Decentralized Groupwise Expectation Propagation Detector for Uplink Massive MU-MIMO Systems

Hua, Li; Dong, Yuanyuan; Gong, Caihong; Wang, Xiyuan; Dai, Xiaoming

doi:10.1109/jiot.2022.3222361

Cited by 3 publications

(7 citation statements)

References 36 publications

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“…To introduce the information sharing between DUs, following [7] , we further studied the FAMP detector for Daisy-Chain architecture. In this architecture, DUs are connected sequentially, let…”

Section: Famp Detector For Daisy-chain Architecturementioning

confidence: 99%

“…In [4]- [7] , the expectation propagation (EP) based signal detection method was applied to the Star architecture. Although this method achieves good detection performance, there is still high computational complexity with massive BS antennas.…”

Section: Introductionmentioning

confidence: 99%

“…Uplink massive MIMO signal detection method for Daisy-Chain architecture was studied in [7]- [9] . This architecture does not require a CU, DUs are serially connected based on a daisy chain topology structure.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized signal detection via first-order approximate message passing for uplink massive MIMO systems

Zong,

Dai

2023

Third International Conference on Optics and Communication Technology (ICOCT 2023)

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Massive MIMO technology has been used in wireless communication systems, due to its high spectral efficiency. However, existing baseband processing methods for uplink massive MIMO systems mainly rely on centralized baseband processing architectures, which results in high data volume between base station antennas and baseband processing unit, and leads to high computational complexity in the single baseband processing unit. In response to these problems, some decentralized baseband processing (DBP) architectures have been presented recently. This paper investigates the performance of two kinds of DBP architectures, i.e., the Star architecture with a fusion unit and Daisy-Chain architecture without a fusion unit. For the Star architecture, a first-order approximate message passing based detection method is used in the decentralized-processing units (DUs) to reduce the computational complexity while keeping a comparable detection performance, compared to the expectation propagation based DBP detection method. Furthermore, for the Daisy-Chain architecture, a sequential detection scheme and a local fusion method is utilized to improve the detection performance, compared to the Star architecture. Simulation results show that the proposed methods exhibit desirable tradeoff between detection accuracy and computational complexity.

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Section: Famp Detector For Daisy-chain Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Decentralized signal detection via first-order approximate message passing for uplink massive MIMO systems

Zong,

Dai

2023

Third International Conference on Optics and Communication Technology (ICOCT 2023)

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“…The EP framework was also used to develop decentralized detection schemes for MaMIMO systems in [17], [24]- [26]. In these works, the computational complexity was reduced compared to centralized schemes by processing the signals received by antenna sub-arrays locally via EP message passing and then combining the messages from sub-arrays at the CPU.…”

Section: Introductionmentioning

confidence: 99%

“…In [25], the authors introduced a pre-processing based on QR-factorization and a variance compensation scheme in the decentralized detector of [24]. In [26], two decentralized EP detection approaches were proposed, the first based on user grouping and, thus, group-wise joint detection, and the second on a daisy-chain architecture.…”

Section: Introductionmentioning

confidence: 99%

Bilinear Expectation Propagation for Distributed Semi-Blind Joint Channel Estimation and Data Detection in Cell-Free Massive MIMO

Karataev,

Forsch,

Cottatellucci

2024

IEEE Open J. Signal Process.

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We consider a cell-free massive multiple-input multiple-output (CF-MaMIMO) communication system in the uplink transmission and propose a novel algorithm for blind or semi-blind joint channel estimation and data detection (JCD). We formulate the problem in the framework of bilinear inference and develop a solution based on the expectation propagation (EP) method for both channel estimation and data detection. We propose a new approximation of the joint a posteriori distribution of the channel and data whose representation as a factor graph enables the application of the EP approach using the messagepassing technique, local low-complexity computations at the nodes, and an effective modeling of channeldata interplay. The derived algorithm, called bilinear-EP JCD, allows for a distributed implementation among access points (APs) and the central processing unit (CPU) and has polynomial complexity. Our simulation results show that it outperforms other EP-based state-of-the-art polynomial time algorithms.

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OTFS-PDMA Scheme With EPA-Based Receivers for High-Mobility IoT Networks

Li,

Gong,

et al. 2024

IEEE Trans. Wireless Commun.

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Decentralized Groupwise Expectation Propagation Detector for Uplink Massive MU-MIMO Systems

Cited by 3 publications

References 36 publications

Decentralized signal detection via first-order approximate message passing for uplink massive MIMO systems

Decentralized signal detection via first-order approximate message passing for uplink massive MIMO systems

Bilinear Expectation Propagation for Distributed Semi-Blind Joint Channel Estimation and Data Detection in Cell-Free Massive MIMO

OTFS-PDMA Scheme With EPA-Based Receivers for High-Mobility IoT Networks

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