428 research outputs found
Symmetric Disjunctive List-Decoding Codes
A binary code is said to be a disjunctive list-decoding -code (LD
-code), , , if the code is identified by the incidence
matrix of a family of finite sets in which the union (or disjunctive sum) of
any sets can cover not more than other sets of the family. In this
paper, we consider a similar class of binary codes which are based on a {\em
symmetric disjunctive sum} (SDS) of binary symbols. By definition, the
symmetric disjunctive sum (SDS) takes values from the ternary alphabet , where the symbol~ denotes "erasure". Namely: SDS is equal to ()
if all its binary symbols are equal to (), otherwise SDS is equal
to~. List decoding codes for symmetric disjunctive sum are said to be {\em
symmetric disjunctive list-decoding -codes} (SLD -codes). In the
given paper, we remind some applications of SLD -codes which motivate the
concept of symmetric disjunctive sum. We refine the known relations between
parameters of LD -codes and SLD -codes. For the ensemble of binary
constant-weight codes we develop a random coding method to obtain lower bounds
on the rate of these codes. Our lower bounds improve the known random coding
bounds obtained up to now using the ensemble with independent symbols of
codewords.Comment: 18 pages, 1 figure, 1 table, conference pape
Applications of Coding Theory to Massive Multiple Access and Big Data Problems
The broad theme of this dissertation is design of schemes that admit iterative algorithms
with low computational complexity to some new problems arising in massive
multiple access and big data. Although bipartite Tanner graphs and low-complexity
iterative algorithms such as peeling and message passing decoders are very popular
in the channel coding literature they are not as widely used in the respective areas
of study and this dissertation serves as an important step in that direction to bridge
that gap. The contributions of this dissertation can be categorized into the following
three parts.
In the first part of this dissertation, a timely and interesting multiple access
problem for a massive number of uncoordinated devices is considered wherein the
base station is interested only in recovering the list of messages without regard to the
identity of the respective sources. A coding scheme with polynomial encoding and
decoding complexities is proposed for this problem, the two main features of which
are (i) design of a close-to-optimal coding scheme for the T-user Gaussian multiple
access channel and (ii) successive interference cancellation decoder. The proposed
coding scheme not only improves on the performance of the previously best known
coding scheme by ≈ 13 dB but is only ≈ 6 dB away from the random Gaussian
coding information rate.
In the second part construction-D lattices are constructed where the underlying
linear codes are nested binary spatially-coupled low-density parity-check codes (SCLDPC)
codes with uniform left and right degrees. It is shown that the proposed
lattices achieve the Poltyrev limit under multistage belief propagation decoding.
Leveraging this result lattice codes constructed from these lattices are applied to the
three user symmetric interference channel. For channel gains within 0.39 dB from
the very strong interference regime, the proposed lattice coding scheme with the
iterative belief propagation decoder, for target error rates of ≈ 10^-5, is only 2:6 dB
away the Shannon limit.
The third part focuses on support recovery in compressed sensing and the nonadaptive
group testing (GT) problems. Prior to this work, sensing schemes based on
left-regular sparse bipartite graphs and iterative recovery algorithms based on peeling
decoder were proposed for the above problems. These schemes require O(K logN)
and Ω(K logK logN) measurements respectively to recover the sparse signal with
high probability (w.h.p), where N, K denote the dimension and sparsity of the signal
respectively (K (double backward arrow) N). Also the number of measurements required to recover
at least (1 - €) fraction of defective items w.h.p (approximate GT) is shown to be
cv€_K logN/K. In this dissertation, instead of the left-regular bipartite graphs, left-and-
right regular bipartite graph based sensing schemes are analyzed. It is shown
that this design strategy enables to achieve superior and sharper results. For the
support recovery problem, the number of measurements is reduced to the optimal
lower bound of
Ω (K log N/K). Similarly for the approximate GT, proposed scheme
only requires c€_K log N/
K measurements. For the probabilistic GT, proposed scheme
requires (K logK log vN/
K) measurements which is only log K factor away from the
best known lower bound of Ω (K log N/
K). Apart from the asymptotic regime, the proposed
schemes also demonstrate significant improvement in the required number of
measurements for finite values of K, N
Applications of Coding Theory to Massive Multiple Access and Big Data Problems
The broad theme of this dissertation is design of schemes that admit iterative algorithms
with low computational complexity to some new problems arising in massive
multiple access and big data. Although bipartite Tanner graphs and low-complexity
iterative algorithms such as peeling and message passing decoders are very popular
in the channel coding literature they are not as widely used in the respective areas
of study and this dissertation serves as an important step in that direction to bridge
that gap. The contributions of this dissertation can be categorized into the following
three parts.
