Abstract
As high-frequency bands are considered for wireless communications, the in-phase and quadrature imbalance caused by the local oscillator and frequency mixer is becoming more severe. This study proposed an I/Q phase imbalance estimator based on the self-attention mechanism, which captures long-range dependencies to learn the relations among the input data symbols. Simulation results showed that the proposed self-attention-based method reduces the estimation error compared with the conventional methods. The proposed method can reduce the required data symbols to estimate the I/Q imbalance by half while achieving better performance at high signal-to-noise ratio regimes.
| Original language | English |
|---|---|
| Pages (from-to) | 3262-3266 |
| Number of pages | 5 |
| Journal | IEEE Communications Letters |
| Volume | 25 |
| Issue number | 10 |
| DOIs | |
| State | Published - 1 Oct 2021 |
Keywords
- I/Q imbalance estimation
- Machine learning for communications
- self-attention