**Summary:** This paper analyzes the accuracy of phase calibration in distributed antenna systems (DAS), focusing on scalability and the impact of calibration protocols on beamforming performance. The key findings are: 1. **Phase Calibration Challenges**: For certain topologies (e.g., line or ring), phase calibration errors can grow unbounded as the system size increases. This is due to the accumulation of errors in the calibration process when antennas are spread out geographically. 2. **Optimal Calibration Strategy**: Despite the challenges, it is optimal to solve a single calibration problem for the entire system and use the results for all antennas, regardless of the topology. This approach ensures better beamforming accuracy and avoids the need for frequent recalibration in distributed systems. 3. **Reciprocity Calibration**: Reciprocity (R)-calibration is essential for joint coherent downlink beamforming. It involves estimating the sum of transmit and receive phase shifts for each antenna. R-calibration can be performed using over-the-air measurements between antennas, and it does not require prior knowledge of propagation delays. 4. **Full Calibration**: Full (F)-calibration provides more detailed information about phase shifts, enabling more sophisticated beamforming techniques. However, it requires prior knowledge of propagation delays between antennas, which can be challenging in distributed systems. 5. **Beamforming Performance**: The accuracy of beamforming is significantly affected by phase estimation errors. The paper shows that using a single calibration for the entire system (case a) results in better beamforming performance than using a subset of antennas for calibration (case b). 6. **Scalability**: The paper highlights the importance of scalability in DAS, showing that while some topologies pose challenges for phase calibration, the overall system can still achieve good performance with proper calibration strategies. The analysis is supported by mathematical derivations and examples, including the line (radio stripe) topology, where the calibration errors grow unbounded as the system size increases. The paper concludes that solving a single calibration problem for the entire system is optimal for beamforming performance, even in large-scale distributed antenna systems.**Summary:** This paper analyzes the accuracy of phase calibration in distributed antenna systems (DAS), focusing on scalability and the impact of calibration protocols on beamforming performance. The key findings are: 1. **Phase Calibration Challenges**: For certain topologies (e.g., line or ring), phase calibration errors can grow unbounded as the system size increases. This is due to the accumulation of errors in the calibration process when antennas are spread out geographically. 2. **Optimal Calibration Strategy**: Despite the challenges, it is optimal to solve a single calibration problem for the entire system and use the results for all antennas, regardless of the topology. This approach ensures better beamforming accuracy and avoids the need for frequent recalibration in distributed systems. 3. **Reciprocity Calibration**: Reciprocity (R)-calibration is essential for joint coherent downlink beamforming. It involves estimating the sum of transmit and receive phase shifts for each antenna. R-calibration can be performed using over-the-air measurements between antennas, and it does not require prior knowledge of propagation delays. 4. **Full Calibration**: Full (F)-calibration provides more detailed information about phase shifts, enabling more sophisticated beamforming techniques. However, it requires prior knowledge of propagation delays between antennas, which can be challenging in distributed systems. 5. **Beamforming Performance**: The accuracy of beamforming is significantly affected by phase estimation errors. The paper shows that using a single calibration for the entire system (case a) results in better beamforming performance than using a subset of antennas for calibration (case b). 6. **Scalability**: The paper highlights the importance of scalability in DAS, showing that while some topologies pose challenges for phase calibration, the overall system can still achieve good performance with proper calibration strategies. The analysis is supported by mathematical derivations and examples, including the line (radio stripe) topology, where the calibration errors grow unbounded as the system size increases. The paper concludes that solving a single calibration problem for the entire system is optimal for beamforming performance, even in large-scale distributed antenna systems.