Abstract

The hierarchical cooperation (HC) scheme is known to exhibit linear scaling from the viewpoint of information theory under the assumption of no control and data frame overhead. However, if we consider the control and data frame overheads of the HC scheme in a more practical ad-hoc network environment, the scaling law of the aggregate throughput is expected to be far from linear scaling. In this paper, we observe the effect of the control and data frame overheads on the capacity scaling of the HC scheme. From the results of performance evaluation, we find that the data frame overhead only affects the degradation of the aggregate throughput in proportion to the data frame overhead ratio. Moreover, the control overhead affects the trend of the aggregate throughput. The slope of the aggregate throughput converges to near zero as the total number of nodes, N, increases, and the aggregate throughput becomes saturated for any given number of stages, h. The significant performance degradation in the aggregate throughput is inevitable due to the control and data frame overheads. Therefore, it is not always good to use as many stages as possible, and, thus, there exists an optimal number of stages according to the given system parameters.

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