In the first part of this dissertation, a timely and interesting multiple access
problem for a massive number of uncoordinated devices is considered wherein the
base station is interested only in recovering the list of messages without regard to the
identity of the respective sources. A coding scheme with polynomial encoding and
decoding complexities is proposed for this problem, the two main features of which
are (i) design of a close-to-optimal coding scheme for the T-user Gaussian multiple
access channel and (ii) successive interference cancellation decoder. The proposed
coding scheme not only improves on the performance of the previously best known
coding scheme by ≈ 13 dB but is only ≈ 6 dB away from the random Gaussian
coding information rate.
In the second part construction-D lattices are constructed where the underlying
linear codes are nested binary spatially-coupled low-density parity-check codes (SCLDPC)
codes with uniform left and right degrees. It is shown that the proposed
lattices achieve the Poltyrev limit under multistage belief propagation decoding.
Leveraging this result lattice codes constructed from these lattices are applied to the
three user symmetric interference channel. For channel gains within 0.39 dB from
the very strong interference regime, the proposed lattice coding scheme with the
iterative belief propagation decoder, for target error rates of ≈ 10^-5, is only 2:6 dB
away the Shannon limit.
The third part focuses on support recovery in compressed sensing and the nonadaptive
group testing (GT) problems. Prior to this work, sensing schemes based on
left-regular sparse bipartite graphs and iterative recovery algorithms based on peeling
decoder were proposed for the above problems. These schemes require O(K logN)
and Ω(K logK logN) measurements respectively to recover the sparse signal with
high probability (w.h.p), where N, K denote the dimension and sparsity of the signal
respectively (K (double backward arrow) N). Also the number of measurements required to recover
at least (1 - €) fraction of defective items w.h.p (approximate GT) is shown to be
cv€_K logN/K. In this dissertation, instead of the left-regular bipartite graphs, left-and-
right regular bipartite graph based sensing schemes are analyzed. It is shown
that this design strategy enables to achieve superior and sharper results. For the
support recovery problem, the number of measurements is reduced to the optimal
lower bound of
Ω (K log N/K). Similarly for the approximate GT, proposed scheme
only requires c€_K log N/
K measurements. For the probabilistic GT, proposed scheme
requires (K logK log vN/
K) measurements which is only log K factor away from the
best known lower bound of Ω (K log N/
K). Apart from the asymptotic regime, the proposed
schemes also demonstrate significant improvement in the required number of
measurements for finite values of K, N
Code design and analysis for multiple access communications
This thesis explores various coding aspects of multiple access communications, mainly for spread spectrum multiaccess(SSMA) communications and collaborative coding multiaccess(CCMA) communications. Both the SSMA and CCMA techniques permit efficient simultaneous transmission by several users sharing a common channel, without subdivision in time or frequency. The general principle behind these two multiaccess schemes is that one can find sets of signals (codes) which can be combined together to form a composite signal; on reception, the individual signals in the set can each be recovered from the composite signal. For the CCMA scheme, the isolation between users is based on the code structure; for the SSMA scheme, on the other hand, the isolation between users is based on the autocorrelation functions(ACFs) and crosscorrelation functions (CCFs) of the code sequences. It is clear that, in either case, the code design is the key to the system design.For the CCMA system with a multiaccess binary adder channel, a class of superimposed codes is analyzed. It is proved that every constant weight code of weight w and maximal correlation λ corresponds to a subclass of disjunctive codes of order T 3, the out-of-phase ACFs and CCFs of the codes are constant and equal to √L. In addition, all codes of the same length are mutually orthogonal.2. Maximal length sequences (m-sequences) over Gaussian integers, suitable for use with QAM modulation, are considered. Two sub-classes of m-sequences with quasi-perfect periodic autocorrelations are obtained. The CCFs between the decimated m-sequences are studied. By applying a simple operation, it is shown that some m-sequences over rational and Gaussian integers can be transformed into perfect sequences with impulsive ACFs.3. Frank codes and Chu codes have perfect periodic ACFs and optimum periodic CCFs. In addition, it is shown that they also have very favourable nonperiodic ACFs; some new results concerning the behaviour of the nonperiodic ACFs are derived. Further, it is proved that the sets of combinedFrank/Chu codes, which contain a larger number of codes than either of the two constituent sets, also have very good periodic CCFs. Based on Frank codes and Chu codes, two interesting