paper-with-me

Papers

Sequential HW-Aware Precoding: Over-the-air cancellation of HWI in Downlink Cell-Free Massive MIMO with Serial Fronthaul

2025-03-21 · Antoine Durant, Asma Mabrouk, Rafik Zayani

This paper addresses the critical challenge of mitigating hardware impairments (HWIs) in downlink cell-free massive MIMO (CF-mMIMO) networks while ensuring computational scalability. We propose a novel sequential hardware-aware (HW-aware) precoding technique that leverages the serial fronthaul topology to perform over-the-air HWI cancellation. This approach involves sequentially exchanging approximated user-perceived distortion information among successive access points (APs) for over-the-air HWI mitigation. Each AP independently computes its spatial multiplexing weights and transmits signals that counteract the distortions introduced by the preceding AP. We develop a problem formulation and present a closed-form solution for this method. For performance evaluation, we study two reference methods taken either from centralized massive MIMO literature (Tone Reservation [TR]) or tailored for CF-mMIMO networks (PAPR-aware precoding), both focusing on reducing the PAPR of OFDM signals in the downlink. Results indicate that the sequential HW-aware approach achieves a substantial increase in spectral efficiency (SE) in high-distortion scenarios, with an average SE increase factor of 1.8 under severe distortions. Additionally, the proposed method, which is executed locally, demonstrates better scalability, achieving a reduction of up to 40\% and 72\% in the total number of complex multiplications compared to the PAPR-aware and TR approaches, respectively. Finally, the sequential HW-aware precoder offers high performance even when applied to cost-effective APs with few antennas, presenting a promising and practical solution for HWI compensation in CF-mMIMO systems with serial fronthaul.

📄 PDF Abstract BibTeX arXiv:2503.17562

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Cache-Aided Massive MIMO: Linear Precoding Design and Performance Analysis

2019-03-22

In this paper, we propose a novel joint caching and massive multiple-input multiple-output (MIMO) transmission scheme, referred to as cache-aided massive MIMO, for advanced downlink cellular communications. In addition t…

Sum Rate Maximization in the Constant Envelope MIMO Downlink with the RZF Precoder

2024-11-05 · Ferhad Askerbeyli, Wen Xu, Josef A. Nossek

Feeding power amplifiers (PAs) with constant envelope (CE) signals is an effective way to reduce the power consumption in massive multiple-input-multiple-output (MIMO) systems. The nonlinear distortion caused by CE signa…

Quantization

Quantisation-aware Precoding for MU-MIMO with Limited-capacity Fronthaul

2022-02-17 · Yasaman Khorsandmanesh, Emil Björnson, Joakim Jaldèn

Base stations in 5G and beyond use advanced antenna systems (AASs), where multiple passive antenna elements and radio units are integrated into a single box. A critical bottleneck of such a system is the digital fronthau…

Quantization

Optimized Precoding for MU-MIMO With Fronthaul Quantization

2022-09-05 · Yasaman Khorsandmanesh, Emil Björnson, Joakim Jaldén

One of the first widespread uses of multi-user multiple-input multiple-output (MU-MIMO) is in 5G networks, where each base station has an advanced antenna system (AAS) that is connected to the baseband unit (BBU) with a …

Quantization

Knowledge Distillation-aided End-to-End Learning for Linear Precoding in Multiuser MIMO Downlink Systems with Finite-Rate Feedback

2020-08-10 · Kyeongbo Kong, Woo-Jin Song, Moonsik Min

We propose a deep learning-based channel estimation, quantization, feedback, and precoding method for downlink multiuser multiple-input and multiple-output systems. In the proposed system, channel estimation and quantiza…

BinarizationKnowledge DistillationQuantization