13 V. PART I: MGF OF THE CUMULATIVE UPLINK AND DOWNLINK INTERCELL INTERFERENCE Computing the distribution of the cumulative ICI Y requires the convolution of the PDF of L RVs X$_{l}$ , ∀ l = 1 , 2 , · · · L , which is a tedious task for many practical scenarios. To avoid the convolutions, we utilize an MGF based approach and derive the expression for the MGF of the cumulative ICI Y . A. Derivation for the Uplink Interference Since each cell is considered to have same scheduling scheme deployed, therefore, the MGF of the cumulative interference considering i.i.d. interferers can be calculated as follows: M$_{Y}$ ( t ) = L ∏ l =1 M$_{X}$$_{l}$ ( t ) = ( M$_{X}$ ( t )) L = ( E [ e $^{tx}$] ) L (31) Looking at the structure of (30), we can write M$_{X}$ ( t ) as: M$_{X}$ ( t ) = ∫ ∞ 0 e $^{tx}$f$_{X}$ ( x ) dx = M$_{X}$ ( t ) = ˜ r$_{M}$ ∑ ˜ r$_{m}$ =˜ r 1 P (˜ r$_{sel}$ = ˜ r$_{m}$ ) ¯ K ˜ r − β m ∫ ∞ 0 e $^{tx}$f$_{χ}$ ( x ˜ r β m ¯ K − $^{1}$) dx (32) The derived expression is generic and applies to any composite fading distribution. Next, we will present explicit MGF expressions for the uplink ICI considering three typically used practical fading models. Special Case 1: Rayleigh fading - ζ, χ ∼ Exp( λ ) : In this case, the small scale fading coefficient on a given subcarrier is considered to be Rayleigh distributed whereas the effect of shadowing is not considered. The distribution of interference considering a single interfering cell can then be derived as follows: f$_{X}$ ( x ) = ˜ r$_{M}$ ∑ ˜ r$_{m}$ =˜ r 1 ¯ K − $^{1}$λ ˜ r β $_{m}$e − λ ˜ r β m ¯ K $^{$^{$_{−}$1}$x}$P (˜ r$_{sel}$ = ˜ r$_{m}$ ) (33) Note that (33) is a Hyper-Exponential distribution with parameter ¯ K − $^{1}$λ ˜ r β $_{m}$. Thus, using the MGF of the Hyper-Exponential distribution, M$_{Y}$ ( t ) can be derived as follows: M$_{Y}$ ( t ) = ( ˜ r$_{M}$ ∑ ˜ r$_{m}$ =˜ r 1 ¯ K − $^{1}$λ ˜ r β m ¯ K − $^{1}$λ ˜ r β $_{m}$− t P (˜ r$_{sel}$ = ˜ r$_{m}$ ) ) L (34) Special Case 2: Generalized- K composite fading - ζ, χ ∼ K$_{G}$ ( m$_{s}$, m$_{c}$, Ω) : In wireless channels, shad- owing and fading across the channel between a user and BS can be jointly modeled by a composite fading distribution. A closed form composite fading model, namely Generalized- K also referred to as Gamma- Gamma distribution, has been recently introduced in [15] which is general enough to model well-known shadowing and fading distributions such as log-normal, Nakagami- m , Rayleigh etc. Using (30), f$_{X}$ ( x ) in