DocumentCode :
20285
Title :
The Finite State MAC With Cooperative Encoders and Delayed CSI
Author :
Goldfeld, Ziv ; Permuter, Haim H. ; Zaidel, Benajmin M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
Volume :
60
Issue :
10
fYear :
2014
fDate :
Oct. 2014
Firstpage :
6181
Lastpage :
6203
Abstract :
In this paper, we consider the finite-state multiple access channel (MAC) with partially cooperative encoders and delayed channel state information (CSI). Here, partial cooperation refers to the communication between the encoders via finite-capacity links. The channel states are assumed to be governed by a Markov process. Full CSI is assumed at the receiver, while at the transmitters, only delayed CSI is available. The capacity region of this channel model is derived by first solving the case of the finite-state MAC with a common message. Achievability for the latter case is established using the notion of strategies, however, we show that optimal codes can be constructed directly over the input alphabet. This results in a single codebook construction that is then leveraged to apply simultaneous joint decoding. Simultaneous decoding is crucial here because it circumvents the need to rely on the capacity region´s corner points, a task that becomes increasingly cumbersome with the growth in the number of messages to be sent. The common message result is then used to derive the capacity region for the case with partially cooperating encoders. Next, we apply this general result to the special case of the Gaussian vector MAC with diagonal channel transfer matrices, which is suitable for modeling, e.g., orthogonal frequency division multiplexing-based communication systems. The capacity region of the Gaussian channel is presented in terms of a convex optimization problem that can be solved efficiently using numerical tools. The region is derived by first presenting an outer bound on the general capacity region and then suggesting a specific input distribution that achieves this bound. Finally, numerical results are provided that give valuable insight into the practical implications of optimally using conferencing to maximize the transmission rates.
Keywords :
Gaussian channels; Markov processes; channel capacity; channel coding; convex programming; decoding; CSI; Gaussian channel; Gaussian vector MAC; Markov process; capacity region; channel state information; convex optimization problem; diagonal channel transfer matrices; finite state MAC; finite-state multiple access channel; optimal codes; partially cooperative encoders; simultaneous joint decoding; single codebook construction; Channel coding; Decoding; Markov processes; Receivers; Silicon; Vectors; Capacity region; common message; convex optimization; cooperative encoders; delayed CSI; diagonal vector gaussian multiple-access channel; finite-state channel; multiple-access channel; simultaneous decoding; strategy letters;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2014.2346494
Filename :
6874560
Link To Document :
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