The celebrated Blahut-Arimoto algorithm computes the capacity of a discrete memoryless point-to-point channel by alternately maximizing the objective function of a maximization problem. This algorithm has been applied to degraded broadcast channels, in which the supporting hyperplanes of the capacity region are again cast as maximization problems. In this work, we consider general broadcast channels and extend this algorithm to compute inner and outer bounds on the capacity regions. Our main contributions are as follows: first, we show that the optimization problems are max-min problems and that the exchange of minimum and maximum holds; second, we design Blahut-Arimoto algorithms for the maximization part and gradient descent algorithms for the minimization part; third, we provide convergence analysis for both parts. Numerical experiments validate the effectiveness of our algorithms.
Keywords: Blahut–Arimoto algorithm; Marton’s inner bound; UV outer bound; broadcast channel; capacity region; superposition coding inner bound.