The paper "Power Allocation for Massive MIMO-ISAC Systems" by Liao et al. (2024) investigates the transmit beamforming design for massive multiple-input multiple-output (mMIMO) integrated sensing and communications (ISAC) systems. The authors propose a structured mMIMO-ISAC transmit beamformer that combines a linear precoder and a pre-designed array beamformer, with weights adjusted through power allocation to balance communication and sensing performance. The design problem is formulated as a total transmit power minimization while satisfying sensing and communication requirements. Closed-form expressions for effective SINR and mainlobe-to-average sidelobe ratio (MASR) are derived using the use-and-then-forget strategy, leading to linear programming (LP) problems with analytical solutions. The paper also analyzes the best sensing and communication performance, the minimum number of antennas required, and the impact of channel correlation. Simulations demonstrate the effectiveness of the proposed methods.The paper "Power Allocation for Massive MIMO-ISAC Systems" by Liao et al. (2024) investigates the transmit beamforming design for massive multiple-input multiple-output (mMIMO) integrated sensing and communications (ISAC) systems. The authors propose a structured mMIMO-ISAC transmit beamformer that combines a linear precoder and a pre-designed array beamformer, with weights adjusted through power allocation to balance communication and sensing performance. The design problem is formulated as a total transmit power minimization while satisfying sensing and communication requirements. Closed-form expressions for effective SINR and mainlobe-to-average sidelobe ratio (MASR) are derived using the use-and-then-forget strategy, leading to linear programming (LP) problems with analytical solutions. The paper also analyzes the best sensing and communication performance, the minimum number of antennas required, and the impact of channel correlation. Simulations demonstrate the effectiveness of the proposed methods.