11 (ii) the first time slot of the greedy round robin scheme. Monte-Carlo simulation time required for 100,000 trials in greedy scheme requires around 150.671928 sec which is more than 150 times the computational complexity of NIntegrate operation. This fact demonstrates the computational effici ency of greedy scheme in comparison to Monte-Carlo simulations. However, in the second time slot, greedy round robin scheme requires K − 1 integrations whereas, for the third time slot K − 2 integrations are required. Therefore, in general the computational complexity of greedy round robin scheme at any time slot w can be given as: where K denotes the number of rings. Therefore considering w = 15 and K = w for greedy round robin, the analytical time complexity is around 113 sec which is still lower than the Monte-Carlo simulation time required for the greedy scheme. Therefore, even though the greedy round robin scheme is computationally complex for large W , the evaluation time remains comparable to the Monte-Carlo simulations. Note that, P ( r$_{sel}$ = r$_{k}$ ) derived for all of the above scheduling schemes is the marginal PMF of P ( r$_{sel}$ = r$_{k}$, θ = θ$_{i}$ ) where θ denotes the angle of the allocated user with respect to the serving BS and it is uniformly distributed from 0 to 2 π (see Fig. 1). Although the PDF of θ is continuous we can discretize it for analytical consistency and complexity reduction. Consider discretizing the range of RV θ in I uniform angular intervals of desired accuracy. Thus P ( θ = θ$_{i}$ ) = 1 I where θ$_{i}$ denotes any discrete value that the RV θ can take. Since r$_{sel}$ and θ are independent, their joint PMF can be written as follows: The derivation for the distribution of the ICI from an interfering cell l , i.e., f$_{X}$$_{l}$ ( x ) , depends on the distribution of the distance between the allocated user in the interfering cell l and the BS of interest, i.e., f$_{˜}$ $_{r$_{sel}$$_{l}$}$(˜ r ) . As mentioned earlier, each interfering cell is assumed to have identical conditions in a given time slot. Therefore, f$_{˜}$ $_{r$_{sel}$}$(˜ r ) applies to all interfering cells and, thus, we will drop the subscript l in the sequel to simplify notation. Using the cosine law (see Fig. 1), we can write: ˜ r 2 sel = r 2 sel + D 2 − 2 r$_{sel}$D cos θ (25) P ( r$_{sel}$ = r$_{k}$, θ = θ$_{i}$ ) = P ( r$_{sel}$ = r$_{k}$ ) P ( θ = θ$_{i}$ ) = P ( r$_{sel}$ = r$_{k}$ ) I (24) IV. PART I: DISTRIBUTION OF INTERCELL INTERFERENCE FROM ONE CELL Computational time[sec] = 0 . 95 + w ∑ i =2 0 . 95( K − i + 1); w ≤ K (23) F. Evaluating the Joint PMF of r$_{sel}$ and θ