A Complexity Adjustable Scheduling Algorithm for Throughput Maximization in Clusterized TDMA Networks

We consider clustered wireless networks, where transceivers in a cluster use a time-slotted mechanism (TDMA) to access a wireless channel that is shared among several clusters. Earlier work has demonstrated that a significant increase in network throughput can be achieved if all the schedules are optimized jointly. However, a drawback of this approach is the prohibitive level of computational complexity is required when a network with a large number of clusters and time-slots is to be scheduled. In this paper, we propose a modification to our previously proposed algorithm which allows for the complexity to be adjusted to the available processing power, provided some minimum processing power is available. This is achieved by carefully reducing the number of interfering clusters considered when scheduling a cluster. In addition, we propose and evaluate two heuristic methods of discarding the less significant clusters. While the optimality of the obtained schedule is not proven, our results demonstrate that large gains are consistently attainable