245 research outputs found
Rewritable storage channels with hidden state
Many storage channels admit reading and rewriting of the content at a given
cost. We consider rewritable channels with a hidden state which models the
unknown characteristics of the memory cell. In addition to mitigating the
effect of the write noise, rewrites can help the write controller obtain a
better estimate of the hidden state. The paper has two contributions. The first
is a lower bound on the capacity of a general rewritable channel with hidden
state. The lower bound is obtained using a coding scheme that combines
Gelfand-Pinsker coding with superposition coding. The rewritable AWGN channel
is discussed as an example. The second contribution is a simple coding scheme
for a rewritable channel where the write noise and hidden state are both
uniformly distributed. It is shown that this scheme is asymptotically optimal
as the number of rewrites gets large
Iterative Programming of Noisy Memory Cells
In this paper, we study a model, which was first presented by Bunte and Lapidoth, that mimics the programming operation of memory cells. Under this paradigm we assume that cells are programmed sequentially and individually. The programming process is modeled as transmission over a channel, while it is possible to read the cell state in order to determine its programming success, and in case of programming failure, to reprogram the cell again. Reprogramming a cell can reduce the bit error rate, however this comes with the price of increasing the overall programming time and thereby affecting the writing speed of the memory. An iterative programming scheme is an algorithm which specifies the number of attempts to program each cell. Given the programming channel and constraints on the average and maximum number of attempts to program a cell, we study programming schemes which maximize the number of bits that can be reliably stored in the memory. We extend the results by Bunte and Lapidoth and study this problem when the programming channel is either the BSC, BEC, or Z channel. For the BSC and the BEC our analysis is also extended for the case where the error probabilities on consecutive writes are not necessarily the same. Lastly, we also study a related model which is motivated by the synthesis process of DNA molecules
Iterative Programming of Noisy Memory Cells
In this paper, we study a model, which was first presented by Bunte and
Lapidoth, that mimics the programming operation of memory cells. Under this
paradigm we assume that cells are programmed sequentially and individually. The
programming process is modeled as transmission over a channel, while it is
possible to read the cell state in order to determine its programming success,
and in case of programming failure, to reprogram the cell again. Reprogramming
a cell can reduce the bit error rate, however this comes with the price of
increasing the overall programming time and thereby affecting the writing speed
of the memory. An iterative programming scheme is an algorithm which specifies
the number of attempts to program each cell. Given the programming channel and
constraints on the average and maximum number of attempts to program a cell, we
study programming schemes which maximize the number of bits that can be
reliably stored in the memory. We extend the results by Bunte and Lapidoth and
study this problem when the programming channel is either the BSC, BEC, or
channel. For the BSC and the BEC our analysis is also extended for the case
where the error probabilities on consecutive writes are not necessarily the
same. Lastly, we also study a related model which is motivated by the synthesis
process of DNA molecules.Comment: 10 pages, 2 figure
Entropy of a bit-shift channel
We consider a simple transformation (coding) of an iid source called a
bit-shift channel. This simple transformation occurs naturally in magnetic or
optical data storage. The resulting process is not Markov of any order. We
discuss methods of computing the entropy of the transformed process, and study
some of its properties.Comment: Published at http://dx.doi.org/10.1214/074921706000000293 in the IMS
Lecture Notes--Monograph Series
(http://www.imstat.org/publications/lecnotes.htm) by the Institute of
Mathematical Statistics (http://www.imstat.org
NSSDC Conference on Mass Storage Systems and Technologies for Space and Earth Science Applications, volume 1
Papers and viewgraphs from the conference are presented. This conference served as a broad forum for the discussion of a number of important issues in the field of mass storage systems. Topics include magnetic disk and tape technologies, optical disks and tape, software storage and file management systems, and experiences with the use of a large, distributed storage system. The technical presentations describe, among other things, integrated mass storage systems that are expected to be available commercially. Also included is a series of presentations from Federal Government organizations and research institutions covering their mass storage requirements for the 1990's
Towards higher-dimensional structured light
Structured light refers to the arbitrarily tailoring of optical fields in all their degrees of freedom (DoFs), from spatial to temporal. Although orbital angular momentum (OAM) is perhaps the most topical example, and celebrating 30 years since its connection to the spatial structure of light, control over other DoFs is slowly gaining traction, promising access to higher-dimensional forms of structured light. Nevertheless, harnessing these new DoFs in quantum and classical states remains challenging, with the toolkit still in its infancy. In this perspective, we discuss methods, challenges, and opportunities for the creation, detection, and control of multiple DoFs for higher-dimensional structured light. We present a roadmap for future development trends, from fundamental research to applications, concentrating on the potential for larger-capacity, higher-security information processing and communication, and beyond
Ultrafast manipulation of mirror domain walls in a charge density wave
Domain walls (DWs) are singularities in an ordered medium that often host
exotic phenomena such as charge ordering, insulator-metal transition, or
superconductivity. The ability to locally write and erase DWs is highly
desirable, as it allows one to design material functionality by patterning DWs
in specific configurations. We demonstrate such capability at room temperature
in a charge density wave (CDW), a macroscopic condensate of electrons and
phonons, in ultrathin 1T-TaS. A single femtosecond light pulse is shown to
locally inject or remove mirror DWs in the CDW condensate, with probabilities
tunable by pulse energy and temperature. Using time-resolved electron
diffraction, we are able to simultaneously track anti-synchronized CDW
amplitude oscillations from both the lattice and the condensate, where
photo-injected DWs lead to a red-shifted frequency. Our demonstration of
reversible DW manipulation may pave new ways for engineering correlated
material systems with light
Iterative Programming of Noisy Memory Cells
In this paper, we study a model, which was first presented by Bunte and Lapidoth, that mimics the programming operation of memory cells. Under this paradigm we assume that cells are programmed sequentially and individually. The programming process is modeled as transmission over a channel, while it is possible to read the cell state in order to determine its programming success, and in case of programming failure, to reprogram the cell again. Reprogramming a cell can reduce the bit error rate, however this comes with the price of increasing the overall programming time and thereby affecting the writing speed of the memory. An iterative programming scheme is an algorithm which specifies the number of attempts to program each cell. Given the programming channel and constraints on the average and maximum number of attempts to program a cell, we study programming schemes which maximize the number of bits that can be reliably stored in the memory. We extend the results by Bunte and Lapidoth and study this problem when the programming channel is either the BSC, BEC, or Z channel. For the BSC and the BEC our analysis is also extended for the case where the error probabilities on consecutive writes are not necessarily the same. Lastly, we also study a related model which is motivated by the synthesis process of DNA molecules
A Tutorial on Coding Methods for DNA-based Molecular Communications and Storage
Exponential increase of data has motivated advances of data storage
technologies. As a promising storage media, DeoxyriboNucleic Acid (DNA) storage
provides a much higher data density and superior durability, compared with
state-of-the-art media. In this paper, we provide a tutorial on DNA storage and
its role in molecular communications. Firstly, we introduce fundamentals of
DNA-based molecular communications and storage (MCS), discussing the basic
process of performing DNA storage in MCS. Furthermore, we provide tutorials on
how conventional coding schemes that are used in wireless communications can be
applied to DNA-based MCS, along with numerical results. Finally, promising
research directions on DNA-based data storage in molecular communications are
introduced and discussed in this paper
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