(the code available for a practical use is described for example in [@Hautmann:2014uua]). Another approach, so called KMR (Kimber-Martin-Ryskin) procedure [@Kimber:1999xc; @Kimber:2001sc], takes ordinary PDFs and injects $k_{T}$ dependence via the Sudakov form factor taking care of matching to the BFKL evolution at small $x$. A serious advantage of this procedure is that one can use well known PDF sets, fitted to large data sets. Yet another approach was used in [@vanHameren:2014ala] in therms of so-called “Sudakov resummation model”. This procedure reverts, in a sense, the logic used in the KMR and uses the Sudakov form factor to inject the hard scale dependence instead of $k_{T}$. The procedure is parton-shower-like, i.e. it is applied after the MC events are generated and the cross section is known, and is unitary (i.e. the procedure does not change the total cross section). The advantage is that one may use it on the top of UGDs involving nonlinear effects. The basic idea behind the model is that it assigns the Sudakov probability $P$ for events with given $k_T$ and a hard scale $\mu\sim p_T$. Then, the probability of surviving is $1-P$. For events with small $k_T$ and large $\mu$ the emission probability is $P\sim 