Utility Maximization for MISO Bursty Interference Channels

Abstract

Interference, a major bottleneck in modern wireless communication, is not always present in many practical situations. In fact, due to the bursty nature of traffic in wireless networks, the corresponding interference is often bursty too. Such burstiness, if properly exploited, can provide significant performance gains. To investigate such potential gains, a multiple-user multiple-input single-output bursty interference channel is considered here. It is assumed that interference between users is present with a certain probability. On the basis of the knowledge of interference status, each transmitter adopts a different beamforming strategy and communication rate. Under this setting, we aim to maximize the average system utility and consider the optimal beamforming design when perfect channel state information is assumed at transmitters. The corresponding optimization problem is nonconvex and difficult to solve. To handle such difficulties, we apply a series of convex approximation techniques such as semidefinite relaxation and first-order approximation. Furthermore, we improve the accuracy of our approximation through solving the approximated problem successively and propose successive convex approximation (SCA) algorithms. The near-optimal performances of our proposed SCA algorithms are demonstrated by simulations. Our results show that significant performance gains can be achieved by exploiting the bursty nature of wireless interference networks.