946 research outputs found
The Dispersion of Superposition Coding for Gaussian Broadcast Channels
International audienceIn this paper, we analyze the performance of superposition coding for Gaussian broadcast channels with finite blocklength. To this end, we adapt two different achievability bounds, the dependence testing and the κβ bounds introduced by Polyanskiy et al. in 2010 to the broadcast setting. The distinction between these bounds lies in fixing either the input or the output distributions of the channel. For the first case of the dependence testing bound, an upper bound on the average error probability of the system is derived whereas for the latter, lower bounds on the maximal code sizes of each user are presented
On Second Order Rate Regions for the Static Scalar Gaussian Broadcast Channel
This paper considers the single antenna, static Gaussian broadcast channel in
the finite blocklength regime. Second order achievable and converse rate
regions are presented. Both a global reliability requirement and per-user
reliability requirements are considered. The two-user case is analyzed in
detail, and generalizations to the -user case are also discussed. The
largest second order achievable region presented here requires both
superposition and rate splitting in the code construction, as opposed to the
(infinite blocklength, first order) capacity region which does not require rate
splitting. Indeed, the finite blocklength penalty causes superposition alone to
under-perform other coding techniques in some parts of the region. In the
two-user case with per-user reliability requirements, the capacity achieving
superposition coding order (with the codeword of the user with the smallest SNR
as cloud center) does not necessarily gives the largest second order region.
Instead, the message of the user with the smallest point-to-point second order
capacity should be encoded in the cloud center in order to obtain the largest
second order region for the proposed scheme
The Dispersion of Nearest-Neighbor Decoding for Additive Non-Gaussian Channels
We study the second-order asymptotics of information transmission using
random Gaussian codebooks and nearest neighbor (NN) decoding over a
power-limited stationary memoryless additive non-Gaussian noise channel. We
show that the dispersion term depends on the non-Gaussian noise only through
its second and fourth moments, thus complementing the capacity result
(Lapidoth, 1996), which depends only on the second moment. Furthermore, we
characterize the second-order asymptotics of point-to-point codes over
-sender interference networks with non-Gaussian additive noise.
Specifically, we assume that each user's codebook is Gaussian and that NN
decoding is employed, i.e., that interference from the unintended users
(Gaussian interfering signals) is treated as noise at each decoder. We show
that while the first-order term in the asymptotic expansion of the maximum
number of messages depends on the power of the interferring codewords only
through their sum, this does not hold for the second-order term.Comment: 12 pages, 3 figures, IEEE Transactions on Information Theor
Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities
This monograph presents a unified treatment of single- and multi-user
problems in Shannon's information theory where we depart from the requirement
that the error probability decays asymptotically in the blocklength. Instead,
the error probabilities for various problems are bounded above by a
non-vanishing constant and the spotlight is shone on achievable coding rates as
functions of the growing blocklengths. This represents the study of asymptotic
estimates with non-vanishing error probabilities.
In Part I, after reviewing the fundamentals of information theory, we discuss
Strassen's seminal result for binary hypothesis testing where the type-I error
probability is non-vanishing and the rate of decay of the type-II error
probability with growing number of independent observations is characterized.
In Part II, we use this basic hypothesis testing result to develop second- and
sometimes, even third-order asymptotic expansions for point-to-point
communication. Finally in Part III, we consider network information theory
problems for which the second-order asymptotics are known. These problems
include some classes of channels with random state, the multiple-encoder
distributed lossless source coding (Slepian-Wolf) problem and special cases of
the Gaussian interference and multiple-access channels. Finally, we discuss
avenues for further research.Comment: Further comments welcom
Combinatorial Channel Signature Modulation for Wireless ad-hoc Networks
In this paper we introduce a novel modulation and multiplexing method which
facilitates highly efficient and simultaneous communication between multiple
terminals in wireless ad-hoc networks. We term this method Combinatorial
Channel Signature Modulation (CCSM). The CCSM method is particularly efficient
in situations where communicating nodes operate in highly time dispersive
environments. This is all achieved with a minimal MAC layer overhead, since all
users are allowed to transmit and receive at the same time/frequency (full
simultaneous duplex). The CCSM method has its roots in sparse modelling and the
receiver is based on compressive sampling techniques. Towards this end, we
develop a new low complexity algorithm termed Group Subspace Pursuit. Our
analysis suggests that CCSM at least doubles the throughput when compared to
the state-of-the art.Comment: 6 pages, 7 figures, to appear in IEEE International Conference on
Communications ICC 201
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