Multiple-antenna wireless systems, also known as multiple-input multiple-output (MIMO) cellular networks, can improve the capacity and reliability of communications. To realize these advantages, a packet scheduler should effectively allocate radio resources to users in a fair way. The previously proposed MIMO schedulers have problems such as ignoring traffic arrival process or complexity. We propose a load adaptive multi-output fair queueing (LA-MO-FQ) scheduler, which is based on a fair queueing algorithm with mechanisms for rate selection, compensation of lagging users, and virtual time system. Since some of the scheduler's system parameters are sensitive to the traffic load, it dynamically adjusts them in a way with low complexity so the system performs better. Intensive simulation studies considering the mobility of users and the traffic arrival demonstrate the good performance of LA-MO-FQ. Furthermore, we also propose in this paper some formulae for the time and service fairness comparisons of MIMO schedulers and we use them for comparison with some famous existing schedulers.

In multiple-input multiple-output (MIMO) cellular networks, certain schedulers have two independent phases: the first selects a group of users based on the scheduler criterion, and the second assigns the selected users to the transmit antennas by using an assignment scheme taking into consideration capacity maximization. Other schedulers directly select among the available channels between users and the base station in a centralized way. The schedulers of the first category can be implemented with lower complexity compared with the schedulers of the second category. For the first category, we propose three near-optimal assignment schemes with low complexities. We conducted a simulation in which the mobility of users was considered that demonstrated the superior performance of our assignment schemes. Furthermore, we analytically demonstrate their efficiency.