  We address the problem of uplink co-operative reception with constraints on
both backhaul bandwidth and the receiver aperture, or number of antenna signals
that can be processed. The problem is cast as a network utility (weighted sum
rate) maximization subject to computational complexity and architectural
bandwidth sharing constraints. We show that a relaxed version of the problem is
convex, and can be solved via a dual-decomposition. The proposed solution is
distributed in that each cell broadcasts a set of {\em demand prices} based on
the data sharing requests they receive. Given the demand prices, the algorithm
determines an antenna/cell ordering and antenna-selection for each scheduled
user in a cell. This algorithm, referred to as {\em LiquidMAAS}, iterates
between the preceding two steps. Simulations of realistic network scenarios
show that the algorithm exhibits fast convergence even for systems with large
number of cells.
