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Found 7 papers, 3 papers with code
Superimposed Pilot-based Channel Estimation for RIS-Assisted IoT Systems Using Lightweight Networks
Specifically, at the user equipment (UE), the pilot for CE is superimposed on the uplink user data to improve the spectral efficiency and energy consumption for IoT systems, and two lightweight networks at the base station (BS) alleviate the computational complexity and processing delay for the CE and symbol detection (SD).
Transfer Learning-based Channel Estimation in Orthogonal Frequency Division Multiplexing Systems Using Data-nulling Superimposed Pilots
To this end, a novel CE network for the DNSP scheme in OFDM systems is structured, which improves its estimation accuracy and alleviates the model mismatch.
Mapping evolving population geography in China
China's demographic changes have important global economic and geopolitical implications.
Enhanced ELM Based Channel Estimation for RIS-Assisted OFDM systems with Insufficient CP and Imperfect Hardware
Reconfigurable intelligent surface (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems have aroused extensive research interests due to the controllable communication environment and the performance of combating multi-path interference.
Joint Model and Data Driven Receiver Design for Data-Dependent Superimposed Training Scheme with Imperfect Hardware
Data-dependent superimposed training (DDST) scheme has shown the potential to achieve high bandwidth efficiency, while encounters symbol misidentification caused by hardware imperfection.
Understanding the mesoscopic scaling patterns within cities
Understanding quantitative relationships between urban elements is crucial for a wide range of applications.
Physics and Society
Group Sparse Bayesian Learning for Active Surveillance on Epidemic Dynamics
To address the challenge, we study the problem of active surveillance, i. e., how to identify a small portion of system components as sentinels to effect monitoring, such that the epidemic dynamics of an entire system can be readily predicted from the partial data collected by such sentinels.
