Performance analysis of multi-user detection of 5G overloaded sporadic system by Guoyu MA, Bo AI, Xian’an HU, Xiaobing JIANG

Subjects: Get full text

Jointing sparse recovery estimation algorithm of underwater acoustic channels with long time delay spread by Yue-hai ZHOU, Xiu-ling CAO, Dong-sheng CHEN, Feng TONG

Subjects: Get full text

A comprehensive review of metasurface-assisted direction-of-arrival estimation by Huang Min, Li Ruichen, Zou Yijun, Zheng Bin, Qian Chao, Jin Hui, Chen Hongsheng

Subjects: Get full text

Regularized threshold iteration method for impulsive noise suppression in underwater acoustic communication by Nana LI, Youming LI, Mingchen YU, Qianqian LU

Subjects: Get full text

Padding-enabled real-time high-fidelity temporal single pixel imaging by Ryota Keyaki, Jin Matsuno, Susumu Fukatsu

Subjects: Get full text

Sparse Bayesian learning-based massive multi-user detection algorithm by Pingping CHEN, Xuanda WANG, Zhaopeng XIE, Yi FANG, Jiahui CHEN

Subjects: Get full text

An overview of artificial intelligence assisted channel estimation by Kun LI, Jing ZHANG, Xiao LI, Shi JIN

Subjects: Get full text

Partial-norm-constrained sparse recovery algorithm and its application on single carrier underwater-acoustic-data telemetry by Feiyun WU, Kunde YANG, Feng TONG

Subjects: “…compressive sensing…”
Get full text

A compressive data gathering method based on El Gamal cryptography by Xiaohan YU, Keming DONG, Xia LI, Chao CHEN

Subjects: Get full text

Joint sparse model based data reconstruction algorithm for wireless sensor network by Yi-yin LIU, Guo-rui LI, Li TIAN

Subjects: Get full text

Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA by Yong LIAO, Zhirong CAI

Subjects: Get full text

CS-based data collection method for airborne clustering WSN by HOUWei Z, INGBo J, UANGYi-feng H, IAOXiao-xuan J, UJia-xing H, IANGWei L

Subjects: Get full text

High-Speed Target HRRP Reconstruction Based on Fast Mean-Field Sparse Bayesian Unrolled Network by Hang Dong, Fengzhou Dai, Juan Zhang

Subjects: Get full text

A Novel Gridless Non-Uniform Linear Array Direction of Arrival Estimation Approach Based on the Improved Alternating Descent Conditional Gradient Algorithm for Automotive Radar Sys... by Mingxiao Shao, Yizhe Fan, Yan Zhang, Zhe Zhang, Jie Zhao, Bingchen Zhang

Subjects: “…compressive sensing…”
Get full text

Compressive SAR Imaging Based on Modified Low-Rank and Sparse Decomposition by Jeong-Il Byeon, Wookyung Lee, Jihoon Choi

Subjects: Get full text

A novel transmission-augmented deep unfolding network with consideration of residual recovery by Zhijie Zhang, Huang Bai, Ljubiša Stanković, Junmei Sun, Xiumei Li

Subjects: “…Compressive sensing…”
Get full text

RESEARCH ON COMPRESSION AND RECONSTRUCTION OF TUBE FOULING ULTRASONIC TESTING SIGNAL BASED ON IMPROVED COSAMP by WANG TongTong, SUN LingFang

Subjects: Get full text

Construction method of optimal codebook based on Zadoff-Chu matrix by Yubo LI, Shengyi LIU, Jingjing ZHANG, Dongyan JIA

“…Codebooks with low-coherence have wide utilization in code division multiple access (CDMA) communications,quantum information theory,compressed sensing and so on.In order to expand the number of codebooks,the restrictions on the transformation matrix were relaxed.Based on the Zadoff-Chu matrix,new codebooks were constructed using the difference set,almost difference set,and finite field character sum.The proposed codebooks were optimal or near optimal according to the Welch bound or Levenstein bound.Through experimental simulation,it is found that the deterministic measurement matrices constructed using these codebooks also have good performance in the process of compressed sensing.…”
Get full text

SCWOMP Recovery Algorithm for 5G MIMO Communication Symbol Detection by Tao Fu, Yanfeng Yu, Cheng Liu

“…Then, the improved compressed sensing recovery algorithm is simulated and analyzed. …”
Get full text

Joint channel and impulsive noise estimation method for MIMO-OFDM systems by Xinrong LYU, Youming LI, Qiang GUO

“…Aiming at the impulsive noise occurring in MIMO-OFDM systems， a joint channel and impulsive noise estimation method based on the multiple measurement vector compressed sensing theory was proposed.The channel impulse response and the impulsive noise were combined to form a row sparse matrix to be estimated， and a multiple measurement vector compressed sensing model based on all subcarriers was constructed.As the measurement matrix was partially unknown due to the presence of unknown transmitted symbols in data tones， the multiple response sparse Bayesian learning theory and expectation maximization framework were adopted to jointly estimate the channel impulse response， the impulsive noise， and the data symbols which were regarded as unknown parameters.Compared with the existing methods， the proposed method not only utilizes all subcarriers but also does not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed method achieves significant improvement on the channel estimation and bit error rate performance.…”
Get full text