arXiv subjects

Meir Feder

Publications and source records attributed to Meir Feder.

70 records · Page 4Linked to original sources

arXiv2012

The Jacobi MIMO Channel

This paper presents a new fading model for MIMO channels, the Jacobi fading model. It asserts that $H$, the transfer matrix which couples the $m_t$ inputs into $m_r$ outputs, is a sub-matrix of an $m\times m$ random (Haar-distributed) unitary matrix. The (squared) singular values of $H$ follow the law of the classical Jacobi ensemble of random matrices; hence the name of the channel. One motivation to define such a channel comes from multimode/multicore optical fiber communication. It turns out that this model can be qualitatively different than the Rayleigh model, leading to interesting practical and theoretical results. This work first evaluates the ergodic capacity of the channel. Then, it considers the non-ergodic case, where it analyzes the outage probability and the diversity-multiplexing tradeoff. In the case where $k=m_t+m_r-m > 0$ it is shown that at least $k$ degrees of freedom are guaranteed not to fade for any channel realization, enabling a zero outage probability or infinite diversity order at the corresponding rates. A simple scheme utilizing (a possibly outdated) channel state feedback is provided, attaining the no-outage guarantee. Finally, noting that as $m$ increases, the Jacobi model approaches the Rayleigh model, the paper discusses the applicability of the model in other communication scenaria.

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arXiv2012

A simpler derivation of the coding theorem

A simple proof for the Shannon coding theorem, using only the Markov inequality, is presented. The technique is useful for didactic purposes, since it does not require many preliminaries and the information density and mutual information follow naturally in the proof. It may also be applicable to situations where typicality is not natural.

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arXiv2012

Communication over Individual Channels -- a general framework

We consider the problem of communicating over a channel for which no mathematical model is specified, and the achievable rates are determined as a function of the channel input and output sequences known a-posteriori, without assuming any a-priori relation between them. In a previous paper we have shown that the empirical mutual information between the input and output sequences is achievable without specifying the channel model, by using feedback and common randomness, and a similar result for real-valued input and output alphabets. In this paper, we present a unifying framework which includes the two previous results as particular cases. We characterize the region of rate functions which are achievable, and show that asymptotically the rate function is equivalent to a conditional distribution of the channel input given the output. We present a scheme that achieves these rates with asymptotically vanishing overheads.

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arXiv2012

Universal Communication over Arbitrarily Varying Channels

We consider the problem of universally communicating over an unknown and arbitrarily varying channel, using feedback. The focus of this paper is on determining the input behavior, and specifically, a prior distribution which is used to randomly generate the codebook. We pose the problem of setting the prior as a sequential universal prediction problem, that attempts to approach a given target rate, which depends on the unknown channel sequence. The main result is that, for a channel comprised of an unknown, arbitrary sequence of memoryless channels, there is a system using feedback and common randomness that asymptotically attains, with high probability, the capacity of the time-averaged channel, universally for every sequence of channels. While no prior knowledge of the channel sequence is assumed, the rate achieved meets or exceeds the traditional arbitrarily varying channel (AVC) capacity for every memoryless AVC defined over the same alphabets, and therefore the system universally attains the random code AVC capacity, without knowledge of the AVC parameters. The system we present combines rateless coding with a universal prediction scheme for the prior. We present rough upper bounds on the rates that can be achieved in this setting and lower bounds for the redundancies.

