Muriel Médard

Muriel Médard
Massachusetts Institute of Technology | MIT · Department of Electrical Engineering and Computer Science

Sc.D.

About

925
Publications
104,711
Reads
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34,424
Citations
Additional affiliations
August 1998 - December 1999
University of Illinois, Urbana-Champaign
Position
  • Professor (Assistant)
March 2009 - July 2009
Technical University of Munich
Position
  • Instructor
January 2000 - present
Massachusetts Institute of Technology
Position
  • Professor (Full)

Publications

Publications (925)
Preprint
Long, powerful soft detection forward error correction codes are typically constructed by concatenation of shorter component codes that are decoded through iterative Soft-Input Soft-Output (SISO) procedures. The current gold-standard is Low Density Parity Check (LDPC) codes, which are built from weak single parity check component codes that are cap...
Preprint
We introduce an algorithm for approximating the codebook probability that is compatible with all successive cancellation (SC)-based decoding algorithms, including SC list (SCL) decoding. This approximation is based on an auxiliary distribution that mimics the dynamics of decoding algorithms with an SC decoding schedule. Based on this codebook proba...
Preprint
Guessing Codeword Decoding (GCD) is a recently proposed soft-input forward error correction decoder for arbitrary linear forward error correction codes. Inspired by recent proposals that leverage binary linear codebook structure to reduce the number of queries made by Guessing Random Additive Noise Decoding (GRAND), for binary linear codes that inc...
Preprint
We introduce a novel approach to error correction decoding in the presence of additive alpha-stable noise, which serves as a model of interference-limited wireless systems. In the absence of modifications to decoding algorithms, treating alpha-stable distributions as Gaussian results in significant performance loss. Building on Guessing Random Addi...
Preprint
Large language models have drastically changed the prospects of AI by introducing technologies for more complex natural language processing. However, current methodologies to train such LLMs require extensive resources including but not limited to large amounts of data, expensive machinery, and lengthy training. To solve this problem, this paper pr...
Preprint
Full-text available
This paper presents several methods for minimizing packet service time in networks using 5G and beyond. We propose leveraging network coding alongside Hybrid Automatic Repeat reQuest (HARQ) to reduce service time as well as optimizing Modulation and Coding Scheme (MCS) selection based on the service time. Our network coding approach includes a meth...
Article
We propose guessing random additive noise decoding-aided macrosymbols (GRAND-AM) as a nonorthogonal multiple access method that can detect, error correct, and decode multiple users with imperfect channel estimation, asynchronous transmission, and interference, which are all topics of concern for Internet of Things. GRAND-AM is a NOMA method that us...
Article
Full-text available
We study a new framework for designing differentially private (DP) mechanisms via randomized graph colorings, called rainbow differential privacy. In this framework, datasets are nodes in a graph, and two neighboring datasets are connected by an edge. Each dataset in the graph has a preferential ordering for the possible outputs of the mechanism, a...
Preprint
We establish that it is possible to extract accurate blockwise and bitwise soft output from Guessing Codeword Decoding with minimal additional computational complexity by considering it as a variant of Guessing Random Additive Noise Decoding. Blockwise soft output can be used to control decoding misdetection rate while bitwise soft output results i...
Conference Paper
Full-text available
The use of Mutual Information (MI) as a measure to evaluate the efficiency of cryptosystems has an extensive history. However, estimating MI between unknown random variables in a high-dimensional space is challenging. Recent advances in machine learning have enabled progress in estimating MI using neural networks. This work presents a novel applica...
Article
We present the notion of reasonable utility for binary mechanisms, which applies to all utility functions in the literature. This notion induces a partial ordering on the performance of all binary differentially private (DP) mechanisms. DP mechanisms that are maximal elements of this ordering are optimal DP mechanisms for every reasonable utility...
Article
Guessing random additive noise decoding (GRAND) has enabled the practical implementation of maximum likelihood (ML) or near-ML decoding, shifting the paradigm of code-specific decoder design to a code-agnostic decoding architecture. Ordered reliability bits GRAND (ORBGRAND) is a soft-detection variant of GRAND that uses soft information to guide it...
Article
We introduce an algorithm for approximating the codebook probability that is compatible with all successive cancellation (SC)-based decoding algorithms, including SC list (SCL) decoding. This approximation is based on an auxiliary distribution that mimics the dynamics of decoding algorithms with an SC decoding schedule. Based on this codebook proba...
Article
We establish that it is possible to extract accurate blockwise and bitwise soft output (SO) from Guessing Codeword Decoding (GCD) with minimal additional computational complexity by considering it through the lens of Guessing Random Additive Noise Decoding (GRAND). Blockwise SO can be used to control decoding misdetection rate, while bitwise SO res...
Article
Full-text available
