Affine Invariant Semi-Blind Receiver: Joint Channel Estimation and High-Order Signal Detection for Multiuser Massive MIMO-OFDM Systems

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Authors: Erdeng Zhang, Shuntian Zheng, Sheng Yi Wu, Haoge Jia, Zhe Ji, Ailing Xiao
Cited by: 0
References: 40

Abstract

Massive multiple-input and multiple-output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) are foundational for downlink multiuser (MU) systems in future wireless networks, for their ability to enhance spectral efficiency and support a large number of users. However, high user density intensifies severe inter-user interference (IUI) and pilot overhead. Consequently, existing blind and semi-blind channel estimation (CE) and signal detection (SD) algorithms suffer performance degradation and increased complexity, and are further challenged by frequency-selective channels with high-order modulation demands. To this end, this paper proposes a novel semi-blind joint channel estimation and signal detection (JCESD) method. Specifically, the proposed approach employs a hybrid precoding architecture to suppress IUI. Furthermore, we formulate JCESD as a non-convex optimization exploiting constellation affine invariance. A few pilots are used to achieve coarse estimation for initialization and ambiguity resolution. For high-order modulations, a data augmentation mechanism utilizes the symmetry of quadrature amplitude modulation (QAM) constellations to increase the effective number of samples. To address frequency-selective channels, CE accuracy is then enhanced via an iterative refinement strategy that leverages improved SD results. Simulation results demonstrate an average throughput gain of 11% over pilot-based methods in MU scenarios, highlighting its potential for improving spectral efficiency.

Fields of Study & Subjects

Advanced Wireless Communication Techniques Advanced MIMO Systems Optimization PAPR reduction in OFDM

Publication details

Journal / source
IEEE Transactions on Communications
Volume
74
Pages
4384–4399
Publication date
1 January 2026