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arXiv2011

Finite Dimensional Infinite Constellations

In the setting of a Gaussian channel without power constraints, proposed by Poltyrev, the codewords are points in an n-dimensional Euclidean space (an infinite constellation) and the tradeoff between their density and the error probability is considered. The capacity in this setting is the highest achievable normalized log density (NLD) with vanishing error probability. This capacity as well as error exponent bounds for this setting are known. In this work we consider the optimal performance achievable in the fixed blocklength (dimension) regime. We provide two new achievability bounds, and extend the validity of the sphere bound to finite dimensional infinite constellations. We also provide asymptotic analysis of the bounds: When the NLD is fixed, we provide asymptotic expansions for the bounds that are significantly tighter than the previously known error exponent results. When the error probability is fixed, we show that as n grows, the gap to capacity is inversely proportional (up to the first order) to the square-root of n where the proportion constant is given by the inverse Q-function of the allowed error probability, times the square root of 1/2. In an analogy to similar result in channel coding, the dispersion of infinite constellations is 1/2nat^2 per channel use. All our achievability results use lattices and therefore hold for the maximal error probability as well. Connections to the error exponent of the power constrained Gaussian channel and to the volume-to-noise ratio as a figure of merit are discussed. In addition, we demonstrate the tightness of the results numerically and compare to state-of-the-art coding schemes.

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arXiv2010

Parallel Bit Interleaved Coded Modulation

A new variant of bit interleaved coded modulation (BICM) is proposed. In the new scheme, called Parallel BICM, L identical binary codes are used in parallel using a mapper, a newly proposed finite-length interleaver and a binary dither signal. As opposed to previous approaches, the scheme does not rely on any assumptions of an ideal, infinite-length interleaver. Over a memoryless channel, the new scheme is proven to be equivalent to a binary memoryless channel. Therefore the scheme enables one to easily design coded modulation schemes using a simple binary code that was designed for that binary channel. The overall performance of the coded modulation scheme is analytically evaluated based on the performance of the binary code over the binary channel. The new scheme is analyzed from an information theoretic viewpoint, where the capacity, error exponent and channel dispersion are considered. The capacity of the scheme is identical to the BICM capacity. The error exponent of the scheme is numerically compared to a recently proposed mismatched-decoding exponent analysis of BICM.

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arXiv2010

Optimal Feedback Communication via Posterior Matching

In this paper we introduce a fundamental principle for optimal communication over general memoryless channels in the presence of noiseless feedback, termed posterior matching. Using this principle, we devise a (simple, sequential) generic feedback transmission scheme suitable for a large class of memoryless channels and input distributions, achieving any rate below the corresponding mutual information. This provides a unified framework for optimal feedback communication in which the Horstein scheme (BSC) and the Schalkwijk-Kailath scheme (AWGN channel) are special cases. Thus, as a corollary, we prove that the Horstein scheme indeed attains the BSC capacity, settling a longstanding conjecture. We further provide closed form expressions for the error probability of the scheme over a range of rates, and derive the achievable rates in a mismatch setting where the scheme is designed according to the wrong channel model. Several illustrative examples of the posterior matching scheme for specific channels are given, and the corresponding error probability expressions are evaluated. The proof techniques employed utilize novel relations between information rates and contraction properties of iterated function systems.

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arXiv2010

An Achievable Rate for the MIMO Individual Channel

We consider the problem of communicating over a multiple-input multiple-output (MIMO) real valued channel for which no mathematical model is specified, and achievable rates are given as a function of the channel input and output sequences known a-posteriori. This paper extends previous results regarding individual channels by presenting a rate function for the MIMO individual channel, and showing its achievability in a fixed transmission rate communication scenario.

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arXiv2009

Feedback Communication over Individual Channels

We consider the problem of communicating over a channel for which no mathematical model is specified. We present achievable rates as a function of the channel input and output sequences known a-posteriori for discrete and continuous channels. Furthermore we present a rate-adaptive scheme employing feedback which achieves these rates asymptotically without prior knowledge of the channel behavior.

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arXiv2009

Power Adaptive Feedback Communication over an Additive Individual Noise Sequence Channel

We consider a real-valued additive channel with an individual unknown noise sequence. We present a simple sequential communication scheme based on the celebrated Schalkwijk-Kailath scheme, which varies the transmit power according to the power of the sequence, so that asymptotically the relation between the SNR and the rate matches the Gaussian channel capacity 1/2 log(1+SNR)for almost every noise sequence.

