Feedback-efficient agile scheduling-beamforming for network MIMO OFDMA systems with realistic channel models

The acquisition of channel state information is a pressing issue in the implementation of network multi-input multi-output (MIMO) systems, where the base-stations coordinate across multiple cells for intercell interference mitigation. This paper proposes a two-stage channel quantization and feedback mechanism named agile scheduling-beamforming (ASB) for the downlink network MIMO system employing both spatial multiplexing and orthogonal frequency-division multiple-access (OFDMA). The proposed scheme polls the users for their best set of spatial-frequency resource blocks, then schedules the users according to the fairness criterion, and finally asks the selected users to feedback finer channel quantization. This paper utilizes insights derived from the scaling law of the optimal quantization bit allocation for this scheme, and evaluates its performance on realistic channel models. Rate map simulations based on ray-tracing-based wireless propagation models of realistic urban small-cell deployment show that the proposed scheme can already approach the performance of network MIMO with full channel state information with only modest amount of channel feedback.