Energy-Efficient Downlink Resource Allocation in Heterogeneous OFDMA Networks

International audienceIn this paper, we investigate energy-efficient downlink resource allocation in heterogeneous OFDMA networks, and formulate the energy efficiency (EE) maximization problem as a mixed-integer nonlinear fractional programming (MINLFP) problem with a non-concave nonlinear objective function and nonlinear constraints. By means of fractional programming and changing of variables, we transform the original MINLFP problem into an equivalent optimization problem in a parametric subtractive form, which is proved to be a concave mixed-integer nonlinear programming (MINLP) problem and is optimally solved by using Dinkelbach and branch-and-bound (BB) methods. In BB method, the concave MINLP problem is relaxed to a series of concave nonlinear programming problems and solved by the use of Powell-Hestenes-Rockafellar augmented Lagrangian method. The optimal solution can be used to benchmark the performance of sub-optimal solutions. As the computational complexity of BB method increases exponentially with problem size, we further develop a sub-optimal two-step scheme, which first allocates the resource blocks and then performs the transmit power control, to give sub-optimal solution with much lower complexity. Simulation results demonstrate the effectiveness of the proposed schemes and show that the proposed sub-optimal two-step scheme is promising for practical applications as it makes a good tradeoff between EE performance and computational complexity