## 4 Conclusions  
In this paper, we described a cloud radio access network aimed at operating at the mmWave/THz bands beyond 5G systems where the access points support multi-user MU-MIMO transmission using massive/ultra-massive antenna arrays. In order to make the implementation of this scheme feasible, low-complexity hybrid precoding based on several analog architectures, namely fully connected, an array of subarrays and a dynamic array of subarrays combined with single- or double-phase shifters, was considered. Numerical evaluation of both the link- and system-level for the proposed cloud radio access network downlink scheme integrated into a beyond 5G system showed that it is possible to obtain a performance close to the digital precoding when considering scenarios with a larger number of subcarriers and users. The use of partially connected architectures (array of subarrays and dynamic array of subarrays) when compared with fully connected structures tends to achieve good performances in terms of the trade-off between spectral efficiency and energy consumption.  
Assessment of the cloud radio access network deployments in two indoor office scenarios at the THz band showed the capability of achieving significant improvements in terms of throughput performance and coverage over typical cellular networks. The indoor-mixed office scenario provides higher throughput and coverage performances in comparison to the indoor-open office scenario independently of the cluster size, due to less inter-site interference. The variation of the transmitted power of the access points can impact the system results since in order to obtain a better performance an optimal value of transmitted power of around 100 mW must be considered. Furthermore, it was observed that the use of a larger cluster size, namely using 3C instead of 1C, tends to result in a lower throughput penalty when replacing a fully digital implementation with a lower complexity hybrid scheme (fully connected or dynamic array of subarrays).  
Conceptualization, J.P.P., A.C. and N.S.; methodology, J.P.P., A.C. and N.S.; software, J.P.P., A.C., V.V. and N.S.; validation, J.P.P., A.C., V.V., M.R., PS. and N.S.; formal analysis, J.P.P., A.C., V.V., M.R., P.S. and N.S.; investigation J.P.P., A.C., V.V., M.R., P.S. and N.S.; resources, A.C., M.R., P.S. and N.S.; data curation, J.P.P. and A.C.; writing--original draft preparation J.P.P., A.C., V.V., M.R., P.S. and N.S.; writing--review and editing, J.P.P., A.C., V.V., M.R., P.S. and N.S.; visualization, J.P.P. and A.C.; supervision, A.C., M.R. and N.S.; project administration, A.C. and N.S.; funding acquisition, A.C. and N.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the FCT--Fundacao para a Ciencia e Tecnologia under the grant 2020.05621.BD. The authors also acknowledge the funding provided by FCT/MCTES through national funds and applicable co-funded EU funds under the project UIDB/50008/2020.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.