A Distributed Probability Collectives Optimization Method for Multicast in CDMA Wireless Data Networks

Recently, the problem of resource allocation for achieving optimal multicast throughput has become of high interest. In this paper, we consider scenarios in which the utility function is an arbitrary, rather than concave function of multicast rate and specifically apply the proposed algorithm to the multicast problem in CDMA wireless networks. By using a combination of probability collectives (PC) method and network coding, a new cross-layer optimization approach which converges to a sub-optimal solution is proposed. This solution has been achieved by decomposing the original problem into data routing sub-problems at the network layer and power allocation sub-problems at the physical layer. These sub-problems are then coupled through a set of Lagrangian multipliers and each sub- problem is solved in a distributed fashion. It will also be shown that if the utility function is concave or monotonic, the proposed approach converges to a near optimal solution.