Long-Term Beamforming in Single Frequency Networks using Semidefinite Relaxation

We examine the application of beamforming in a single frequency network (SFN) for the provision of multicast services. A single frequency network is characterized by the simultaneous transmission of the same signal from multiple base stations. Since each user receives the signal from several base stations, the beamforming weights for many different base stations need to be jointly optimized for the transmission in order to give optimal results. The determination of the beamforming weights that maximize the minimum SNR is a nonconvex problem. A constraint relaxation however yields a convex program, which can be solved with fast algorithms at only a slight loss of performance. Furthermore, this convex formulation of the problem gives solutions that perform significantly better than omnidirectional transmission.