Development of a Modified Adaptive Independent Component Analysis Scheme to Improve CSI in M-MIMO

Mustapha Mubarak, Tekanyi A. M. S., Sani S. M.

Abstract


A lot of techniques had been developed to obtain near perfect Channel State Information (CSI) in Massive Multiple Input Multiple Output (M-MIMO). Adaptive Independent Component Analysis (AICA) was another scheme developed with the limitation of having the same performance with conventional Independent Component Analysis (ICA). AICA had same performance with conventional Independent Component Analysis (ICA) with reduced computational time (run time), thus there was need to improve the performance in terms of reduced channel estimation error. This research focused on blind channel estimation technique based on AICA through normalizing the covariance matrix and modifying the Gram-Schmidt as a de-correlation algorithm instead of the classical Gram-Schmidt used in AICA. Hence, it was termed Modified Adaptive Independent Component Analysis (MAICA). The modified technique was implemented in a Graphical User Interface (GUI) using MATLAB R2019a incorporated with COST2100 channel model. Simulation results showed that the developed MAICA provided a better CSI estimate using Root Mean Square Error (RMSE) as performance metrics compared to AICA. The average RMSE was also found to reduce from   to   which translated to 17.4% reduction in error. In conclusion, the developed scheme had a better performance as compared to the work of Peken et al., (2017) but became inefficient as the number of symbols increased.

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References


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