On The Capacity of Broadcast Channels With Degraded Message Sets and Message Cognition Under Different Secrecy Constraints
Abstract
This paper considers a three-receiver broadcast channel with degraded message sets and message cognition. The model consists of a common message for all three receivers, a private common message for only two receivers and two additional private messages for these two receivers, such that each receiver is only interested in one message, while being fully cognizant of the other one. First, this model is investigated without any secrecy constraints, where the capacity region is established, showing that the straightforward extension of the Körner and Marton inner bound to the investigated scenario is optimal. In particular, this agrees with Nair and Wang's result, which states that the idea of indirect decoding - introduced to improve the Körner and Marton inner bound - does not provide a better region for this scenario. Further, some secrecy constraints are introduced by letting the private messages to be confidential ones. Two different secrecy criteria are considered: joint secrecy and individual secrecy. For both criteria, a general achievable rate region is provided. Moreover, the joint and individual secrecy capacity regions are established, if the two legitimate receivers are more capable than the eavesdropper. The established capacity regions indicate that the individual secrecy criterion can provide a larger capacity region as compared to the joint one, because each cognizant message can be used as a secret key for the other individual message. Further, the joint secrecy capacity is established for a more general class of more capable channels, where only one of the two legitimate receivers is more capable than the eavesdropper. This was done by showing that principle of indirect decoding introduced by Nair and El Gamal is optimal for this class of channels. This result is in contrast with the nonsecrecy case, where the indirect decoding does not provide any gain.
- Publication:
-
arXiv e-prints
- Pub Date:
- January 2015
- DOI:
- 10.48550/arXiv.1501.04490
- arXiv:
- arXiv:1501.04490
- Bibcode:
- 2015arXiv150104490M
- Keywords:
-
- Computer Science - Information Theory