A theoretical framework of uplink macroscopic optimization for multicell systems with multiuser detection

In this paper, we consider a system with K client users (single antenna), n_B base stations (each has single antenna), as well as a centralized controller. All the base stations operate at the same frequency and have optimal multiuser detection (MUD) per base station. The MUD at the base station is able to cancel only the intracell interference but not the intercell interference. A client user is associated with a single base station at any time. We consider a general problem of uplink macroscopic optimization (or macroscopic resource management) where the centralized controller dynamically determines an appropriate association mapping of the K users with respect to the n_B base stations over a macroscopic time scale. We propose a novel multicell capacity region as well as an analytical framework for the above macroscopic optimization problem. A simple conventional rule is to associate a user with the strongest base station (camp-on-the-strongest-cell) and this has been widely employed in conventional cellular systems. However, based on the optimization framework, we found that this conventional approach is in fact not optimal when MUD is employed at the base station. We show that the optimal macroscopic optimization algorithm is of exponential complexity and we propose a simple greedy algorithm as a feasible solution. It is shown that the macroscopic optimization gain over the conventional approach increases with decreasing path loss exponent due to large area of overlapping.