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Deep Reinforcement Learning-aided Transmission Design for Energy-efficient Link Optimization in Vehicular Communications
This letter presents a deep reinforcement learning (DRL) approach for transmission design to optimize the energy efficiency in vehicle-to-vehicle (V2V) communication links.
A Low-Complexity Range Estimation with Adjusted Affine Frequency Division Multiplexing Waveform
Affine frequency division multiplexing (AFDM) is a recently proposed communication waveform for time-varying channel scenarios.
Digital Self-Interference Cancellation With Robust Multi-layered Total Least Mean Squares Adaptive Filters
In each layer, our proposed m-MTLS estimator first employs an M-estimate total least mean squares (MTLS) algorithm to eliminate residual SI from the received signal and give a new estimation of the RT channel.
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