  This article presents an efficient quasi-optimal sum rate (SR) maximization
technique based on zero-forcing water-filling (ZFWF) algorithm directly applied
to cognitive radio networks (CRNs). We have defined the non-convexity nature of
the optimization problem in the context of CRNs while we have offered all
necessary conditions to solve the related SR maximization problem, which
considers power limit at cognitive transmitter and interference levels at
primary users (PUs) and secondary users (SUs). A general expression capable to
determine the optimal number of users as a function of the main system
parameters, namely the signal-to-interference-plus-noise ratio (SINR) and the
number of BS antennas is proposed. Our numerical results for the CRN
performance are analyzed in terms of both BER and sum-capacity for the proposed
ZF-WF precoding technique, and compared to the classical minimum mean square
error (MMSE), corroborating the effectiveness of the proposed technique
operating in multi user multiple input single output (MU-MISO) CRNs
