Multiuser Eigenmode Transmission Research Articles

An efficient scheduling scheme based on MET for MIMO systems

An efficient multi-user scheduling scheme is proposed to increase the throughput of the system and guarantee the fairness to all the users. In each timeslot, the product factor of each user is updated by the requested data rate and the increment of the mean of the requested data rate. Then the users who are in bad channel condition but have better throughput increment will have more chance to be scheduled; in this way, we can improve the fairness of the system significantly. As the Multi-user Eigen-mode Transmission MET has good performance in improving the throughput of the system, we consider combining the proposed scheme with the MET of MIMO systems. The simulation results show a better trade-off between the throughput and the fairness comparing with the Proportional Fair Scheduling scheme.

On the Fairness of the Multiuser Eigenmode Transmission System

The Multiuser Eigenmode Transmission (MET) has generated significant interests in literature due to its optimal performance in linear precoding systems. The MET can simultaneously transmit several spatial multiplexing eigenmodes to multiple users which significantly enhance the system performance. The maximum number of users that can be served simultaneously is limited due to the constraints on the number antennas, and thus an appropriate user selection is critical to the MET system. Various algorithms have been developed in previous works such as the enumerative search algorithm. However, the high complexities of these algorithms impede their applications in practice. In this paper, motivated by the necessity of an efficient and effective user selection algorithm, a low complexity recursive user selection algorithm is proposed for the MET system. In addition, the fairness of the MET system is improved by using the combination of the proposed user selection algorithm and the adaptive Proportional Fair Scheduling (PFS) algorithm. Extensive simulations are implemented to verify the efficiency and effectiveness of the proposed algorithm.