Most of studies on Distributed Antenna System(DAS) focus on maximizing the sum capacity and perfect channel state information at transmitter(CSIT).However,CSI is inevitable imperfect in practical wireless networks.Based on the sources of error,there are two models.One assumes error lies in a bounded region,the other assumes random error.Accordingly,we propose two joint antenna selection(AS) and robustbeamforming schemes aiming to minimize the total transmit power at antenna nodes subject to quality of service(QoS) guarantee for all the mobile users(MUs) in multicell DAS.This problem is mathematically intractable.For the bounded error model,we cast it into a semidefinite program(SDP) using semidefinite relaxation(SDR) and S-procedure.For the second,we first design outage constrained robust beamforming and then formulate it as an SDP based on the Bernstein-type inequality,which we generalize it to the multi-cell DAS.Simulation results verify the effectiveness of the proposed methods. Most of studies on Distributed Antenna System (DAS) focus on maximizing the sum capacity and perfect channel state information at transmitter (CSIT). However, CSI is inevitable imperfect in practical wireless networks. Based on the sources of error, there are two models. One assumes error lies in a bounded region, the other assumes random error. Accredially, we propose two joint antenna selection (AS) and robust beamforming schemes aiming to minimize the total transmit power at antenna nodes subject to quality of service (QoS) guarantee for all the mobile users (MUs) in multicell DAS. This problem is mathematically intractable. For the bounded error model, we cast it into a semidefinite program (SDP) using semidefinite relaxation (SDR) and S-procedure. For the second, we first design outage constrained robust beamforming and then formulate it as an SDP based on the Bernstein-type inequality, which we generalize it to the multi-cell DAS. Simulation results verify the effectiveness of the proposed methods.