Information Theory and Reliable Communication

Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. This paper proposes a new paradigm, referred to as many-user information theory , where the number of users is allowed to grow with the blocklength. This paradigm is motivated by emerging systems with a massive number of users in an area, such as the Internet of Things. The focus of this paper is the many-access channel model, which consists of a single receiver and many transmitters, whose number increases unboundedly with the blocklength. Moreover, an unknown subset of transmitters may transmit in a given block and need to be identified as well as decoded by the receiver. A new notion of capacity is introduced and characterized for the Gaussian many-access channel with random user activities. The capacity can be achieved by first detecting the set of active users and then decoding their messages. The minimum cost of identifying the active users is also quantified.

Capacity of Gaussian Many-Access Channels

This paper applies Information Theoretic analysis to packet-based random multiple access communication systems. A new channel coding approach is proposed for coding within each data packet with built-in support for bursty traffic properties, such as message underflow, and for random access properties, such as packet collision detection. The coding approach does not require joint communication rate determination either among the transmitters or between the transmitters and the receiver. Its performance limitation is characterized by an achievable region defined in terms of communication rates, such that reliable packet recovery is supported for all rates inside the region and reliable collision detection is supported for all rates outside the region. For random access communication over a discrete-time memoryless channel, it is shown that the achievable rate region of the introduced coding approach equals the Shannon information rate region without a convex hull operation. Further connections between the achievable rate region and the Shannon information rate region are developed and explained.

/pdf/a-new-approach-to-random-access-reliable-communication-and-58y5qbppmb.pdf

A New Approach to Random Access: Reliable Communication and Reliable Collision Detection

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the rate information among each other or with the receiver. The receiver will either decode the message or report a collision depending on whether reliable message recovery is possible. It was shown that, asymptotically as the codeword length goes to infinity, the set of communication rates supporting reliable message recovery can be characterized by an achievable region which equals Shannon's information rate region possibly without a convex hull operation. In this paper, we derive achievable bounds on error probabilities, including the decoding error probability and the collision miss detection probability, of random multiple access systems with a finite codeword length. Achievable error exponents are obtained by taking the codeword length to infinity.

Error Performance of Channel Coding in Random Access Communication

A new universal coding/decoding scheme for random access with collision detection is given in case of two senders. The result is used to give achievable joint source-channel coding error exponents for multiple access channel and independent sources. In a modified model admitting zero rate communication between the senders, an improved exponent is derived, of form similar to Csiszar’s joint source-channel exponent for the one-sender case.

Random Access and Source-Channel Coding Error Exponents for Multiple Access Channels

A storage device is configured to utilize different encoding and decoding schemes in reading and writing data to different regions of a storage device based on the position of the storage regions and/or component-specific physical characteristics of the regions. Each encoding scheme may include multiple different types of encoders selected based an optimization process for each region.

Storage device with multiple coding redundancies

1 Random access communication is used in practical systems to deliver bursty short messages. Because users only transmit occasionally, it is often difficult for the receiver to keep track of the time varying wireless channel states. Under this motivation, we develop channel coding theorems for random multiple access communication over compound channels with finite codeword length. Error performance bound and asymptotic error probability scaling laws are derived. We found that the results also help in deriving error performance bounds for the random multiple access system where the receiver is only interested in decoding messages from a user subset.

https://www.engr.colostate.edu/~rockey/Papers/RandomAccessCompoundChannelISIT2011.pdf

Coding theorems for random access communication over compound channel

This paper extends linear-complexity concatenated coding schemes to fountain communication over the discrete-time memoryless channel. Achievable fountain error exponents for one-level and multi-level concatenated fountain codes are derived. It is also shown that concatenated coding schemes possess interesting properties in several multi-user fountain communication scenarios.

Fountain Communication using Concatenated Codes

Guruswami and Indyk showed in [1] that Forney's error exponent can be achieved with linear coding complexity over binary symmetric channels. This paper extends this conclusion to general discrete-time memoryless channels and shows that Forney's and Blokh-Zyablov error exponents can be arbitrarily approached by one-level and multi-level concatenated codes with linear encoding/decoding complexity. The key result is a revision to Forney's general minimum distance decoding algorithm, which enables a low complexity integration of Guruswami-Indyk's outer codes into the concatenated coding schemes.

https://www.engr.colostate.edu/~rockey/Papers/LinearComplexityCodeJournal.pdf

Approaching blokh-zyablov error exponent with linear-time encodable/decodable codes

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Zheng Wang

Author Tools

Chat about Author