Low complexity user pairing and resource allocation of heterogeneous users for uplink virtual MIMO system over LTE-A network

Virtual Multiple-Input Multiple-Output (MIMO) is a promising uplink technology that can meet the throughput demand of Long-Term Evolution-Advanced (LTE-A) systems. However, the complexity of scheduling virtual MIMO is a challenge; existing virtual MIMO is therefore limited to best effort applications. We investigate the resource allocation and scheduling problem in a heterogeneous virtual MIMO system where delay sensitive applications are present. The goal is to maximize the system throughput while maintaining delay bound for delay sensitive traffic. To tackle the complexity challenge, we propose two low-complexity subopthnal algorithms, where the key idea is to reduce the search space and iteratively minimize the rate loss respectively. Simulation results show that the rate loss minimization based heuristic algorithm converges to within 99% of the optimal throughput on average and maintains delay bound for delay sensitive users. It also achieves almost the same fairness performance as the optimal solution.