A convex approximation approach to weighted sum rate maximization of multiuser MISO interference channel under outage constraints.
Journal
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic
Pages
3368-3371
Date Issued
2011
Author(s)
Abstract
This paper considers weighted sum rate maximization of multiuser multiple-input single-output interference channel (MISO-IFC) under outage constraints. The outage-constrained weighted sum rate maximization problem is a nonconvex optimization problem and is difficult to solve. While it is possible to optimally deal with this problem in an exhaustive search manner by finding all the Pareto-optimal rate tuples in the (discretized) outage-constrained achievable rate region, this approach, however, suffers from a prohibitive computational complexity and is feasible only when the number of transmitter-receive pairs is small. In this paper, we propose a convex optimization based approximation method for efficiently handling the outage-constrained weighted sum rate maximization problem. The proposed approximation method consists of solving a sequence of convex optimization problems, and thus can be efficiently implemented by interior-point methods. Simulation results show that the proposed method can yield near-optimal solutions. © 2011 IEEE.
Subjects
convex optimization; Multiuser interference channel; outage probability; weighted sum rate maximization
Other Subjects
Achievable rate region; Approximation methods; Convex approximation; Convex optimization problems; Exhaustive search; Interference channels; Interior-point method; Maximization problem; Multi user multiple input single outputs; Multi-user; Multi-user interference; Near-optimal solutions; Nonconvex optimization problem; outage probability; Pareto-optimal; Simulation result; Weighted sum-rate; Approximation theory; Computational complexity; Constrained optimization; Signal interference; Speech communication; Convex optimization
Type
conference paper