.png){kind=icon}
Return
A Low Complexity Precoding Algorithm Based on Parallel Conjugate Gradient for Massive MIMO Systems
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2018.2870861.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Linear precoding algorithms with low complexity in massive multi-in multi-out system have always been a hot research topic to solve the problem of inter-cell interference. In this paper, we proposed a conjugate gradient-based regularized zero-forcing (CG-RZF) precoding algorithm, with which the base station can directly obtain the transmitted signal after RZF precoding and avoid directly solving the inverse matrix in RZF. Moreover, an RZF precoding algorithm based on a parallel conjugate gradient (Parallel-CG-RZF) is also proposed, which can optimize initial values and iterative process of the aforementioned CG-RZF precoding algorithm. The simulation results have shown that the proposed CG-RZF and the optimized Parallel-CG-RZF precoding algorithm can significantly improve the performance of bit error rate with fast convergence speed compared with other precoding algorithms and can reduce the number of global communications. Meanwhile, the calculation complexity of the proposed CG-RZF and Parallel-CG-RZF precoding algorithm is much lower than the optimized Chebyshev iteration algorithm.
Keywords:
Massive MIMO systems
parallel conjugate gradient
RZF
bit error rate
calculation complexity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveLow-Complexity Precoding Design for Massive Multiuser MIMO Systems Using Approximate Message PassingOAAI
OAAIShareSaveShareSave
View more