Capacity and fairness of distributed antenna systems in multi-cell environments with user scheduling, power control and imperfect CSI

Abstract

Distributed antenna systems (DASs) have attracted lots of attention as a method to improve the performance of future wireless networks. Capacity analysis and optimum power allocation for the physical layer of DASs have been extensively explored in the literature. However, the study of cross-layer issues, such as channel-aware scheduling and fairness evaluation, is relatively scarce. This paper partially fills this gap by addressing the downlink capacity and fairness analysis of a DAS assisted by joint user scheduling and transmit power control. The algorithm is evaluated in a multi-cell environment assuming imperfect channel state information. The algorithm exploits the spatial diversity provided by the distributed antennas in order to schedule over the same frequency band a different user attached to each one of the distributed nodes. The objective is to optimize the power levels to control the interference created between the transmissions of the selected users, thereby multiplexing as many of them as possible while maximizing capacity. To achieve this goal, a sum-rate capacity optimization with respect to the power levels is here proposed by using a gradient descent iterative technique. The result is the set of optimum user-antenna pairs to be scheduled and their optimum power levels. Inter-cell interference is calculated by reusing the results of previous simulation runs in the transmission parameters of outer-cells, thereby efficiently replicating system-level behavior. The algorithm is also evaluated in terms of fairness by using the spatial distribution of the user capacity. Capacity and fairness of the algorithm considerably outperform previous solutions, particularly in scenarios with good line-of-sight and optimum node location.