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Opportunistic user access scheduling enhances the capacity of wireless networks by exploiting the multi user diversity. When frame aggregation is used, opportunistic schemes are no longer optimal, since users with high capacity links are frequently served, causing small queue sizes and low throughput. Recently, we have proposed schedulers that take queue and channel conditions into account jointly, to maximize the instantaneous throughput. In this paper, we extend this work to design a scheduler that performs block scheduling for maximizing network throughput over multiple transmission sequences. This scheduler makes use of the estimated evolution of the aggregation process by queueing theory and determines users' temporal access proportions using an approach based on the water-filling principle. Through detailed simulations, we show that our new algorithm with block scheduling offers further improvement in throughput over the previous schedulers, along with better fairness.