Distributed Algorithms for Minimum Cost Multicast with Network Coding in Wireless Networks

We adopt the network coding approach to achieve minimum-cost multicast in interference-limited wireless networks where link capacities are functions of the signal-to-interference-plus-noise ratio (SINR). Since wireless link capacities can be controlled by varying transmission powers, minimum-cost multicast must be achieved by jointly optimizing network coding subgraphs with power control and congestion control schemes. To address this, we design a set of node-based distributed gradient projection algorithms which iteratively adjust local control variables so as to converge to the optimal power control, coding subgraph, and congestion control configuration. We explicitly derive the scaling matrices required in the gradient projection algorithms for fast, guaranteed global convergence, and show how the scaling matrices can be computed in a distributed manner.