Joint User Scheduling and Link Adaptation for Distributed Antenna Systems in Multi-Cell Environments with Imperfect CSI
Joint User Scheduling and Link Adaptation for Distributed Antenna Systems in Multi-Cell Environments with Imperfect CSI, Proc Advanced International Conference on Telecommunications AICT, Stuttgart, Germany, Vol. 1, pp. 1 - 5, May, 2012.
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This paper proposes a novel management scheme 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 highest possible modulation and coding schemes. This goal is achieved by using a joint channel-aware scheduling and link adaptation algorithm (including power control and adaptive modulation and coding) that allows an appropriate management of intra-cell interference. This interference management is used to create room for additional user transmissions (i.e., diversity gains) and higher-order modulation and coding schemes (i.e., decoding gains). The algorithm provides the optimum set of scheduled users, as well as their optimum serving nodes, their instantaneous transmit power levels, and their modulation and coding schemes that maximize the instantaneous 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 only a given SINR value that ensures the transmission of the chosen modulation and coding scheme with a particular value of block-error-rate (BLER). To achieve this requirement, an iterative power optimization scheme is proposed in which the set of scheduled users and their modulation and coding schemes 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. The simulation results show considerable gains in terms of throughput and reduced power consumption per node when compared to conventional cellular systems, thereby making the proposed algorithm suitable for green energy solutions.