Geometric programming duals of channel capacity and rate distortion

被引:70
作者
Chiang, M [1 ]
Boyd, S
机构
[1] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
[2] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
关键词
channel capacity; convex optimization; duality; free energy; geometric programming; rate distortion;
D O I
10.1109/TIT.2003.822581
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We show that the Lagrange dual problems of the channel capacity problem with input cost and the rate distortion problem are simple geometric programs. Upper bounds on channel capacity, And lower bounds on rate distortion can be efficiently generated from their duals. For channel capacity, the geometric programming dual characterization is shown to be equivalent to the minmax Kullback-Leibler (KL) characterization in [10], [14]. For rate distortion, the geometric programming dual is extended to rate distortion with two-sided state information. A "duality by mapping" is then given between the Lagrange dual problems of channel capacity with input cost and rate distortion, which resolves several apparent asymmetries between their primal problems in the familiar form of mutual information optimization problems. Both the primal and dual problems can be interpreted in a common framework of free energy optimization from statistical physics.
引用
收藏
页码:245 / 258
页数:14
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