  Fluid antennas (FAs) and movable antennas (MAs) have attracted increasing
attention in wireless communications recently. As compared to the conventional
fixed-position antennas (FPAs), their geometry can be dynamically reconfigured,
such that more flexible beamforming can be achieved for signal coverage and/or
interference nulling. In this paper, we investigate the use of MAs to achieve
uniform coverage for multiple regions with arbitrary number and width in the
spatial domain. In particular, we aim to jointly optimize the MAs weights and
positions within a linear array to maximize the minimum beam gain over the
desired spatial regions. However, the resulting problem is non-convex and
difficult to be optimally solved. To tackle this difficulty, we propose an
alternating optimization (AO) algorithm to obtain a high-quality suboptimal
solution, where the MAs weights and positions are alternately optimized by
applying successive convex approximation (SCA) technique. Numerical results
show that our proposed MAbased beam coverage scheme can achieve much better
performance than conventional FPAs.
