Title :
Adaptive joint detection and estimation in MIMO systems: a hybrid systems approach
Author :
Kulatunga, Harini ; Kadirkamanathan, Visakan
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK
fDate :
5/1/2006 12:00:00 AM
Abstract :
An adaptive receiver based on hybrid system theory is developed for a multiuser multiple-input multiple-output (MIMO) fading code-division multiple-access (CDMA) system. The basic idea is to treat the transmitted symbols and channel gains as unknown states (discrete and continuous) within a hybrid systems framework. The Bayesian-inference-based state estimation is derived using multiple model theory resulting in an optimal joint sequence estimator, which is shown to be intractable in its computational complexity. A suboptimal receiver (IMM-SIC) is then derived based on the well-known Interacting Multiple Model (IMM) algorithm and successive interference cancellation (SIC) scheme. This paper shows the specific approximations made to the probability densities of the optimal receiver in deriving the IMM-SIC receiver with complexity linear in number of users. This receiver design is well suited for online recursive processing of space-time coded CDMA system, where the decoding stage is incorporated within the multiple model framework.
Keywords :
MIMO systems; belief networks; code division multiple access; computational complexity; fading channels; inference mechanisms; interference suppression; multiuser detection; radio receivers; space-time codes; state estimation; Bayesian-inference-based state estimation; MIMO systems; adaptive receiver; computational complexity; fading code-division multiple-access system; hybrid system theory; interacting multiple model; multiuser multiple-input multiple-output; sequence estimator; space-time coded CDMA system; successive interference cancellation; Computational complexity; Fading; Filtering; MIMO; Multiaccess communication; Multiuser detection; Signal processing algorithms; State estimation; Systems engineering and theory; Transmitters; Joint estimation and detection; multiple models; multiuser detection (MUD);
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2006.871964