1,036 research outputs found
Asymptotic Error Free Partitioning over Noisy Boolean Multiaccess Channels
In this paper, we consider the problem of partitioning active users in a
manner that facilitates multi-access without collision. The setting is of a
noisy, synchronous, Boolean, multi-access channel where active users (out
of a total of users) seek to access. A solution to the partition problem
places each of the users in one of groups (or blocks) such that no two
active nodes are in the same block. We consider a simple, but non-trivial and
illustrative case of active users and study the number of steps used
to solve the partition problem. By random coding and a suboptimal decoding
scheme, we show that for any , where and
are positive constants (independent of ), and can be
arbitrary small, the partition problem can be solved with error probability
, for large . Under the same scheme, we also bound from
the other direction, establishing that, for any ,
the error probability for large ; again and
are constants and can be arbitrarily small. These bounds on the number
of steps are lower than the tight achievable lower-bound in terms of for group testing (in which all active users are identified,
rather than just partitioned). Thus, partitioning may prove to be a more
efficient approach for multi-access than group testing.Comment: This paper was submitted in June 2014 to IEEE Transactions on
Information Theory, and is under review no
Partition Information and its Transmission over Boolean Multi-Access Channels
In this paper, we propose a novel partition reservation system to study the
partition information and its transmission over a noise-free Boolean
multi-access channel. The objective of transmission is not message restoration,
but to partition active users into distinct groups so that they can,
subsequently, transmit their messages without collision. We first calculate (by
mutual information) the amount of information needed for the partitioning
without channel effects, and then propose two different coding schemes to
obtain achievable transmission rates over the channel. The first one is the
brute force method, where the codebook design is based on centralized source
coding; the second method uses random coding where the codebook is generated
randomly and optimal Bayesian decoding is employed to reconstruct the
partition. Both methods shed light on the internal structure of the partition
problem. A novel hypergraph formulation is proposed for the random coding
scheme, which intuitively describes the information in terms of a strong
coloring of a hypergraph induced by a sequence of channel operations and
interactions between active users. An extended Fibonacci structure is found for
a simple, but non-trivial, case with two active users. A comparison between
these methods and group testing is conducted to demonstrate the uniqueness of
our problem.Comment: Submitted to IEEE Transactions on Information Theory, major revisio
Group testing:an information theory perspective
The group testing problem concerns discovering a small number of defective
items within a large population by performing tests on pools of items. A test
is positive if the pool contains at least one defective, and negative if it
contains no defectives. This is a sparse inference problem with a combinatorial
flavour, with applications in medical testing, biology, telecommunications,
information technology, data science, and more. In this monograph, we survey
recent developments in the group testing problem from an information-theoretic
perspective. We cover several related developments: efficient algorithms with
practical storage and computation requirements, achievability bounds for
optimal decoding methods, and algorithm-independent converse bounds. We assess
the theoretical guarantees not only in terms of scaling laws, but also in terms
of the constant factors, leading to the notion of the {\em rate} of group
testing, indicating the amount of information learned per test. Considering
both noiseless and noisy settings, we identify several regimes where existing
algorithms are provably optimal or near-optimal, as well as regimes where there
remains greater potential for improvement. In addition, we survey results
concerning a number of variations on the standard group testing problem,
including partial recovery criteria, adaptive algorithms with a limited number
of stages, constrained test designs, and sublinear-time algorithms.Comment: Survey paper, 140 pages, 19 figures. To be published in Foundations
and Trends in Communications and Information Theor
Statistical Mechanics Analysis of LDPC Coding in MIMO Gaussian Channels
Using analytical methods of statistical mechanics, we analyse the typical
behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with
binary inputs under LDPC network coding and joint decoding. The saddle point
equations for the replica symmetric solution are found in particular
realizations of this channel, including a small and large number of
transmitters and receivers. In particular, we examine the cases of a single
transmitter, a single receiver and the symmetric and asymmetric interference
channels. Both dynamical and thermodynamical transitions from the ferromagnetic
solution of perfect decoding to a non-ferromagnetic solution are identified for
the cases considered, marking the practical and theoretical limits of the
system under the current coding scheme. Numerical results are provided, showing
the typical level of improvement/deterioration achieved with respect to the
single transmitter/receiver result, for the various cases.Comment: 25 pages, 7 figure
Non-Coherent Active Device Identification for Massive Random Access
Massive Machine-Type Communications (mMTC) is a key service category in the
current generation of wireless networks featuring an extremely high density of
energy and resource-limited devices with sparse and sporadic activity patterns.
In order to enable random access in such mMTC networks, base station needs to
identify the active devices while operating within stringent access delay
constraints. In this paper, an energy efficient active device identification
protocol is proposed in which active devices transmit On-Off Keying (OOK)
modulated preambles jointly and base station employs non-coherent energy
detection avoiding channel estimation overheads. The minimum number of
channel-uses required by the active user identification protocol is
characterized in the asymptotic regime of total number of devices when
the number of active devices scales as along with an
achievability scheme relying on the equivalence of activity detection to a
group testing problem. Several practical schemes based on Belief Propagation
(BP) and Combinatorial Orthogonal Matching Pursuit (COMP) are also proposed.
Simulation results show that BP strategies outperform COMP significantly and
can operate close to the theoretical achievability bounds. In a
partial-recovery setting where few misdetections are allowed, BP continues to
perform well
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