  How are we able to fix it so as to theoretically go over it, if the
optimality and efficiency of the orbital angular momentum (OAM) multiplexing
technique in a multi-input multi-output (MIMO) system fails in practice --
something that technically causes a considerable reduction in the maximum
achievable value of the transceiver's degree-of-freedom? Is the aforementioned
challenging issue theoretically interpretable?
  This paper considers the above mentioned challenge in the reconfigurable
intelligent surface based systems -- as an exemplified system model -- and
consequently proposes a Mendelain randomaisation (MR) technique through which
we can further overcome the aforementioned challenge. Towards such end and in
this paper, we take into account a Markov chain
$\mathcal{G}-\circ-\mathcal{X}-\circ-\mathcal{Y}-\circ-\mathcal{V}$ while
$\mathcal{G}$, $\mathcal{X}$, $\mathcal{Y}$ and $\mathcal{V}$ respectively
denote transmit design parameters, quality of goods, error floor in data
detection and non-orthogonality set in the OAM implementation -- arisen from
other non-optimalities, disturbances and inefficiencies such as the atmospheric
Kolmogorov turbulence. Furthermore, we consider a not-necessarily-Gaussian
randomisation method according to which the resultant probability distribution
function (PDF) is 2-D in relation to a definable outage probability in the
design problem in relation to $\mathcal{Y}$ -- that is, in terms of
$\beta_{\mathcal{X}}\theta$ while the randomisation is applied to $\theta$ as
the control input which should be optimally derived as the graph-theoretically
associating parameter between $\mathcal{X}$ and $\mathcal{Y}$, and
$\beta_{\mathcal{X}}$ is the the associating parameter between $\mathcal{G}$
and the exposure $\mathcal{X}$.
