Dataset associated with the conference paper "Efficient DCC-Enhanced Precoder for Radio Stripes in Cell-Free Massive MIMO"

Description This repository contains a simulation dataset of 4 distinct cell-free massive MIMO scenarios, where each scenario includes 20,000 setups. Each scenario considered different configurations that are indicated in the name of the variables as 'parameter_precoder_cooperation' where: parameter: is the estimated variable which values can be; (1) parameter = 'R' for the spectral efficiency (SE) calculated as Pareto-optimal rate, (2) parameter = 'SE' for the SE refined version, and (3) parameter = 'time' for the execution time of that configuration in seconds. precoder: is the precoding scheme used; (1) precoder = 'MMSE' for the minimum mean-squared error (MMSE), (2) precoder = 'LTMMSE' for the local team MMSE (LTMMSE), (3) precoder = 'UTMMSE' for the unidirectional team MMSE (UTMMSE), and (4) precoder = 'LPMMSE' for the local partial MMSE (LPMMSE). cooperation: is the APs cooperation scheme; (1) cooperation = 'all' for all the APs serving all UEs, and (2) cooperation = 'DCC' for dynamic cooperation cluster (DCC) scheme. Please refer to the conference paper below for more detailed information about the simulations. The simulation code is available here on GitHub. Referencing If you in any way use this dataset for research that results in publications, please cite our original article listed above. G. García-Barrios and M. Fuentes, "Efficient DCC-Enhanced Precoder for Radio Stripes in Cell-Free Massive MIMO," 2025 IEEE Conference on Standards for Communications and Networking (CSCN), Bologna, Italy, 2025. [Submitted] Acknowledgments This work is supported by the Spanish ministry of economic affairs and digital transformation and the European Union - NextGenerationEU [UNICO I+D 6G/INSIGNIA] (TSI-064200-2022-006).