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We address the optimization of the sum rate performance in multicellinterference-limited singlehop networks where access points are allowed tocooperate in terms of joint resource allocation. The resource allocationpolicies considered here combine power control and user scheduling. Althoughvery promising from a conceptual point of view, the optimization of the sum ofper-link rates hinges, in principle, on tough issues such as computationalcomplexity and the requirement for heavy receiver-to-transmitter channelinformation feedback across all network cells. In this paper, we show that, infact, distributed algorithms are actually obtainable in the asymptotic regimewhere the numbers of users per cell is allowed to grow large. Additionally,using extreme value theory, we provide scaling laws for upper and lower boundsfor the network capacity (sum of single user rates over all cells),corresponding to zero-interference and worst-case interference scenarios. Weshow that the scaling is either dominated by path loss statistics or bysmall-scale fading, depending on the regime and user location scenario. We showthat upper and lower rate bounds behave in fact identically, asymptotically.This remarkable result suggests not only that distributed resource allocationis practically possible but also that the impact of multicell interference onthe capacity (in terms of scaling) actually vanishes asymptotically.

Joint power control and user scheduling in multicell wireless networks: Capacity scaling laws