Maximum-likelihood detection for the multiuser code-division multiple-access (CDMA) channel is prohibitively complex. This paper considers new iterative multiuser receivers based on the expectation-maximization (EM) algorithm and related, more powerful 'space-alternating' algorithms. The latter algorithms include the SAGE algorithm and a new 'missing parameter' space-alternating algorithm that alternately updates individual parameter components or treats them as probabilistic missing data. Application of these EM-based algorithms to the problem of discrete parameter estimation (i.e., data detection) in the Gaussian multiple-access channel leads to a variety of convergent receiver structures that incorporate soft-decision feedback for interference cancellation and/or sequential updating of iterative bit estimates. Convergence and performance analyzes are based on well-known properties of the EM algorithm and on numerical simulation.
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering