to acknowledge the reception of data and to ensure that the erroneous data is retransmitted [@finite].

Fig. \[fig:00\] depicts the two-state transmission model together with the transition probabilities. In this paper, we assume that the channel fading coefficients stay constant over the frame duration $T$. Hence, the state transitions occur at every $T$ seconds. Now, the probability of staying in the ON state, $p_{22}$, is defined as follows[^3]: $$\begin{aligned}
p_{22} &= P\{r < C[i+TB] \, \big | \, r < C[i]\} = P\{z[i+TB]
> \alpha \, \big | \, z[i] > \alpha \} \label{eq:p_22}\end{aligned}$$ where $$\label{eq:thresh}
\alpha=\frac{2^{\frac{r}{B}}-1}{{{\text{\footnotesize{SNR}}}}}.$$ Note that $p_{22}$ depends on the joint distribution of $(z[i+TB],
z[i])$. For the Rayleigh fading channel, the joint density function of the fading amplitudes can be obtained in closed-form [@rapajic]. In this paper, with the goal of simplifying the analysis and providing results for arbitrary fading distributions, we assume that fading realizations are independent for each frame[^4]. Hence, we basically consider a block-fading channel model. Note that in block-fading channels, the duration $T$ over which the fading coefficients stay constant can be varied to model fast or slow fading scenarios.

Under the block fading assumption, we now have $p_{22} = P\{z[i+TB]
> \alpha\} 