A Channel Classification Scheme Accounting for Nakagami-m Shadowing and FTR Model

In this letter, we address the problem of channel classification. Specifically, consider five models also accounting for incoming fifth generation mobile communication network (5G). The classification is formulated in terms a multiple hypothesis testing and solved through heuristic decision logic relying on sequential binary comparisons. This choice dictated by mathematical intractability probability density functions (PDFs) under some hypotheses which contain transcendental functions. As consequence, rules raising from well-known design criteria based upon data distribution might suffer numerical instability related to routines used implement such PDFs. performance analysis conducted simulated shows effectiveness proposed strategy