Adaptive and distributed scheduling in heterogeneous MIMO-based ad hoc networks

Multiple-input and multiple-output (MIMO) technique is considered as one of the most promising wireless technologies that can significantly improve transmission capacity and reliability. Many emerging mobile wireless applications require peer-to-peer transmissions over an ad hoc network, where the nodes often have different number of antennas, and the channel condition and network topology vary over time. It is important and challenging to develop efficient schemes to distributively coordinate transmission resource sharing among a heterogeneous group of nodes over an infrastructure-free mobile ad hoc network. In this work, we propose a holistic distributed scheduling algorithm that can adaptively select different transmission strategies based on the node types and channel conditions to effectively relieve the bottleneck effect caused by nodes with smaller antenna arrays, and avoid transmission failure due to violation of channel constraint. The algorithm also takes advantage of channel information to opportunistically schedule cooperative spatial multiplexed transmissions between nodes and provide special transmission support for higher priority nodes with weak channels, so that the data rate of the network can be maximized while user transmission quality requirement is supported. The performance of our algorithm is studied through extensive simulations and the results demonstrate that our algorithm is very effective in handling node heterogeneity and channel constraint, and can significantly increase the throughput while reducing the transmission delay.