A UE-Assisted Hybrid Transmission Scheme for Asynchronous Cell-Free Massive MIMO Systems With Imperfect RF Chains

A user equipment (UE)-assisted hybrid coherent and noncoherent transmission scheme is designed for cell-free massive multiple-input–multiple-output (MIMO), operating in the presence of phase offsets caused by both imperfect radio frequency (RF) chains and asynchronous reception. First, considering the effects of both factors, we derive closed-form spectral efficiency (SE) expressions for hybrid transmission under conjugate beamforming and zero-forcing (ZF) precoders. Based on these expressions, we introduce the concept of superposition gain to clarify the rationality of hybrid transmission. To leverage its advantages, we propose an access point (AP) grouping algorithm and its enhanced version, which groups the serving APs based on downlink (DL) equivalent channel at the UE side. Since the DL equivalent channel incorporates information on both RF and delay phase offsets, hybrid transmission based on this algorithm can simultaneously address both. Additionally, to implement this UE-assisted hybrid transmission with low overhead, we propose a signaling interaction strategy that extends traditional processes by introducing ZF-based DL beamforming pilot transmission for obtaining the DL equivalent channel, along with indication method for reporting the grouping results. Moreover, to further improve performance, a sequential convex approximation power allocation algorithm is proposed for hybrid transmission. Finally, simulations show that UE-assisted hybrid transmission achieves nearly fivefold improvement in 95%-likely SE over coherent transmission in the presence of both RF and delay phase offsets.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-09-09
DOI
https://doi.org/10.1109/jiot.2025.3607883
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

A UE-Assisted Hybrid Transmission Scheme for Asynchronous Cell-Free Massive MIMO Systems With Imperfect RF Chains

Yongzhao Li, Yuhan Ruan, Hao Liu, Tao Yang et al.
IEEE Internet of Things Journal
Advanced MIMO Systems Optimization
article

A UE-Assisted Hybrid Transmission Scheme for Asynchronous Cell-Free Massive MIMO Systems With Imperfect RF Chains

Yongzhao Li, Yuhan Ruan, Hao Liu, Tao Yang, Tao Li, Rui Zhang, Liyuan Qin
article en

Abstract

A user equipment (UE)-assisted hybrid coherent and noncoherent transmission scheme is designed for cell-free massive multiple-input–multiple-output (MIMO), operating in the presence of phase offsets caused by both imperfect radio frequency (RF) chains and asynchronous reception. First, considering the effects of both factors, we derive closed-form spectral efficiency (SE) expressions for hybrid transmission under conjugate beamforming and zero-forcing (ZF) precoders. Based on these expressions, we introduce the concept of superposition gain to clarify the rationality of hybrid transmission. To leverage its advantages, we propose an access point (AP) grouping algorithm and its enhanced version, which groups the serving APs based on downlink (DL) equivalent channel at the UE side. Since the DL equivalent channel incorporates information on both RF and delay phase offsets, hybrid transmission based on this algorithm can simultaneously address both. Additionally, to implement this UE-assisted hybrid transmission with low overhead, we propose a signaling interaction strategy that extends traditional processes by introducing ZF-based DL beamforming pilot transmission for obtaining the DL equivalent channel, along with indication method for reporting the grouping results. Moreover, to further improve performance, a sequential convex approximation power allocation algorithm is proposed for hybrid transmission. Finally, simulations show that UE-assisted hybrid transmission achieves nearly fivefold improvement in 95%-likely SE over coherent transmission in the presence of both RF and delay phase offsets.

IEEE Internet of Things JournalVol. 12(22)
Xidian University (CN), Nokia (China) (CN)
Openalex Percentile: Top 76%
Advanced MIMO Systems Optimization
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