1,504 research outputs found
A Unified Relay Framework with both D-F and C-F Relay Nodes
Decode-and-forward (D-F) and compress-and-forward (C-F) are two fundamentally
different relay strategies proposed by (Cover and El Gamal, 1979).
Individually, either of them has been successfully generalized to multi-relay
channels. In this paper, to allow each relay node the freedom of choosing
either of the two strategies, we propose a unified framework, where both the
D-F and C-F strategies can be employed simultaneously in the network. It turns
out that, to fully incorporate the advantages of both the best known D-F and
C-F strategies into a unified framework, the major challenge arises as follows:
For the D-F relay nodes to fully utilize the help of the C-F relay nodes,
decoding at the D-F relay nodes should not be conducted until all the blocks
have been finished; However, in the multi-level D-F strategy, the upstream
nodes have to decode prior to the downstream nodes in order to help, which
makes simultaneous decoding at all the D-F relay nodes after all the blocks
have been finished inapplicable. To tackle this problem, nested blocks combined
with backward decoding are used in our framework, so that the D-F relay nodes
at different levels can perform backward decoding at different frequencies. As
such, the upstream D-F relay nodes can decode before the downstream D-F relay
nodes, and the use of backward decoding at each D-F relay node ensures the full
exploitation of the help of both the other D-F relay nodes and the C-F relay
nodes. The achievable rates under our unified relay framework are found to
combine both the best known D-F and C-F achievable rates and include them as
special cases
Noisy Network Coding with Partial DF
In this paper, we propose a noisy network coding integrated with partial
decode-and-forward relaying for single-source multicast discrete memoryless
networks (DMN's). Our coding scheme generalizes the
partial-decode-compress-and-forward scheme (Theorem 7) by Cover and El Gamal.
This is the first time the theorem is generalized for DMN's such that each
relay performs both partial decode-and-forward and compress-and-forward
simultaneously. Our coding scheme simultaneously generalizes both noisy network
coding by Lim, Kim, El Gamal, and Chung and distributed decode-and-forward by
Lim, Kim, and Kim. It is not trivial to combine the two schemes because of
inherent incompatibility in their encoding and decoding strategies. We solve
this problem by sending the same long message over multiple blocks at the
source and at the same time by letting the source find the auxiliary covering
indices that carry information about the message simultaneously over all
blocks.Comment: 5 pages, 1 figure, to appear in Proc. IEEE ISIT 201
The Generalized Degrees of Freedom of the Interference Relay Channel with Strong Interference
The interference relay channel (IRC) under strong interference is considered.
A high-signal-to-noise ratio (SNR) generalized degrees of freedom (GDoF)
characterization of the capacity is obtained. To this end, a new GDoF upper
bound is derived based on a genie-aided approach. The achievability of the GDoF
is based on cooperative interference neutralization. It turns out that the
relay increases the GDoF even if the relay-destination link is weak. Moreover,
in contrast to the standard interference channel, the GDoF is not a
monotonically increasing function of the interference strength in the strong
interference regime.Comment: 8 pages, 4 figures, Allerton 201
Cooperative Strategies for Simultaneous and Broadcast Relay Channels
Consider the \emph{simultaneous relay channel} (SRC) which consists of a set
of relay channels where the source wishes to transmit common and private
information to each of the destinations. This problem is recognized as being
equivalent to that of sending common and private information to several
destinations in presence of helper relays where each channel outcome becomes a
branch of the \emph{broadcast relay channel} (BRC). Cooperative schemes and
capacity region for a set with two memoryless relay channels are investigated.
The proposed coding schemes, based on \emph{Decode-and-Forward} (DF) and
\emph{Compress-and-Forward} (CF) must be capable of transmitting information
simultaneously to all destinations in such set.
Depending on the quality of source-to-relay and relay-to-destination
channels, inner bounds on the capacity of the general BRC are derived. Three
cases of particular interest are considered: cooperation is based on DF
strategy for both users --referred to as DF-DF region--, cooperation is based
on CF strategy for both users --referred to as CF-CF region--, and cooperation
is based on DF strategy for one destination and CF for the other --referred to
as DF-CF region--. These results can be seen as a generalization and hence
unification of previous works. An outer-bound on the capacity of the general
BRC is also derived. Capacity results are obtained for the specific cases of
semi-degraded and degraded Gaussian simultaneous relay channels. Rates are
evaluated for Gaussian models where the source must guarantee a minimum amount
of information to both users while additional information is sent to each of
them.Comment: 32 pages, 7 figures, To appear in IEEE Trans. on Information Theor
Multiple Access Channels with Generalized Feedback and Confidential Messages
This paper considers the problem of secret communication over a multiple
access channel with generalized feedback. Two trusted users send independent
confidential messages to an intended receiver, in the presence of a passive
eavesdropper. In this setting, an active cooperation between two trusted users
is enabled through using channel feedback in order to improve the communication
efficiency. Based on rate-splitting and decode-and-forward strategies,
achievable secrecy rate regions are derived for both discrete memoryless and
Gaussian channels. Results show that channel feedback improves the achievable
secrecy rates.Comment: To appear in the Proceedings of the 2007 IEEE Information Theory
Workshop on Frontiers in Coding Theory, Lake Tahoe, CA, September 2-6, 200
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