**4.1 OEP 1: deterministic approach**

Given a set of f g *EbNoi Nmeas <sup>i</sup>*¼<sup>1</sup> , we measure the corresponding *BER*<sup>~</sup> *<sup>i</sup>* � �*Nmeas <sup>i</sup>*¼<sup>1</sup> and compute the mean square error (MSE) based on the previously generated data set using:

$$\text{MSE}(T, IIPO) = \sum\_{i=1}^{N\_{\text{max}}} \left(BER(EbNo\_i, T, IPBO) - B\tilde{E}R\_i\right)^2 \tag{3}$$

The goal is to choose the best temperature *T*<sup>∗</sup> and *IPBO*<sup>∗</sup> that minimizes the least mean square error.
