Antenna Grouping based Feedback Compression for FDD-based Massive MIMO Systems

TL;DR

This paper introduces an antenna grouping feedback compression method for FDD massive MIMO systems, significantly reducing feedback overhead while maintaining performance by mapping correlated antennas to representative values.

Contribution

The paper proposes the antenna group beamforming (AGB) algorithm that reduces feedback in FDD massive MIMO by grouping correlated antennas with pre-designed patterns.

Findings

Achieves significant feedback overhead reduction.

Maintains target sum rate with fewer feedback bits.

Outperforms conventional vector quantization methods.

Abstract

Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the basestation. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the basestation. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the basestation is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using pre-designed patterns. The proposed method modifies the feedback packet by introducing the concept of a header to select a suitable group pattern and a payload to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.