This paper investigates the utility of movable antenna (MA) assistance for the multiple-input single-output (MISO) interference channel. The authors propose a joint optimization approach to determine MA positions and transmit beamforming to minimize the total transmit power while satisfying signal-to-interference-plus-noise ratio (SINR) constraints. The non-convex optimization problem is addressed using an efficient iterative algorithm based on successive convex approximation (SCA) and second-order cone programming (SOCP). The algorithm alternately optimizes MA positions and beamforming vectors. Numerical results show that the proposed MA-enabled MISO interference network outperforms conventional systems without MA, significantly enhancing intercell frequency reuse and reducing transmitter design complexity. The MA system with simple beamforming, such as maximum ratio transmission (MRT), performs only slightly worse than complex beamforming and significantly better than the fixed-position antenna (FPA) system. The number of antennas required for MA-aided interference networks is drastically reduced, enabling simpler transmitter designs. The proposed algorithm is effective in MISO interference networks when a certain region size for antenna movement is available. The results demonstrate that the MA-aided interference network can accommodate more cells without increasing total transmit power. The algorithm's complexity is analyzed, and it is shown to be efficient for practical applications. The study concludes that MA-enabled systems offer significant improvements in performance and design simplicity compared to conventional systems.This paper investigates the utility of movable antenna (MA) assistance for the multiple-input single-output (MISO) interference channel. The authors propose a joint optimization approach to determine MA positions and transmit beamforming to minimize the total transmit power while satisfying signal-to-interference-plus-noise ratio (SINR) constraints. The non-convex optimization problem is addressed using an efficient iterative algorithm based on successive convex approximation (SCA) and second-order cone programming (SOCP). The algorithm alternately optimizes MA positions and beamforming vectors. Numerical results show that the proposed MA-enabled MISO interference network outperforms conventional systems without MA, significantly enhancing intercell frequency reuse and reducing transmitter design complexity. The MA system with simple beamforming, such as maximum ratio transmission (MRT), performs only slightly worse than complex beamforming and significantly better than the fixed-position antenna (FPA) system. The number of antennas required for MA-aided interference networks is drastically reduced, enabling simpler transmitter designs. The proposed algorithm is effective in MISO interference networks when a certain region size for antenna movement is available. The results demonstrate that the MA-aided interference network can accommodate more cells without increasing total transmit power. The algorithm's complexity is analyzed, and it is shown to be efficient for practical applications. The study concludes that MA-enabled systems offer significant improvements in performance and design simplicity compared to conventional systems.