Distributed resource optimization in multicell OFDMA networks

We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.