Predicting Wireless MmWave Massive MIMO Channel Characteristics Using Machine Learning Algorithms

Table 4

RMSE Loss with Different Dataset in the Lab Scenarios.

Dataset	3030R		3030G		211211G		3030G and 3030R		211211G and 3030G
RMSE	TL	VL	TL	VL	TL	VL
PL	3.0596	3.1949	1.0616	1.3186	1.0439	1.1459	0.3470	0.4127	0.9833	0.8690
DM	1.8142	2.0642	1.4970	1.8566	1.0196	1.0645	0.8252	0.8994	0.6811	0.5734
DS	0.4866	0.5037	0.2698	0.3528	0.2168	0.3038	0.5545	0.7004	0.8036	0.8611
AAMA	19.1869	19.8408	8.9489	9.0166	7.0688	7.5453	0.4664	0.4544	0.7899	0.8368
AASA	12.6992	12.2539	8.0887	8.4545	5.1746	5.8588	0.6369	0.6899	0.6397	0.6930
AAMD	17.7100	20.5364	14.2148	20.3331	6.7187	7.1652	0.8026	0.9901	0.4727	0.3524
AASD	15.1566	14.7420	8.3635	12.6681	6.2428	6.5880	0.5518	0.8593	0.7464	0.5200
EAMA	3.3544	3.4216	1.4747	1.7197	1.2807	1.4928	0.4396	0.5026	0.8684	0.8681
EASA	1.5093	1.8472	0.8160	0.6658	0.8084	0.4824	0.5356	0.3604	0.9907	0.7245
EAMD	2.2215	2.4836	1.9990	1.9906	1.6045	1.7258	0.8998	0.8015	0.8027	0.8670
EASD	0.3008	0.3739	0.2989	0.3697	0.2287	0.2360	0.9937	0.9888	0.7603	0.6384