classes of real-valued codes with good correlation properties are defined. It is shown that these codes have periodic complementary properties and good periodic and nonperiodic ACF/CCFs.Finally, a hybrid CCMA/SSMA coding scheme is proposed. This new hybrid coding scheme provides a very flexible and powerful multiple accessing capability and allows simple and efficient decoding. Given an SSMA system with K users and a CCMA system with N users, where at most T users are active at any time, then the hybrid system will have K . N users with at most T.K users active at any time. The hybrid CCMA/SSMA coding scheme is superior to the individual CCMA system or SSMA system in terms of information rate, number of users, decoding complexity and external interference rejection capability
Code design and analysis for multiple access communications
This thesis explores various coding aspects of multiple access communications, mainly for spread spectrum multiaccess(SSMA) communications and collaborative coding multiaccess(CCMA) communications. Both the SSMA and CCMA techniques permit efficient simultaneous transmission by several users sharing a common channel, without subdivision in time or frequency. The general principle behind these two multiaccess schemes is that one can find sets of signals (codes) which can be combined together to form a composite signal; on reception, the individual signals in the set can each be recovered from the composite signal. For the CCMA scheme, the isolation between users is based on the code structure; for the SSMA scheme, on the other hand, the isolation between users is based on the autocorrelation functions(ACFs) and crosscorrelation functions (CCFs) of the code sequences. It is clear that, in either case, the code design is the key to the system design.For the CCMA system with a multiaccess binary adder channel, a class of superimposed codes is analyzed. It is proved that every constant weight code of weight w and maximal correlation λ corresponds to a subclass of disjunctive codes of order T 3, the out-of-phase ACFs and CCFs of the codes are constant and equal to √L. In addition, all codes of the same length are mutually orthogonal.2. Maximal length sequences (m-sequences) over Gaussian integers, suitable for use with QAM modulation, are considered. Two sub-classes of m-sequences with quasi-perfect periodic autocorrelations are obtained. The CCFs between the decimated m-sequences are studied. By applying a simple operation, it is shown that some m-sequences over rational and Gaussian integers can be transformed into perfect sequences with impulsive ACFs.3. Frank codes and Chu codes have perfect periodic ACFs and optimum periodic CCFs. In addition, it is shown that they also have very favourable nonperiodic ACFs; some new results concerning the behaviour of the nonperiodic ACFs are derived. Further, it is proved that the sets of combinedFrank/Chu codes, which contain a larger number of codes than either of the two constituent sets, also have very good periodic CCFs. Based on Frank codes and Chu codes, two interesting classes of real-valued codes with good correlation properties are defined. It is shown that these codes have periodic complementary properties and good periodic and nonperiodic ACF/CCFs.Finally, a hybrid CCMA/SSMA coding scheme is proposed. This new hybrid coding scheme provides a very flexible and powerful multiple accessing capability and allows simple and efficient decoding. Given an SSMA system with K users and a CCMA system with N users, where at most T users are active at any time, then the hybrid system will have K . N users with at most T.K users active at any time. The hybrid CCMA/SSMA coding scheme is superior to the individual CCMA system or SSMA system in terms of information rate, number of users, decoding complexity and external interference rejection capability
Near-Optimal Noisy Group Testing via Separate Decoding of Items
The group testing problem consists of determining a small set of defective
items from a larger set of items based on a number of tests, and is relevant in
applications such as medical testing, communication protocols, pattern
matching, and more. In this paper, we revisit an efficient algorithm for noisy
group testing in which each item is decoded separately (Malyutov and Mateev,
1980), and develop novel performance guarantees via an information-theoretic
framework for general noise models. For the special cases of no noise and
symmetric noise, we find that the asymptotic number of tests required for
vanishing error probability is within a factor of the
information-theoretic optimum at low sparsity levels, and that with a small
fraction of allowed incorrectly decoded items, this guarantee extends to all
sublinear sparsity levels. In addition, we provide a converse bound showing
that if one tries to move slightly beyond our low-sparsity achievability
threshold using separate decoding of items and i.i.d. randomized testing, the
average number of items decoded incorrectly approaches that of a trivial
decoder.Comment: Submitted to IEEE Journal of Selected Topics in Signal Processin
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