Optimal Encoding Schemes for Several Classes of Discrete Degraded Broadcast Channels
Bike Xie, Thomas Courtade, and Richard D. Wesel

TL;DR
This paper identifies classes of discrete degraded broadcast channels where a simple encoding scheme called natural encoding achieves capacity, and proves its optimality for several specific channel types.
Contribution
It introduces natural encoding and proves its capacity-achieving property for multiple classes of discrete memoryless degraded broadcast channels.
Findings
Natural encoding achieves capacity for certain classes of DBCs.
The paper proves the optimality of permutation encoding for input-symmetric DBCs.
Provides explicit parametric expressions for specific two-receiver channels.
Abstract
Consider a memoryless degraded broadcast channel (DBC) in which the channel output is a single-letter function of the channel input and the channel noise. As examples, for the Gaussian broadcast channel (BC) this single-letter function is regular Euclidian addition and for the binary-symmetric BC this single-letter function is Galois-Field-two addition. This paper identifies several classes of discrete memoryless DBCs for which a relatively simple encoding scheme, which we call natural encoding, achieves capacity. Natural Encoding (NE) combines symbols from independent codebooks (one for each receiver) using the same single-letter function that adds distortion to the channel. The alphabet size of each NE codebook is bounded by that of the channel input. Inspired by Witsenhausen and Wyner, this paper defines the conditional entropy bound function , studies its properties, and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Communication Security Techniques · Error Correcting Code Techniques · DNA and Biological Computing
