期刊
IEEE TRANSACTIONS ON INFORMATION THEORY
卷 63, 期 6, 页码 3516-3539出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIT.2017.2668391
关键词
Capacity; compressed sensing; multiple access; sparse recovery; user identification
资金
- National Science Foundation [ECCS-1231828, CCF-1423040]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1423040] Funding Source: National Science Foundation
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.
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