To minimize the outage probability of the cell (OPC) in downlink distributed antenna systems with selection transmission, a complex-encoding genetic algorithm (GA) is proposed to find the optimal locations of the antenna elements (AEs). First, the outage probability at a fixed location in the cell is investigated. Next, an analytical expression of the OPC is derived, which is a function of the AE locations. Then the OPC is used as the objective function of the antenna placement optimization problem, and the complexencoding GA is used to find the optimal AE locations in the cell. Numerical results show that the optimal AE locations are symmetric about the cell center, and the outage probability contours are also given with the optimal antenna placement. The algorithm has a good convergence and can also be used to determine the number of AEs which should be installed in order to satisfy the certain OPC value. Lastly, verification of the OPC’s analytical expression is carried out by Monte Carlo simulations. The OPC with optimal AE locations is about 10% lower than the values with completely random located AEs. To minimize the outage probability of the cell (OPC) in downlink distributed antenna systems with selection transmission, a complex-encoding genetic algorithm (GA) is proposed to find the optimal locations of the antenna elements (AEs). First, the outage probability at a fixed location in the cell is investigated. Next, an analytical expression of the OPC is derived, which is a function of the AE locations. Then the OPC is used as the objective function of the antenna placement optimization problem, and the complexencoding GA is used to find the optimal AE locations in the cell. Numerical results show that the optimal AE locations are symmetric about the cell center, and the outage probability contours are also given with the optimal antenna placement. The algorithm has a good convergence and can also be usedly determine the number of AEs which should be installed in order to satisfy the certain OPC value. Lastly, verification of the OPC’s analytical expression is carried out by Monte Carlo simulations. The OPC with optimal AE locations is about 10% lower than the values ​​with completely random located AEs.