Vector precoding based on Geometric Mean Decomposition for MIMO transmission system

Geng, Xuan; Jiang, Lingge; He, Chen

doi:10.1109/icnnsp.2008.4590356

Cited by 1 publication

(3 citation statements)

References 8 publications

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“…However, all the aforementioned algorithms for the SC structures are linear algorithms, it may cause noise enhancement and performance degradation, and it is hard to maintain good performance in noise environment 10 . To solve this problem, several nonlinear algorithms are proposed, including Dirty Paper Coding (DPC), 11 Vector Precoding (VP) 12 and Tomlinson‐Harashima (TH) Precoding 13 and so forth. DPC is developed to eliminate interference between signals, but DPC unavoidably possesses the channel capacity loss on account of quantization 11 .…”

Section: Introductionmentioning

confidence: 99%

“…DPC is developed to eliminate interference between signals, but DPC unavoidably possesses the channel capacity loss on account of quantization 11 . As a suboptimal nonlinear VP, the original signal vector is added to the additional disturbance vector to form the disturbance signal vector, which reduces the total transmitted power and has better performance than linear precoding 12 . Compared with DPC and VP, TH precoding has certain advantages 14 .…”

Section: Introductionmentioning

confidence: 99%

“…11 As a suboptimal nonlinear VP, the original signal vector is added to the additional disturbance vector to form the disturbance signal vector, which reduces the total transmitted power and has better performance than linear precoding. 12 Compared with DPC and VP, TH precoding has certain advantages. 14 The modular operator in TH model's nonlinear elements can effectively improve its anti-interference performance by disturbing the data stream.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid TH precoding with subarray connection for multi‐user mmWave MIMO systems

Guan

Tian

et al. 2023

Trans Emerging Tel Tech

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Existing linear algorithms based on subarray connection (SC) structures may cause noise enhancement and performance degradation. To solve this problem, this paper presents a nonlinear hybrid Tomlinson‐Harashima precoding (THP) algorithm based on SC structure, named as THP‐SC algorithm. In the proposed algorithm, the sum‐rate optimization problem can be transformed into two equivalent optimization subproblems including the transmitter optimization subproblem and the receiver optimization subproblem. These two subproblems are easy to solve. Furthermore, the analog precoding and combining matrices of the optimization subproblem are solved by a new improved successive interference cancelation (SIC) algorithm based on the singular value threshold shrinkage (SVS), which can effectively reduce the computational complexity while eliminating the interference. In the end, the digital precoding and combining matrices are obtained by TH method. Through the joint optimization of the transmitter and receiver matrices in the system, the optimal solution is obtained by alternate iteration of the matrices. In this paper, a more realistic line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) channel system is also considered. Simulations verify that the proposed algorithm can improve the spectral efficiency and energy efficiency to some extent with a comparable complexity compared to the previous works.

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