Interference alignment with hierarchical random vector quantization for MIMO interference channels

Interference alignment (IA) boosts system throughput by effectively mitigating interference for high signal-to-noise (SNR) with perfect and global channel state information (CSI). In a system employ frequency division duplex (FDD), CSI is conveyed by feedback channel. Random vector quantization (RVQ) is widely used to reduce the overhead of feedback because it is easy to design and near-optimal, but suffer high computational complexity to find the best codeword. This paper derives the upper loss of the IA based system throughput due to quantization error of CSI, and proposes an IA scheme with hierarchical RVQ (HRVQ) to reduce effectively the computational complexity in the best codeword selection for CSI.