  Signal-to-noise ratio (SNR) estimation is an important parameter that is
required in any receiver or communication systems. It can be computed either by
a pilot signal data-aided approach in which the transmitted signal would be
known to the receiver, or without any knowledge of the transmitted signal,
which is a non-data-aided (NDA) estimation approach. In this paper, a NDA SNR
estimation algorithm for QPSK signal is proposed. The proposed algorithm
modifies the existing Signal- to-Variation Ratio (SVR) SNR estimation algorithm
in the aim to reduce its bias and mean square error in case of negative SNR
values at low number of samples of it. We first present the existing SVR
algorithm and then show the mathematical derivation of the new NDA algorithm.
In addition, we compare our algorithm to two baselines estimation methods,
namely the M2M4 and SVR algorithms, using different test cases. Those test
cases include low SNR values, extremely high SNR values and low number of
samples. Results showed that our algorithm had a better performance compared to
second and fourth moment estimation (M2M4) and original SVR algorithms in terms
of normalized mean square error (NMSE) and bias estimation while keeping almost
the same complexity as the original algorithms
