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Gaussian Phase Noise Effects on Hybrid Precoding MIMO Systems for Sub-THz Transmission

Yaya Bello, Yahia Medjahdi, Laurent Clavier, Arthur Louchart

Abstract

The sub-THz spectrum offers numerous advantages, including massive multiple-input multiple-output (MIMO) technology with large antenna arrays that enhance spectral efficiency (SE) of future systems. Hybrid precoding (HP) thus emerges as a cost-effective alternative to fully digital precoding regarding complexity and energy consumption. However, sub-THz frequencies introduce hardware challenges, particularly phase noise (PN) from local oscillators (LOs). We analyze PN impact on MIMO systems using HP, leveraging singular value decomposition and common LO architecture. We adopt the Gaussian PN (GPN) model, recognized as accurate for describing PN behavior in sub-THz transmissions. We derive a lower bound on achievable SE and provide closed-form bit error rate expressions for quadrature amplitude modulation (QAM), specifically 4-QAM and 16-QAM, under high-SNR and strong GPN conditions. These analytical results are validated through Monte Carlo simulations. We show that GPN can be effectively counteracted with a single pilot symbol in single-user MIMO systems, unlike single-input single-output systems where mitigation proves infeasible. Simulation results compare conventional QAM against polar-QAM tailored for GPN-impaired systems. Finally, we introduce perspectives for further improvements in performance and energy efficiency.

Gaussian Phase Noise Effects on Hybrid Precoding MIMO Systems for Sub-THz Transmission

Abstract

The sub-THz spectrum offers numerous advantages, including massive multiple-input multiple-output (MIMO) technology with large antenna arrays that enhance spectral efficiency (SE) of future systems. Hybrid precoding (HP) thus emerges as a cost-effective alternative to fully digital precoding regarding complexity and energy consumption. However, sub-THz frequencies introduce hardware challenges, particularly phase noise (PN) from local oscillators (LOs). We analyze PN impact on MIMO systems using HP, leveraging singular value decomposition and common LO architecture. We adopt the Gaussian PN (GPN) model, recognized as accurate for describing PN behavior in sub-THz transmissions. We derive a lower bound on achievable SE and provide closed-form bit error rate expressions for quadrature amplitude modulation (QAM), specifically 4-QAM and 16-QAM, under high-SNR and strong GPN conditions. These analytical results are validated through Monte Carlo simulations. We show that GPN can be effectively counteracted with a single pilot symbol in single-user MIMO systems, unlike single-input single-output systems where mitigation proves infeasible. Simulation results compare conventional QAM against polar-QAM tailored for GPN-impaired systems. Finally, we introduce perspectives for further improvements in performance and energy efficiency.
Paper Structure (18 sections, 57 equations, 11 figures)

This paper contains 18 sections, 57 equations, 11 figures.

Table of Contents

  1. Introduction
  2. Related Works
  3. Contributions
  4. Organization
  5. Notations
  6. System Model
  7. Channel and PN Models
  8. HP SU-MIMO Systems with CLO Architecture
  9. Derivation of bit error rate and Achievable Rate Expressions
  10. HP Systems without PN
  11. HP Systems with PN
  12. Numerical Results
  13. Simulation Environment
  14. Results
  15. Discussions
  16. ...and 3 more sections

Figures (11)

  • Figure 1: HP massive MIMO Tx system model considering CLO architecture.
  • Figure 2: Representation of the 16-QAM constellation in cartesian and polar domains.
  • Figure 3: Reference constellation scheme of a 16-PQAM($\Gamma$) modulation considering $\Gamma = \lbrace 4,8\rbrace$.
  • Figure 4: Received signal constellation for both 16-QAM and 16-PQAM(4) in the medium GPN. We consider a SNR of $30$ dB, $N_{\text{RF}}=N_{\text{s}}=4$, $N_{\text{t}}=144$, $N_{\text{r}}=36$.
  • Figure 5: SE performance as a function of the SNR considering different GPN levels. We use $N_{\text{RF}}=N_{\text{s}}=4$, $N_{\text{t}}=144$, $N_{\text{r}}=36$.
  • ...and 6 more figures