8 slowly, i.e., their path loss remains nearly the same on a short term basis. In this case, the problem of selecting the maximum normalized SNR in a ring k can be written as: where ¯ ζ$_{i}$ = ∫ ∞ 0 ζ$_{i}$f$_{ζ}$$_{i}$ ( ζ$_{i}$ ) dζ$_{i}$ is the average of the composite fading channel and ζ$_{k}$ is the maximum normalized composite fading channel gain in ring k . For i.i.d. composite fading gains of the users located in ring k , i.e., ¯ ζ = ¯ ζ$_{1}$ = ¯ ζ$_{2}$ = · · · ¯ ζ$_{u}$$_{k}$ , the problem of selecting the user with maximum normalized channel gain reduces to selecting the user with the maximum channel gain, i.e., ζ$_{k}$ = max { ζ$_{1}$, ζ$_{2}$, · · · , ζ$_{i}$, · · · , ζ$_{u}$$_{k}$ } . Thus, for any ring k , the CDF and PDF of the selected SNR γ$_{k}$ = Kr − β k ζ$_{k}$ can be written as: The short term average SNR of the selected user in ring k , i.e., ¯ γ$_{k}$ can then be computed as ¯ γ$_{k}$ = ∫ ∞ 0 γ$_{k}$f$_{γ}$$_{k}$ ( γ$_{k}$ ) dγ$_{k}$ . Finally, the normalized selected SNR in each ring k can be defined as ξ$_{k}$ = γ$_{k}$ ¯ γ$_{k}$ and performing a transformation of RVs, the CDF and PDF of ξ$_{k}$ can be given as F$_{ξ}$$_{k}$ ( ξ$_{k}$ ) = F$_{γ}$$_{k}$ (¯ γ$_{k}$ξ$_{k}$ ) ; and f$_{ξ}$$_{k}$ ( ξ$_{k}$ ) = 1 $_{γ$_{k}$}$f$_{γ}$$_{k}$ (¯ γ$_{k}$ξ$_{k}$ ) , respectively. Step 2 ( Selecting the ring k with maximum normalized SNR from the K rings ): Once we characterize the PDF and CDF of ξ$_{k}$ , the probability of selecting any ring k can be written using (9) as follows: C. Round Robin Scheduling Scheme Round robin scheduling is a non-opportunistic scheme where a user is selected randomly within a time slot. As each user has equal probability of allocation, the scheme can be referred to as a strictly fair scheduling scheme. The round robin scheme provides maximum fairness among users and may serve as a lower bound in terms of network throughput which is useful in calibrating the performance of other scheduling schemes, however, the resulting network throughput is significantly low which makes it less P ( r$_{sel}$ = r$_{k}$ ) = ∫ ∞ 0 ( K ∏ i =1 ,i = k F$_{ξ}$$_{i}$ ( ξ$_{k}$ ) ) f$_{ξ}$$_{k}$ ( ξ$_{k}$ ) dξ$_{k}$ (15) f$_{γ}$$_{k}$ ( γ$_{k}$ ) = 1 r − β k u$_{k}$ ∑ j =1 f$_{ζ}$$_{j}$ ( ¯ ζ$_{j}$γ$_{k}$r β $_{k}$K − $^{1}$) u$_{k}$ ∏ i =1 ,i = j F$_{ζ}$$_{i}$ ( ¯ ζ$_{i}$γ$_{k}$r β $_{k}$K − $^{1}$) i . i . d = u$_{k}$ r − β k ( F$_{ζ}$$_{i}$ ( ¯ ζγ$_{k}$r β $_{k}$K − $^{1}$)) u$_{k}$ − $^{1}$f$_{ζ}$ ( ¯ ζγ$_{k}$r β $_{k}$K − $^{1}$) (14) F$_{γ}$$_{k}$ ( γ$_{k}$ ) = u$_{k}$ ∏ i =1 F$_{ζ}$$_{i}$ ( ¯ ζ$_{i}$γ$_{k}$r β $_{k}$K − $^{1}$) i . i . d = ( F$_{ζ}$$_{i}$ ( ¯ ζγ$_{k}$r β $_{k}$K − $^{1}$)) u$_{k}$ (13) ζ$_{k}$ = max { ζ$_{1}$ ¯ ζ$_{1}$ , ζ$_{2}$ ¯ ζ$_{2}$ , · · · , ζ$_{i}$ ¯ ζ$_{i}$ , · · · , ζ$_{u}$$_{k}$ ¯ ζ$_{u}$$_{k}$ } (12)