Abstract

In this paper, we investigate channel estimation and robust detection for uplink massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems with in-phase and quadrature-phase imbalances (IQI). We represent the received signal with a real-valued model, where the combination of the IQI and the wireless channel is treated as the effective channel. Based on the real-valued model, we then perform the minimum mean square error (MMSE) criterion based estimation for the effective channel. We use adjustable phase shift pilots (APSPs) to reduce the pilot overhead and verify that the MSE of the effective channel estimation can be minimized by scheduling the pilot phase shifts properly. We propose a pilot phase shift scheduling algorithm based on the covariance matrices of the effective channels. Since the channel estimation performance might be degraded due to using APSPs, we develop an MMSE criterion based data detection scheme which is robust to the channel estimation error. Using operator-valued free probability theory, we derive an asymptotic deterministic equivalent for the ergodic achievable sum rate of the proposed detection scheme. The performance of the channel estimation with APSPs and the robust data detection is demonstrated via extensive numerical results.

Highlights

  • Massive multiple-input multiple-output (MIMO) systems, which deploy large numbers of antennas at the base stations (BSs), can serve a relatively large number of user terminals (UTs) at the same time and frequency resources simultaneously [1]

  • We show that the channel estimation MSE can be minimized by scheduling the pilot phase shifts to make the wireless channel power distribution in the angle-delay domain non-overlapping, which verifies the feasibility of the adjustable phase shift pilots (APSPs) for the IQ imbalanced case

  • Since we have shown that is invertible in Appendix B, by substituting the effective channel estimates obtained in Proposition 1 into (44), we can obtain that the detection error is independent on the in-phase and quadrature-phase imbalances (IQI) coefficients

Read more

Summary

INTRODUCTION

Massive multiple-input multiple-output (MIMO) systems, which deploy large numbers of antennas at the base stations (BSs), can serve a relatively large number of user terminals (UTs) at the same time and frequency resources simultaneously [1]. The computational cost required for these solutions is prohibitive for practical massive MIMO systems Another method is to design the data detection or IQI compensation scheme based on the estimate of the effective channel [12], [20]–[28]. We adopt operator-valued free probability theory to derive an asymptotic deterministic equivalent for the ergodic achievable sum rate of our proposed data detection that takes the IQI into account. Our Contributions: In this paper, we investigate channel estimation with adjustable phase shift pilots (APSPs) and robust data detection for IQ imbalanced uplink massive MIMO-OFDM systems. The advancements of this paper from the conference version [40] are as follows: 1) Since IQI is considered, we propose an MMSE channel estimation with APSPs based on an augmented real-valued model.

NOTATIONS
PILOT PHASE SHIFT SCHEDULING
ROBUST DATA DETECTION
ROBUST DATA DETECTION BASED ON MMSE
G T WT 2
NUMERICAL RESULTS
MSE PERFORMANCE OF THE EFFECTIVE CHANNEL ESTIMATION
SPECTRAL EFFICIENCY COMPARISON
CONCLUSION AND FUTURE
SPECTRAL NORM OF
ASYMPTOTIC DETERMINISTIC EQUIVALENT FOR THE

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.