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Showing 1 to 3 of 3 for “"indirect learning"”.
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High performance Deep Learning based Digital Pre-distorters for RF Power Amplifiers
In this work, we present different deep learning-based digital pre-distorters and compare them based on their performance towards improving the linearity of highly non-linear power amplifiers. The simulation results show that BiLSTM based DPDs work the best in terms of improving the linearity …
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Predistortion for Nonlinear Power Amplifiers with Memory
The fusion of voice and data applications, along with the demand for high data-rate applications such as video-on-demand, is making radio frequency (RF) spectrum an increasingly expensive commodity for current and future communications. Although bandwidth-efficient digital modulation alleviates …
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Exploiting Spatial Degrees-of-Freedom for Energy-Efficient Next Generation Cellular Systems
… next generation front ends. We propose a novel indirect learning structure which adapts the channel and PA distortion iteratively by cascading adaptive zero-forcing precoding and DPD. Experimental results show that over 70% of computational complexity is saved for the proposed solution, it is …