Exploiting sparse user activity in multiuser detection

Keyphrases

• Sparsity 100%
• Multiuser Detection 100%
• User Activity 100%
• Compressive Sampling 66%
• Finite alphabet 66%
• Code Division multiple Access 66%
• Multiuser Detector 66%
• Performance Improvement 33%
• Optimization Problem 33%
• Linear Regression 33%
• Equiprobable 33%
• Inactivity 33%
• Activity Factor 33%
• Least Absolute Shrinkage and Selection Operator (LASSO) 33%
• Least Square Error 33%
• Sparse Code Division multiple Access 33%
• Active Users 33%
• Operator Spectrum 33%
• Low Activity 33%
• Maximum a Posteriori Probability Criterion 33%

Engineering

• Multiuser 100%
• Sparsity 100%
• Compressive Sampling 66%
• Symbol Vector 66%
• Code Division Multiple Access 66%
• Optimisation Problem 33%
• Active User 33%
• Maximum a Posteriori 33%
• Square Error 33%
• Signal Vector 33%
• Priori Information 33%
• Posteriori Probability 33%
• Least Square 33%

Computer Science

• Sparsity 100%
• Multiuser Detection 100%
• Compressive Sampling 66%
• Code Division Multiple Access 66%
• Least Squares Methods 33%
• Optimization Problem 33%
• Feature Selection 33%
• Selection Operator 33%
• Priori Information 33%
• Posteriori Probability 33%