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Summary: A cell‐free (CF) technology and unmanned aerial vehicles (UAVs) acting as aerial relay stations (ARSs) are gradually viewed as viable technologies for usage in sixth‐generation (6G) wireless networks owing to their outstanding advantages, such as large coverage, uniform service quality, huge connections, flexible deployment in all geographical areas, and high line‐of‐sight (LoS) probability. As a result, the combination of the CF model and UAVs is suitable for densely populated urban areas, shopping malls, festivals, and locations with complex geography. Furthermore, the integration of the CF model and UAV communication can improve system quality and is considered an entirely new research direction as there is no comprehensive investigation of this combined model. In this study, we investigate the quality of the multi‐ARS CF communication system, where ARSs are equipped with multiple antennas and stochastic distribution within a specific region to simultaneously serve numerous ground users. We establish a closed‐form formulation for the uplink and downlink throughput of individual users by using the matched filtering method and conjugate beamforming technology, respectively. Moreover, we propose a novel method to optimize the pilot and data transmission power coefficients for improving channel estimation and increasing throughput per user, thereby ensuring a high quality of service. The power optimization method is executed via the successive convex approximation (SCA) method, second‐order cone program (SOCP), and linear program. We evaluate system performance according to the cumulative distribution function (CDF) of user throughput based on various parameters, such as the number of users, the number of ARSs, and the length of pilot sequences. The analytical findings also reveal that the system with the proposed power optimization method is always superior to the system without the proposed method in both uplink and downlink. [ABSTRACT FROM AUTHOR]

In this study, we examine the downlink cell-free (CF) multiple aerial relay stations (ARSs) system, where ARSs are outfitted with several antennas, distributed randomly in entire responsible areas, and serve a large number of ground users. The application of the CF model is expected to not only improve the performance of the ARS system but also solve the problem of inconsistent throughput between users and the problem of near-far users in the current advanced networks, such as massive multiple-input multiple-output (mMIMO). Moreover, we propose two ARS selection strategies to cut off poor-quality transmission links in the original CF system, thereby reducing the power consumption of ARSs, reducing interference between users, and improving user throughput. We calculate a closed-form formulation for downlink user throughput under the condition of using conjugate beamforming technology. We optimize the pilot and downlink data transmission coefficients using the successive convex approximation (SCA) method and second-order cone programming (SOCP), respectively. The proposed optimization methods mitigate the problems of "pilot contamination" in channel estimation and inter-user interference in downlink data transmission of systems allowing multiple ARS to access the channel simultaneously. Our findings have assessed the downlink system throughput with pilot and data transmission power optimization for superior results based on a variety of selection strategies as well as the CF model (using all ARSs). In addition, the findings also indicate that the proposed novel ARS selection strategies have better user throughput than the CF technique with a specific number of selected ARS. Our proposed system is a promising technology and opens up various practical application scenarios for 6G networks. [ABSTRACT FROM AUTHOR]