  A new work has been proposed in this paper in order to overcome one of the
main drawbacks that found in the Orthogonal Frequency Division Multiplex (OFDM)
systems, namely Peak to Average Power Ratio (PAPR). Furthermore, this work will
be compared with a previously published work that uses the neural network (NN)
as a solution to remedy this deficiency. The proposed work could be considered
as a special averaging technique (SAT), which consists of wavelet
transformation in its first stage, a globally statistical adaptive detecting
algorithm as a second stage; and in the third stage it replaces the affected
peaks by making use of moving average filter process. In the NN work, the
learning process makes use of a previously published work that is based on
three linear coding techniques. In order to check the proposed work validity, a
MATLAB simulation has been run and has two main variables to compare with;
namely BER and CCDF curves. This is true under the same bandwidth occupancy and
channel characteristics. Two types of tested data have been used; randomly
generated data and a practical data that have been extracted from a funded
project entitled by ECEM. From the achieved simulation results, the work that
is based on SAT shows promising results in reducing the PAPR effect reached up
to 80% over the work in the literature and our previously published work. This
means that this work gives an extra reduction up to 15% of our previously
published work. However, this achievement will be under the cost of complexity.
This penalty could be optimized by imposing the NN to the SAT work in order to
enhance the wireless systems performance.
