In information theory, a relay channel is a probability model of the communication between a sender and a receiver aided by one or more intermediate relay nodes.
A discrete memoryless single-relay channel can be modelled as four finite sets, and , and a conditional probability distribution on these sets. The probability distribution of the choice of symbols selected by the encoder and the relay encoder is represented by .o------------------o
| Relay Encoder |
o------------------o
Λ |
| y1 x2 |
| V
o---------o x1 o------------------o y o---------o
| Encoder |--->| p(y,y1|x1,x2) |--->| Decoder |
o---------o o------------------o o---------oThere exist three main relaying schemes: Decode-and-Forward, Compress-and-Forward and Amplify-and-Forward. The first two schemes were first proposed in the pioneer article by Cover and El-Gamal.
Decode-and-Forward (DF): In this relaying scheme, the relay decodes the source message in one block and transmits the re-encoded message in the following block. The achievable rate of DF is known as .
Compress-and-Forward (CF): In this relaying scheme, the relay quantizes the received signal in one block and transmits the encoded version of the quantized received signal in the following block. The achievable rate of CF is known as subject to .
Amplify-and-Forward (AF): In this relaying scheme, the relay sends an amplified version of the received signal in the last time-slot. Comparing with DF and CF, AF requires much less delay as the relay node operates time-slot by time-slot. Also, AF requires much less computing power as no decoding or quantizing operation is performed at the relay side.
The first upper bound on the capacity of the relay channel is derived in the pioneer article by Cover and El-Gamal and is known as the Cut-set upper bound. This bound says where C is the capacity of the relay channel. The first term and second term in the minimization above are called broadcast bound and multi-access bound, respectively.
A relay channel is said to be degraded if y depends on only through and , i.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
While both fundamental limits and system implementations are well understood for the point-to-point communication system, much less is developed for general communication networks. This thesis contrib
EPFL2016
In this paper, we investigate the diversity-multiplexing tradeoff (DMT) of the multiple-antenna (MIMO) static half-duplex relay channel. A general expression is derived for the DMT upper bound, which
Institute of Electrical and Electronics Engineers2010
Network information theory explores the fundamental data transport limits over communication networks. Broadcasting and relaying are two natural models arising in communication contexts where multiple