Optimization by Vector Space Methods
Optimization by Vector Space Methods
Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
The capacity of channels with feedback
IEEE Transactions on Information Theory
Rateless coding for arbitrary channel mixtures with decoder channel state information
IEEE Transactions on Information Theory
On 3-receiver broadcast channels with 2-degraded message sets
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Distortion minimization in Gaussian layered broadcast coding with successive refinement
IEEE Transactions on Information Theory
Achieving the empirical capacity using feedback: memoryless additive models
IEEE Transactions on Information Theory
Optimistic Shannon coding theorems for arbitrary single-user systems
IEEE Transactions on Information Theory
About priority encoding transmission
IEEE Transactions on Information Theory
A broadcast approach for a single-user slowly fading MIMO channel
IEEE Transactions on Information Theory
Variable length coding over an unknown channel
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Optimal Transmission Strategy and Explicit Capacity Region for Broadcast Z Channels
IEEE Transactions on Information Theory
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This paper introduces the notions of variable-to-fixed and fixed-to-variable channel capacity, without feedback. For channels that satisfy the strong converse, these notions coincide with the conventional Shannon capacity. For channels that do not behave ergodically, the conventional fixed-rate Shannon capacity only depends on least-favorable channel conditions, while the variable-rate capacity notions are able to capture the whole range of channel states and their likelihood, even in the absence of any side information about channel state at the transmitter. Particular emphasis is placed on memoryless channels that are governed by finitely valued states. We show that (single-user) variable-to-fixed channel capacity is intimately connected to the capacity region of broadcast channels with degraded message sets, and we give an expression for the fixed-to-variable capacity.