3,096 research outputs found
Variable-Length Coding with Feedback: Finite-Length Codewords and Periodic Decoding
Theoretical analysis has long indicated that feedback improves the error
exponent but not the capacity of single-user memoryless channels. Recently
Polyanskiy et al. studied the benefit of variable-length feedback with
termination (VLFT) codes in the non-asymptotic regime. In that work,
achievability is based on an infinite length random code and decoding is
attempted at every symbol. The coding rate backoff from capacity due to channel
dispersion is greatly reduced with feedback, allowing capacity to be approached
with surprisingly small expected latency. This paper is mainly concerned with
VLFT codes based on finite-length codes and decoding attempts only at certain
specified decoding times. The penalties of using a finite block-length and
a sequence of specified decoding times are studied. This paper shows that
properly scaling with the expected latency can achieve the same performance
up to constant terms as with . The penalty introduced by periodic
decoding times is a linear term of the interval between decoding times and
hence the performance approaches capacity as the expected latency grows if the
interval between decoding times grows sub-linearly with the expected latency.Comment: 8 pages. A shorten version is submitted to ISIT 201
A Rate-Compatible Sphere-Packing Analysis of Feedback Coding with Limited Retransmissions
Recent work by Polyanskiy et al. and Chen et al. has excited new interest in
using feedback to approach capacity with low latency. Polyanskiy showed that
feedback identifying the first symbol at which decoding is successful allows
capacity to be approached with surprisingly low latency. This paper uses Chen's
rate-compatible sphere-packing (RCSP) analysis to study what happens when
symbols must be transmitted in packets, as with a traditional hybrid ARQ
system, and limited to relatively few (six or fewer) incremental transmissions.
Numerical optimizations find the series of progressively growing cumulative
block lengths that enable RCSP to approach capacity with the minimum possible
latency. RCSP analysis shows that five incremental transmissions are sufficient
to achieve 92% of capacity with an average block length of fewer than 101
symbols on the AWGN channel with SNR of 2.0 dB.
The RCSP analysis provides a decoding error trajectory that specifies the
decoding error rate for each cumulative block length. Though RCSP is an
idealization, an example tail-biting convolutional code matches the RCSP
decoding error trajectory and achieves 91% of capacity with an average block
length of 102 symbols on the AWGN channel with SNR of 2.0 dB. We also show how
RCSP analysis can be used in cases where packets have deadlines associated with
them (leading to an outage probability).Comment: To be published at the 2012 IEEE International Symposium on
Information Theory, Cambridge, MA, USA. Updated to incorporate reviewers'
comments and add new figure
Increasing Flash Memory Lifetime by Dynamic Voltage Allocation for Constant Mutual Information
The read channel in Flash memory systems degrades over time because the
Fowler-Nordheim tunneling used to apply charge to the floating gate eventually
compromises the integrity of the cell because of tunnel oxide degradation.
While degradation is commonly measured in the number of program/erase cycles
experienced by a cell, the degradation is proportional to the number of
electrons forced into the floating gate and later released by the erasing
process. By managing the amount of charge written to the floating gate to
maintain a constant read-channel mutual information, Flash lifetime can be
extended. This paper proposes an overall system approach based on information
theory to extend the lifetime of a flash memory device. Using the instantaneous
storage capacity of a noisy flash memory channel, our approach allocates the
read voltage of flash cell dynamically as it wears out gradually over time. A
practical estimation of the instantaneous capacity is also proposed based on
soft information via multiple reads of the memory cells.Comment: 5 pages. 5 figure
Homoacetogenesis and microbial community composition are shaped by pH and total sulfide concentration
Biological CO2 sequestration through acetogenesis with H-2 as electron donor is a promising technology to reduce greenhouse gas emissions. Today, a major issue is the presence of impurities such as hydrogen sulfide (H2S) in CO2 containing gases, as they are known to inhibit acetogenesis in CO2-based fermentations. However, exact values of toxicity and inhibition are not well-defined. To tackle this uncertainty, a series of toxicity experiments were conducted, with a mixed homoacetogenic culture, total dissolved sulfide concentrations ([TDS]) varied between 0 and 5 mM and pH between 5 and 7. The extent of inhibition was evaluated based on acetate production rates and microbial growth. Maximum acetate production rates of 0.12, 0.09 and 0.04 mM h(-1) were achieved in the controls without sulfide at pH 7, pH 6 and pH 5. The half-maximal inhibitory concentration (IC50qAc) was 0.86, 1.16 and 1.36 mM [TDS] for pH 7, pH 6 and pH 5. At [TDS] above 3.33 mM, acetate production and microbial growth were completely inhibited at all pHs. 16S rRNA gene amplicon sequencing revealed major community composition transitions that could be attributed to both pH and [TDS]. Based on the observed toxicity levels, treatment approaches for incoming industrial CO2 streams can be determined
Feedback Communication Systems with Limitations on Incremental Redundancy
This paper explores feedback systems using incremental redundancy (IR) with
noiseless transmitter confirmation (NTC). For IR-NTC systems based on {\em
finite-length} codes (with blocklength ) and decoding attempts only at {\em
certain specified decoding times}, this paper presents the asymptotic expansion
achieved by random coding, provides rate-compatible sphere-packing (RCSP)
performance approximations, and presents simulation results of tail-biting
convolutional codes.
The information-theoretic analysis shows that values of relatively close
to the expected latency yield the same random-coding achievability expansion as
with . However, the penalty introduced in the expansion by limiting
decoding times is linear in the interval between decoding times. For binary
symmetric channels, the RCSP approximation provides an efficiently-computed
approximation of performance that shows excellent agreement with a family of
rate-compatible, tail-biting convolutional codes in the short-latency regime.
For the additive white Gaussian noise channel, bounded-distance decoding
simplifies the computation of the marginal RCSP approximation and produces
similar results as analysis based on maximum-likelihood decoding for latencies
greater than 200. The efficiency of the marginal RCSP approximation facilitates
optimization of the lengths of incremental transmissions when the number of
incremental transmissions is constrained to be small or the length of the
incremental transmissions is constrained to be uniform after the first
transmission. Finally, an RCSP-based decoding error trajectory is introduced
that provides target error rates for the design of rate-compatible code
families for use in feedback communication systems.Comment: 23 pages, 15 figure
Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model
In this paper we discuss climate model tuning and present an iterative automatic tuning method from the statistical science literature. The method, which we refer to here as iterative refocussing (though also known as history matching), avoids many of the common pitfalls of automatic tuning procedures that are based on optimisation of a cost function; principally the over-tuning of a climate model due to using only partial observations. This avoidance comes by seeking to rule out parameter choices that we are confident could not reproduce the observations, rather than seeking the model that is closest to them (a procedure that risks over-tuning). We comment on the state of climate model tuning and illustrate our approach through 3 waves of iterative refocussing of the NEMO ORCA2 global ocean model run at 2° resolution. We show how at certain depths the anomalies of global mean temperature and salinity in a standard configuration of the model exceeds 10 standard deviations away from observations and show the extent to which this can be alleviated by iterative refocussing without compromising model performance spatially. We show how model improvements can be achieved by simultaneously perturbing multiple parameters, and illustrate the potential of using low resolution ensembles to tune NEMO ORCA configurations at higher resolutions
From Observers to Participants: Joining the Scientific Community
In this essay, we have integrated the voices of our mentors and students to explore 45 years of undergraduate research experiences and their role in shaping our scientific community. In considering our collective experiences, we see undergraduate involvement in research as a rich source of community development, one that has both touched our lives and influenced our teaching
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