Reducing the Codeword Search Complexity of FDD Moderately Large MIMO Beamforming Systems

Abstract

It is of great interest to develop larger scale multiple-input multiple-output (MIMO) technology based on frequency division duplexing (FDD) for backward compatibility with existing standards and already deployed cellular networks. One hindrance to the FDD approach is the complexity of the codeword search performed by the receiver, which is known to scale with the number of transmit antennas $N_{t}$ in a system. The codeword search complexity does not scale linearly and soon becomes infeasible even for the not-so-massive MIMO systems expected in the very near future. We address this problem by proposing a natural sequence-based orthogonal codebook and an intra-array interference magnitude (IIM) framework for MIMO beamforming based on quantized equal gain transmission that altogether tremendously simplifies the codeword search problem. We also present an assessment on the quality of the codeword selected by the proposed framework that explains it’s near optimal performance, and, provide detailed codeword search complexity quantification. Finally, we provide simulation analyses of beamforming gain under time selective fading channels and an FDD MIMO system transmit delay model. Our analyses indicate that despite significantly reducing complexity, the proposed IIM framework executed by already commercialized processors is capable of approaching the ideal performance of an static system even in the presence of time-selectivity inherent to high-speed mobile communications. Our analyses also quantify the impact of feedback delay on average beamforming gain of moderately large transmit arrays.