Resource allocation in multicell wireless networks: Some capacity scaling laws

We address the optimization of the sum rate performance in multicell interference-limited wireless networks where access points are allowed to cooperate in terms of joint resource allocation. The resource allocation policies considered here combine power control and user scheduling. Although very promising from a conceptual point of view, the optimization of the sum rate (network capacity) hinges, in principle, on tough issues such as computational complexity and the requirement for heavy receiver-to-transmitter channel information feedback across all network cells. However, we show that, in fact, distributed algorithms are actually obtainable in the asymptotic regime where the numbers of users per cell is allowed to grow to infinity. Additionally, using extreme value theory, we provide scaling laws for upper and lower bounds for the network capacity (as the number of users grows large), corresponding to two forms of distributed resource allocation schemes. We show these bounds are in fact identical asymptotically. This remarkable result suggests that distributed resource allocation is practically possible, with vanishing loss of network capacity if enough users exist.