A5087319572- Indoor and Outdoor Localization Technologies
- Underwater Vehicles and Communication Systems
- Underwater Acoustics Research
- Optical Wireless Communication Technologies
- Wireless Signal Modulation Classification
- Radio Wave Propagation Studies
- Image Enhancement Techniques
- Advanced Wireless Communication Techniques
- Advanced MIMO Systems Optimization
- Microwave Imaging and Scattering Analysis
- Photoacoustic and Ultrasonic Imaging
- Sparse and Compressive Sensing Techniques
Xiamen University
2021-2023
It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because severe propagation conditions, including frequency-selective property, high relative mobility, long latency, and intensive ambient noise, etc. To this end, a deep unfolding neural network based approach is proposed, in which multiple layers mimic iterations classical iterative sparse approximation algorithm extract inherent features by exploiting learning, scheme on...
In this paper, a three-dimensional (3D) indoor visible light localization method based on machine learning and deep is presented, which able to obtain accurate 3D spatial coordinates of the user, including location plane height in room. The approaches adopted for include two typical algorithms, i.e., support vector random forest. For approach, neural networks composed full connected layers are employed training different scenarios. formulated learning-based framework, received signal...
It is well known that the underwater acoustic channel (UAC) has physical characteristic of sparse structure due to significant multipath effect. To improve performance UAC estimation, with knowledge on sparsity in mind we propose a novel method called Deep Learning based Estimation (DL-UACE) this paper. The DL-UACE combines conventional iterative recovery algorithm approximate message passing (AMP) deep neural network (DNN) construct sparsity-aware DNN for learning inherent UAC. Furthermore,...
Due to the limitation of energy supply and requirements high reliability in mission-critical Internet Medical Things (IoMT), efficient reliable transmission sensing siganl implantable medical devices (IMDs) is still a challenge. In order improve spectrum efficiency reliability, this paper, Generative Adversarial Network-enabled Sparse Compression Recovery (GAN-SCR) scheme proposed by exploiting physical knowledge sparsity, which compressively measures sparse IMD signal transmitter, recovers...
Channel estimation for multi-user multiple input output (MIMO) systems has been recognized as a key issue in next generation wireless communication. The channel is approximately sparse due to the transmission noise effect, which limits performance of existing method. To address this problem, denoising deep learning based method MU-MIMO system proposed paper. Utilizing algorithm remove perturbations estimation, can obtain accurate feature channels system. Moreover, accuracy and spectrum...