Abstract
In this paper, we consider a system with K single-antenna client users, n/sub B/ base stations (each base station has n/sub B/ antennas) as well as a centralized controller. All the base stations operate at the same frequency and have optimal multi-user detection per base-station. A client user could be associated with a single base station at any time. We consider a general problem of uplink macroscopic scheduling where the centralized controller dynamically determines an appropriate association mapping of the K users with respect to the n/sub B/ base stations over a macroscopic time scale. We propose a novel analytical framework for the above macroscopic scheduling problems. A simple 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 multi-user detection is employed at the base station. We show that the optimal macroscopic scheduling algorithm is of exponential complexity and we propose a simple greedy algorithm as a feasible solution. It is shown that the macroscopic scheduling gain relative to the conventional approach increases with increasing n/sub B/ (due to the extra degree of freedom introduced by multiple antennas) and decreasing path loss exponent (due to large area of overlapping).
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