Ultra-reliability and low-latency are pivotal requirements of the emerging 6th generation of communication systems (xURLLC). The transition in millimeter-wave (mmWave) technology, from omni-directional to highly directional antennas, has been seen as an enabler for high bandwidth communications, still susceptible to high loss and high latency varia...
Preprint
Full-text available
This paper presents CERMET, an energy-efficient hardware architecture designed for hardware-constrained cryptosystems. CERMET employs a base cryptosystem in conjunction with network coding to provide both information-theoretic and computational security while reducing energy consumption per bit. This paper introduces the hardware architecture for t...
Article
In the wideband regime, the performance of many of the popular modulation schemes such as code division multiple access and orthogonal frequency division multiplexing fails quickly without channel state information. black It is known that in this regime, reliable channel state information, both imperfect and perfect, cannot be obtained owing to ene...
Article
Full-text available
In this paper, we show that the Advanced Encryption Standard (AES) cryptosystem can be utilized as an error-correcting code to obtain reliability over noisy communication and data systems. Specifically, we show that by composing a simple padding followed by encrypting with AES, we can achieve error-correcting performance similar to random codes. We...
Article
Full-text available
Security against eavesdropping is one of the key concerns in the design of any communication system. Many common considerations of the security of a wireless communication channel rely on comparing the signal level measured by Bob (the intended receiver) to that accessible to Eve (a single eavesdropper). Frameworks such as Wyner's wiretap model ens...
Preprint
Full-text available
Network coding has been widely used as a technology to ensure efficient and reliable communication. The ability to recode packets at the intermediate nodes is a major benefit of network coding implementations. This allows the intermediate nodes to choose a different code rate and fine-tune the outgoing transmission to the channel conditions, decoup...
Preprint
We propose to use a liquid time constant (LTC) network to predict the future blockage status of a millimeter wave (mmWave) link using only the received signal power as the input to the system. The LTC network is based on an ordinary differential equation (ODE) system inspired by biology and specialized for near-future prediction for time sequence o...
Preprint
Guessing Random Additive Noise Decoding (GRAND) is a family of hard- and soft-detection error correction decoding algorithms that provide accurate decoding of any moderate redundancy code of any length. Here we establish a method through which any soft-input GRAND algorithm can provide soft output in the form of an accurate a posteriori estimate of...
Preprint
The problem of mismatched guesswork considers the additional cost incurred by using a guessing function which is optimal for a distribution $q$ when the random variable to be guessed is actually distributed according to a different distribution $p$. This problem has been well-studied from an asymptotic perspective, but there has been little work on...
Preprint
Full-text available
Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique for this still-open problem is to train models on the encoded data. Our approach, called Privately Encoded Open Datasets with Public Labels (PEOPL), uses a certain class...
Chapter
In this chapter, we will consider task-oriented representation and acquisition of data in networked and distributed settings: How to acquire, represent, and encode data for the purpose of a specific task. While traditional methods and tools to represent and communicate data are task-agnostic, as they aim to reliably represent the data itself, here...
Preprint
Random jammers that overpower transmitted signals are a practical concern for many wireless communication protocols. As such, wireless receivers must be able to cope with standard channel noise and jamming (intentional or unintentional). To address this challenge, we propose a novel method to augment the resilience of the recent family of universal...
Article
We design a distributed function-aware quantization scheme for distributed functional compression. We consider 2 correlated sources X <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and X <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>...
Article
Full-text available
Spread-spectrum techniques have found extensive use in broadband communications, both in military and commercial applications, for their low interception probability. However, it has been shown that these techniques prove ineffective on non-coherent fading channels with very large bandwidths since its capacity decreases with the increase of the ban...
Article
With the large bandwidths available in the terahertz regime, directional transmissions can exhibit angular dispersion, i.e., frequency-dependent radiation direction. Unfortunately, angular dispersion introduces new security threats as increased bandwidth necessarily yields a larger signal footprint in the spatial domain and potentially benefits an...
Preprint
We establish that during the execution of any Guessing Random Additive Noise Decoding (GRAND) algorithm, an interpretable, useful measure of decoding confidence can be evaluated. This measure takes the form of a log-likelihood ratio (LLR) of the hypotheses that, should a decoding be found by a given query, the decoding is correct versus its being i...
Preprint
