Joint User Scheduling and Link Adaptation for Distributed Antenna Systems in Multi-Cell Environments with Imperfect CSI

This paper proposes a novel management algorithm for distributed antenna systems (DASs) that exploits the spatial diversity of the distributed architecture in order to schedule (over the same radio resource) as many transmissions as possible with the most appropriate modulation and coding schemes (MCSs). This goal is achieved by implementing a joint user scheduling and link adaptation algorithm (including power control and adaptive modulation and coding) that allows for an appropriate management of intra-cell interference. The algorithm provides the optimum set of scheduled users, the optimum serving nodes, the transmit power levels, and the MCSs that maximize the capacity of the system. In comparison with conventional approaches, where the objective is to maximize the signal-to-interference-plus- noise ratio (SINR) of each user, in this paper the target is to satisfy a given SINR value that ensures the transmission of the chosen MCS with a particular value of block-error-rate (BLER). To achieve this goal, an iterative optimization scheme is proposed in which the set of scheduled users, the power levels, and the MCSs are modified according to channel and interference conditions. A novel method for the calculation of outer-cell interference in multi-cell configurations is also proposed. Imperfect channel state information is used throughout the system-level simulation work. Simulation results show considerable gains in terms of throughput and reduced power consumption per node when compared to conventional systems, thereby making the proposed algorithm suitable for green energy solutions.