equipment pairing. The ADPS algorithm begins with measuring the SNR value for each user equipment (UE), where this measurement is done by the base station. The channel matrix between the base station and user equipment is measured as well by the base station. Next, the first user will be selected by base station and the second user is selected from the remaining user equipment. The second user is selected by calculating the paring factor with the first user. The criterion for the second user to be selected is depending on the pairing factor. Hence, on the remaining users, the users that achieve the maximum pairing factor is chosen to be paired with the first user. However, the authors only focus on presenting the pairing algorithm with two users. Because the second user will be selected from the remaining user equipment, high computational complexity occurs when more than two users are paired. This is because a single calculation is made for each user equipment in determining the pairing factor before they can be paired. Another study on the user pairing algorithms has been done by Chen et al. (2008). The uplinks virtual-MIMO (V-MIMO) is considered in this research work, where the double proportional fairness (D-PF) algorithm is proposed for implementing the user paring. For user pairing, the first user is selected using the proposed D-PF algorithm with proportional fairness criterion. Then, the second user is chosen, where second user is selected by implementing a modified proportional fair criterion. The performance comparison has been made between the proposed D-PF algorithm with the single PF (S-PF). The S-PF will choose the first user using the proportional fair criterion. Then, the next user is selected to maximize the overall throughput of the user pair. Tough the S-PF algorithm is able to achieve a high overall throughput, but a good fairness between users may not being offered. The scheduler on the base station will choose the group to share the time-frequency resource blocks. In this study, the author focuses only on implementing the user paring with two users for every group, hence, the number of paired users is fixed to two. However, the proposed D-PF algorithm is able to be implemented with more users per group, where the additional number of receiver antennas is needed. For the uplinks V-MIMO system, the identical resource blocks are shared by at least two users or more, in order to improve the system spectral efficiency. By comparing the performance of the proposed D-PF algorithm with the single PF (S-PF), the proposed D-PF algorithms achieve fairly good performances on the trade-off between fairness and throughput. The capacity for the uplink multiuser system can be enhanced by implementing the multiuser scheduling as shown by Viterbo and Hottinen (2008). A scheduling strategy is introduced where the users transmit in different time, frequency or code slots and accordingly refer to the channel quality. The proposed scheduling strategy will be used to solve the problem of combinatorial optimization. The Hungarian algorithm is proposed to perform the multiuser scheduling with the Minimum Mean Square Error (MMSE) receiver detection. It is possible to improve the capacity of the multiuser system in different time-frequency-code (TFC) slots because each user will use different channel condition. The capacity can be enhanced by allocating different groups of users. The user pairing starts by assuming the number of paired users that will access two TFC slots in order to double their rate. Then, the single user will use only one TFC slot as a compensation and allow to double the transmit power. A higher modulation can be employed by the unpaired users by transmitting the double transmit power. Hence, their spectral efficiency can be doubled and compensated for their usage of one TFC slot only. The proposed strategy has improved the performance of multiuser system, where the strategies of efficiently exploiting the channel, interference diversity and joint optimisa>