BCJR algorithm is an exact and efficient algorithm to compute the marginal posterior distributions of state variables and pairs of consecutive state variables of a trellis structure. Due to its overwhelming complexity, reduced complexity variations, such as the M-BCJR algorithm, have been developed. In this paper, we propose improvements upon the conventional M-BCJR algorithm based on modified active state selection criteria. We propose selecting the active states based on estimates of the fixed-lag smoothed distributions of the state variables. We also present Gaussian approximation techniques for the low-complexity estimation of these fixed-lag smoothed distributions. The improved performance over the M-BCJR algorithm is shown via computer simulations.
Bibliographical notePublisher: Institute of Electrical and Electronics Engineers (IEEE)
Rose publication type: Journal article
Sponsorship: This work was supported by Toshiba Research
Europe, Ltd., Bristol, U.K.
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- fading channels
- state space methods
- digital communication
- multiple-input multiple-output (MIMO) systems
- nonlinear detection
- signal detection