Capacity of Gaussian Many-Access Channels

Xu Chen, Tsung Yi Chen, Dongning Guo

Research output: Contribution to journalArticlepeer-review

82 Scopus citations


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.

Original languageEnglish (US)
Article number7852531
Pages (from-to)3516-3539
Number of pages24
JournalIEEE Transactions on Information Theory
Issue number6
StatePublished - Jun 2017


  • Capacity
  • compressed sensing
  • multiple access
  • sparse recovery
  • user identification

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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