Iterative interference alignment techniques for broadband wireless systems with limited feedback

Interference alignment (IA) is a promising technique that allows high capacity gains in interfering channels. In this paper we consider iterative IA techniques for the downlink of OFDM-based (Orthogonal Frequency Division Multiplexing) broadband wireless systems with limited feedback. A quantized version of the channel state information (CSI) associated to the different links between base station (BS) and user terminal (UT) is feedback from the UT to the BS, which sends it to the other BSs through a limited-capacity backhaul network. This information is employed by each BS to perform the overall IA design. Our channel quantization method requires much less complexity than random vector quantization based techniques and requires the quantization of a fraction of the channel frequency response samples. The results have shown that a small number of quantization bits per multipath component is enough to allow performance close to one obtained with perfect channel knowledge.