratio. We solve optimization related questions about selecting uniform point samples from metric spaces; the uniformity is measured using gap ratio. We give lower bounds for specific as well as general instances, prove hardness results on specific metric spaces, and a general approximation algorithm framework giving different approximation ratios for different metric spaces
Statistical Mechanics of Broadcast Channels Using Low Density Parity Check Codes
We investigate the use of Gallager's low-density parity-check (LDPC) codes in
a broadcast channel, one of the fundamental models in network information
theory. Combining linear codes is a standard technique in practical network
communication schemes and is known to provide better performance than simple
timesharing methods when algebraic codes are used. The statistical physics
based analysis shows that the practical performance of the suggested method,
achieved by employing the belief propagation algorithm, is superior to that of
LDPC based timesharing codes while the best performance, when received
transmissions are optimally decoded, is bounded by the timesharing limit.Comment: 14 pages, 4 figure
Media-Based MIMO: A New Frontier in Wireless Communications
The idea of Media-based Modulation (MBM), is based on embedding information
in the variations of the transmission media (channel state). This is in
contrast to legacy wireless systems where data is embedded in a Radio Frequency
(RF) source prior to the transmit antenna. MBM offers several advantages vs.
legacy systems, including "additivity of information over multiple receive
antennas", and "inherent diversity over a static fading channel". MBM is
particularly suitable for transmitting high data rates using a single transmit
and multiple receive antennas (Single Input-Multiple Output Media-Based
Modulation, or SIMO-MBM). However, complexity issues limit the amount of data
that can be embedded in the channel state using a single transmit unit. To
address this shortcoming, the current article introduces the idea of Layered
Multiple Input-Multiple Output Media-Based Modulation (LMIMO-MBM). Relying on a
layered structure, LMIMO-MBM can significantly reduce both hardware and
algorithmic complexities, as well as the training overhead, vs. SIMO-MBM.
Simulation results show excellent performance in terms of Symbol Error Rate
(SER) vs. Signal-to-Noise Ratio (SNR). For example, a LMIMO-MBM is
capable of transmitting bits of information per (complex) channel-use,
with SER at dB (or SER
at dB). This performance is achieved using a single transmission
and without adding any redundancy for Forward-Error-Correction (FEC). This
means, in addition to its excellent SER vs. energy/rate performance, MBM
relaxes the need for complex FEC structures, and thereby minimizes the
transmission delay. Overall, LMIMO-MBM provides a promising alternative to MIMO
and Massive MIMO for the realization of 5G wireless networks.Comment: 26 pages, 11 figures, additional examples are given to further
explain the idea of Media-Based Modulation. Capacity figure adde
On Achievable Rates for Long-Haul Fiber-Optic Communications
Lower bounds on mutual information (MI) of long-haul optical fiber systems
for hard-decision and soft-decision decoding are studied. Ready-to-use
expressions to calculate the MI are presented. Extensive numerical simulations
are used to quantify how changes in the optical transmitter, receiver, and
channel affect the achievable transmission rates of the system. Special
emphasis is put to the use of different quadrature amplitude modulation
formats, channel spacings, digital back-propagation schemes and probabilistic
shaping. The advantages of using MI over the prevailing -factor as a figure
of merit of coded optical systems are also highlighted.Comment: Hard decision mutual information analysis added, two typos correcte
Efficient Multi-way Theta-Join Processing Using MapReduce
Multi-way Theta-join queries are powerful in describing complex relations and
therefore widely employed in real practices. However, existing solutions from
traditional distributed and parallel databases for multi-way Theta-join queries
cannot be easily extended to fit a shared-nothing distributed computing
paradigm, which is proven to be able to support OLAP applications over immense
data volumes. In this work, we study the problem of efficient processing of
multi-way Theta-join queries using MapReduce from a cost-effective perspective.
Although there have been some works using the (key,value) pair-based
programming model to support join operations, efficient processing of multi-way
Theta-join queries has never been fully explored. The substantial challenge
lies in, given a number of processing units (that can run Map or Reduce tasks),
mapping a multi-way Theta-join query to a number of MapReduce jobs and having
them executed in a well scheduled sequence, such that the total processing time
span is minimized. Our solution mainly includes two parts: 1) cost metrics for
both single MapReduce job and a number of MapReduce jobs executed in a certain
order; 2) the efficient execution of a chain-typed Theta-join with only one
MapReduce job. Comparing with the query evaluation strategy proposed in [23]
and the widely adopted Pig Latin and Hive SQL solutions, our method achieves
significant improvement of the join processing efficiency.Comment: VLDB201
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