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This paper considers the memoryless input-constrained binary erasure channel (BEC). The channel input constraint is the $(d,\infty)$-runlength limited (RLL) constraint, which mandates that any pair of successive $1$s in the input sequence…

Information Theory · Computer Science 2022-04-15 V. Arvind Rameshwar , Navin Kashyap

The input-constrained erasure channel with feedback is considered, where the binary input sequence contains no consecutive ones, i.e., it satisfies the $(1,\infty)$-RLL constraint. We derive the capacity for this setting, which can be…

Information Theory · Computer Science 2015-03-12 Oron Sabag , Haim H. Permuter , Navin Kashyap

The input-constrained binary erasure channel (BEC) with strictly causal feedback is studied. The channel input sequence must satisfy the $(0,k)$-runlength limited (RLL) constraint, i.e., no more than $k$ consecutive `$0$'s are allowed. The…

Information Theory · Computer Science 2017-12-08 Ori Peled , Oron Sabag , Haim H. Permuter

We propose two coding schemes for the two-receiver discrete memoryless broadcast channel (BC) with rate-limited feedback from one or both receivers. They improve over the nofeedback capacity region for a large class of channels, including…

Information Theory · Computer Science 2016-02-19 Youlong Wu , Michèle Wigger

Existing fixed-length feedback communication schemes are either specialized to particular channels (Schalkwijk--Kailath, Horstein), or apply to general channels but either have high coding complexity (block feedback schemes) or are…

Information Theory · Computer Science 2016-09-08 Cheuk Ting Li , Abbas El Gamal

We study finite alphabet channels with Unit Memory on the previous Channel Outputs called UMCO channels. We identify necessary and sufficient conditions, to test whether the capacity achieving channel input distributions with feedback are…

Information Theory · Computer Science 2017-01-05 Christos K. Kourtellaris , Charalambos D. Charalambous , Ioannis Tzortzis

In this paper, we consider the problem of variable-length coding over the class of memoryless binary asymmetric channels (BACs) with noiseless feedback, including the binary symmetric channel (BSC) as a special case. In 2012, Naghshvar et…

Information Theory · Computer Science 2021-12-01 Hengjie Yang , Minghao Pan , Amaael Antonini , Richard D. Wesel

The theory of multiple-input multiple-output (MIMO) technology has been well-developed to increase fading channel capacity over single-input single-output (SISO) systems. This capacity gain can often be leveraged by utilizing channel state…

Information Theory · Computer Science 2008-02-25 Il Han Kim , David J. Love

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…

Information Theory · Computer Science 2010-08-11 Ofer Shayevitz , Meir Feder

The Ising channel, which was introduced in 1990, is a channel with memory that models Inter-Symbol interference. In this paper we consider the Ising channel with feedback and find the capacity of the channel together with a…

Information Theory · Computer Science 2015-03-20 Ohad Elishco , Haim Permuter

We consider a unit memory channel, called Binary State Symmetric Channel (BSSC), in which the channel state is the modulo2 addition of the current channel input and the previous channel output. We derive closed form expressions for the…

Information Theory · Computer Science 2015-07-03 Christos K. Kourtellaris , Charalambos D. Charalambous

We address the problem of correcting a single error in an arbitrary discrete memoryless channel with error-free instantaneous feedback. For the case of a one-time feedback, we propose a method for constructing optimal transmission…

Information Theory · Computer Science 2023-01-06 Ilya Vorobyev , Alexey Lebedev , Vladimir Lebedev , Christian Deppe

We propose a new method to compute the feedback capacity of unifilar finite state channels (FSCs) with memory using reinforcement learning (RL). The feedback capacity was previously estimated using its formulation as a Markov decision…

Information Theory · Computer Science 2020-08-19 Ziv Aharoni , Oron Sabag , Haim Henri Permuter

This paper investigates the secrecy capacity of the binary beampointing (BBP) channel with block memory and feedback, a simplified yet insightful model for millimeter-wave (mmWave) systems with beamformed transmissions and backscatter…

Information Theory · Computer Science 2025-08-29 Siyao Li , Mingzhe Chen , Shuangyang Li , Giuseppe Caire

The paper considers the input-constrained binary erasure channel (BEC) with causal, noiseless feedback. The channel input sequence respects the $(d,\infty)$-runlength limited (RLL) constraint, i.e., any pair of successive $1$s must be…

Information Theory · Computer Science 2021-02-19 V. Arvind Rameshwar , Navin Kashyap

Finding a computable expression for the feedback capacity of channels with colored Gaussian, additive noise is a long standing open problem. In this paper, we solve this problem in the scenario where the channel has multiple inputs and…

Information Theory · Computer Science 2023-01-20 Oron Sabag , Victoria Kostina , Babak Hassibi

We propose two coding schemes for discrete memoryless broadcast channels (DMBCs) with rate-limited feedback from only one receiver. For any positive feedback rate and for the class of strictly less-noisy DMBCs, our schemes strictly improve…

Information Theory · Computer Science 2013-07-23 Youlong Wu , Michèle Wigger

We consider finite state channels where the state of the channel is its previous output. We refer to these as POST (Previous Output is the STate) channels. We first focus on POST($\alpha$) channels. These channels have binary inputs and…

Information Theory · Computer Science 2013-09-24 Haim H. Permuter , Himanshu Asnani , Tsachy Weissman

For information transmission a binary symmetric channel is used. There is also another noisy binary symmetric channel (feedback channel), and the transmitter observes without delay all the outputs of the forward channel via that feedback…

Information Theory · Computer Science 2010-11-10 M. V. Burnashev , H. Yamamoto

In this paper, we propose a novel method to compute the feedback capacity of channels with memory using reinforcement learning (RL). In RL, one seeks to maximize cumulative rewards collected in a sequential decision-making environment. This…

Information Theory · Computer Science 2020-01-28 Ziv Aharoni , Oron Sabag , Haim Henry Permuter
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