Pathbook: Cross-layer optimization for full-duplex wireless networks

Recently, Choi et al. designed the first practical full-duplex wireless system, which challenges the basic assumption in wireless communications that a radio cannot transmit and receive on the same frequency at the same time. In this paper, we study cross-layer optimization for full-duplex wireless networks, comprehensively considering various resource and social constraints. We focus on (1) the problem of allocating resources to maximize the total profit of multiple users subject to node constraints and (2) the problem of allocating resources to minimize the network power consumption subject to user rate demands and node constraints. We formulate these problems as convex programming systems. By combining Lagrangian decomposition and subgradient methods, we design distributed iterative algorithms to solve these problems, which compute the optimized user information flow (i.e. user behavior) for the network layer and the optimized node broadcast rate (i.e. node behavior) for the MAC layer. Our algorithms allow each user and each node to adjust its own behavior individually in each iteration. We analyze the convergence rate, the amount of feasibility violation, and the gap between the optimal solution and our solution in each iteration. We also use the dual space information to analyze node load constraint violation.