In the classic wiretap model, Alice wishes to reliably communicate to Bob without being overheard by Eve who is eavesdropping over a degraded channel. Systems for achieving that physical layer security often rely on an error correction code whose rate is below the Shannon capacity of Alice and Bob's channel, so Bob can reliably decode, but above Al...
Preprint
Optimal modulation (OM) schemes for Gaussian channels with peak and average power constraints are known to require nonuniform probability distributions over signal points, which presents practical challenges. An established way to map uniform binary sources to non-uniform symbol distributions is to assign a different number of bits to different con...
Preprint
Full-text available
The use of mutual information as a tool in private data sharing has remained an open challenge due to the difficulty of its estimation in practice. In this paper, we propose InfoShape, a task-based encoder that aims to remove unnecessary sensitive information from training data while maintaining enough relevant information for a particular ML train...
Conference Paper
Full-text available
Malicious attacks such as jamming can cause significant disruption or complete denial of service (DoS) to wireless communication protocols. Moreover, jamming devices are getting smarter, making them difficult to detect. Forward error correction, which adds redundancy to data, is commonly deployed to protect communications against the deleterious ef...
Preprint
Full-text available
Malicious attacks such as jamming can cause significant disruption or complete denial of service (DoS) to wireless communication protocols. Moreover, jamming devices are getting smarter, making them difficult to detect. Forward error correction, which adds redundancy to data, is commonly deployed to protect communications against the deleterious ef...
Article
Emulating a shared atomic , read/write storage system is a fundamental problem in distributed computing. Replicating atomic objects among a set of data hosts was the norm for traditional implementations (e.g., [11]) in order to guarantee the availability and accessibility of the data despite host failures. As replication is highly storage demanding...
Preprint
Full-text available
Packet losses are common events in today's networks. They usually result in longer delivery times for application data since retransmissions are the de facto technique to recover from such losses. Retransmissions is a good strategy for many applications but it may lead to poor performance with latency-sensitive applications compared to network codi...
Preprint
Full-text available
Security against eavesdropping is one of the key concerns in the design of any communication system. Many common considerations of the security of a wireless communication channel rely on comparing the signal level measured by Bob (the intended receiver) to that accessible to Eve (an eavesdropper). Frameworks such as Wyner's wiretap model ensure th...
Preprint
A notable result from analysis of Boolean functions is the Basic Invariance Principle (BIP), a quantitative nonlinear generalization of the Central Limit Theorem for multilinear polynomials. We present a generalization of the BIP for bivariate multilinear polynomials, i.e., polynomials over two n-length sequences of random variables. This bivariate...
Preprint
Full-text available
Modern computationally-heavy applications are often time-sensitive, demanding distributed strategies to accelerate them. On the other hand, distributed computing suffers from the bottleneck of slow workers in practice. Distributed coded computing is an attractive solution that adds redundancy such that a subset of distributed computations suffices...
Preprint
For spectral efficiency, higher order modulation symbols confer information on more than one bit. As soft detection forward error correction decoders assume the availability of information at binary granularity, however, soft demappers are required to compute per-bit reliabilities from complex-valued signals. Here we show that the recently introduc...
Preprint
Randomized backoff protocols, such as exponential backoff, are a powerful tool for managing access to a shared resource, often a wireless communication channel (e.g., [1]). For a wireless device to transmit successfully, it uses a backoff protocol to ensure exclusive access to the channel. Modern radios, however, do not need exclusive access to the...
Preprint
Full-text available
Guessing Random Additive Noise Decoding (GRAND) is a family of universal decoding algorithms suitable for decoding any moderate redundancy code of any length. We establish that, through the use of list decoding, soft-input variants of GRAND can replace the Chase algorithm as the component decoder in the turbo decoding of product codes. In addition...
Preprint
Full-text available
Guessing random additive noise decoding (GRAND) is a universal maximum-likelihood decoder that recovers code-words by guessing rank-ordered putative noise sequences and inverting their effect until one or more valid code-words are obtained. This work explores how GRAND can leverage additive-noise statistics and channel-state information in fading c...
Preprint
Full-text available
Guessing random additive noise decoding (GRAND) is a maximum likelihood (ML) decoding method that identifies the noise effects corrupting code-words of arbitrary code-books. In a joint detection and decoding framework, this work demonstrates how GRAND can leverage crude soft information in received symbols and channel state information to generate,...
Article
While many communications media, such as wireless and certain classes of wireline channels, typically lead to bursty errors, most decoders are designed assuming memoryless channels. Consequently, communication systems generally rely on interleaving over tens of thousands of bits to match decoder assumptions. Even for short high rate codes, awaiting...