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arXiv2009

Communication over Individual Channels

We consider the problem of communicating over a channel for which no mathematical model is specified. We present achievable rates as a function of the channel input and output known a-posteriori for discrete and continuous channels, as well as a rate-adaptive scheme employing feedback which achieves these rates asymptotically without prior knowledge of the channel behavior.

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arXiv2008

Achieving the Empirical Capacity Using Feedback Part I: Memoryless Additive Models

We address the problem of universal communications over an unknown channel with an instantaneous noiseless feedback, and show how rates corresponding to the empirical behavior of the channel can be attained, although no rate can be guaranteed in advance. First, we consider a discrete modulo-additive channel with alphabet $\mathcal{X}$, where the noise sequence $Z^n$ is arbitrary and unknown and may causally depend on the transmitted and received sequences and on the encoder's message, possibly in an adversarial fashion. Although the classical capacity of this channel is zero, we show that rates approaching the empirical capacity $\log|\mathcal{X}|-H_{emp}(Z^n)$ can be universally attained, where $H_{emp}(Z^n)$ is the empirical entropy of $Z^n$. For the more general setting where the channel can map its input to an output in an arbitrary unknown fashion subject only to causality, we model the empirical channel actions as the modulo-addition of a realized noise sequence, and show that the same result applies if common randomness is available. The results are proved constructively, by providing a simple sequential transmission scheme approaching the empirical capacity. In part II of this work we demonstrate how even higher rates can be attained by using more elaborate models for channel actions, and by utilizing possible empirical dependencies in its behavior.

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arXiv2008

Signal Codes

Motivated by signal processing, we present a new class of channel codes, called signal codes, for continuous-alphabet channels. Signal codes are lattice codes whose encoding is done by convolving an integer information sequence with a fixed filter pattern. Decoding is based on the bidirectional sequential stack decoder, which can be implemented efficiently using the heap data structure. Error analysis and simulation results indicate that signal codes can achieve low error rate at approximately 1dB from channel capacity.

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arXiv2007

Low Density Lattice Codes

Low density lattice codes (LDLC) are novel lattice codes that can be decoded efficiently and approach the capacity of the additive white Gaussian noise (AWGN) channel. In LDLC a codeword x is generated directly at the n-dimensional Euclidean space as a linear transformation of a corresponding integer message vector b, i.e., x = Gb, where H, the inverse of G, is restricted to be sparse. The fact that H is sparse is utilized to develop a linear-time iterative decoding scheme which attains, as demonstrated by simulations, good error performance within ~0.5dB from capacity at block length of n = 100,000 symbols. The paper also discusses convergence results and implementation considerations.

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arXiv2006

Bounded expected delay in arithmetic coding

We address the problem of delay in an arithmetic coding system. Due to the nature of the arithmetic coding process, source sequences causing arbitrarily large encoding or decoding delays exist. This phenomena raises the question of just how large is the expected input to output delay in these systems, i.e., once a source sequence has been encoded, what is the expected number of source letters that should be further encoded to allow full decoding of that sequence. In this paper, we derive several new upper bounds on the expected delay for a memoryless source, which improve upon a known bound due to Gallager. The bounds provided are uniform in the sense of being independent of the sequence's history. In addition, we give a sufficient condition for a source to admit a bounded expected delay, which holds for a stationary ergodic Markov source of any order.

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arXiv2006

Universal decoding with an erasure option

Motivated by applications of rateless coding, decision feedback, and ARQ, we study the problem of universal decoding for unknown channels, in the presence of an erasure option. Specifically, we harness the competitive minimax methodology developed in earlier studies, in order to derive a universal version of Forney's classical erasure/list decoder, which in the erasure case, optimally trades off between the probability of erasure and the probability of undetected error. The proposed universal erasure decoder guarantees universal achievability of a certain fraction $ξ$ of the optimum error exponents of these probabilities (in a sense to be made precise in the sequel). A single--letter expression for $ξ$, which depends solely on the coding rate and the threshold, is provided. The example of the binary symmetric channel is studied in full detail, and some conclusions are drawn.

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