Analysis and Augmented Spatial Processing for Uplink OFDMA MU-MIMO Receiver with Transceiver I/Q Imbalance and External Interference

TL;DR

This paper proposes an augmented spatial processing method for uplink OFDMA MU-MIMO receivers that effectively mitigates I/Q imbalance and external interference, improving signal quality and robustness in complex network conditions.

Contribution

It introduces an augmented LMMSE receiver that jointly processes subcarriers and antennas to address I/Q imbalance and interference without separate calibration, extending to massive MIMO systems.

Findings

Augmented processing significantly improves SIR and SER over traditional methods.

The approach effectively mitigates I/Q imbalance and external interference.

Performance gains are maintained in massive MIMO scenarios.

Abstract

We address receiver (RX) signal processing in MIMO systems under in-phase/quadrature (I/Q) imbalance, which causes cross-talk of mirror-subcarriers in OFDM systems. We extend the typically reported single-user studies to uplink OFDMA-based multiuser MIMO, with simultaneous user multiplexing in frequency and spatial domains. We also incorporate multiple external interferers, for modeling challenging conditions in heterogeneous networks. In the signal processing developments, we exploit the augmented subcarrier processing, which processes each subcarrier jointly with its counterpart at the image subcarrier, and jointly across RX antennas. Furthermore, we derive an augmented LMMSE RX. The novel approach integrates the I/Q imbalance mitigation, interference suppression and data stream separation into a single processing stage, thus avoiding a separate transceiver calibration. Our numerical results show the signal-to-interference-plus-noise ratio and symbol-error rate of an arbitrary data stream after RX processing as a function of different system parameters. The per-subcarrier processing is shown to suffer heavily under I/Q imbalances, and being particularly sensitive to external interferers, whereas the augmented method provides efficient data stream separation and interference suppression. Finally, we extend the studies to massive MIMO framework and show that the per-subcarrier processing still suffers from performance degradation, whereas the augmented approach can fully exploit the array gain.