.png){kind=icon}
.png){kind=icon}
Return
Multi-Dimensional Graph-Based Soft Iterative Receiver for MIMO-OFDM
.png){kind=icon}
PRE
AI
DOI：10.1109/TCOMM.2012.042712.110108.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A graph-based receiver is presented that iteratively performs soft channel estimation and soft data detection. Reliability information of data symbols is utilized to improve channel estimation, and in turn, soft channel estimates refine data symbol estimates. The proposed multi-dimensional factor graph introduces transfer nodes that exploit correlation of adjacent channel coefficients in an arbitrary number of dimensions (e. g. time, frequency, and spatial domain). This establishes a simple and flexible receiver structure that facilitate soft channel estimation and data detection in multi-dimensional dispersive channels, and supports arbitrary modulation and channel coding schemes. Simulation results demonstrate that the proposed multidimensional graph-based receiver outperforms iterative and non-iterative state-of-the-art receivers.
Keywords:
Channel estimation
factor graph
MIMO-OFDM
iterative decoding
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W