Iterative Detection, Decoding and Channel Parameter Estimation for Orthogonally Modulated DS-CDMA Systems

Doctoral thesis, 2004

In this thesis, we study iterative detection, decoding and channel parameter estimation algorithms for asynchronous direct-sequence code division multiple access (DS-CDMA) systems employing orthogonal signalling formats and long scrambling codes. Multiuser detection techniques are widely used to combat the detrimental effects of multipath fading and multiple access interference (MAI), which are the major impairments in CDMA communication systems. Although the emphasis is placed on nonlinear interference cancellation schemes, several linear interference filtering techniques are also discussed in the first part of the thesis. The multistage parallel interference canceler (PIC) is evaluated analytically and compared with simulation results. To prevent performance degradation of PIC due to error propagation, some soft cancellation schemes using soft decision feedback are presented. Most multiuser detectors rely on accurate channel information, which needs to be estimated in practice. For the purpose of channel estimation, both classic and Bayesian methods are considered in this thesis, depending on whether prior knowledge about the parameters to be estimated is available or not. We focus on the decision directed approach when estimating the fading channel gains. That is, the receiver estimates the channel parameters based on the detected data, no training sequences are needed. The estimated channel coefficients are also used to regenerate the signal of each user for the purpose of interference cancellation. Another essential channel parameter to be estimated is the propagation delay. Many studies show that multiuser detectors need very accurate delay estimates to perform well. We propose some suboptimal synchronization algorithms that achieve good acquisition performance in presence of MAI and have reduced complexity compared to the optimum maximum likelihood estimator. In the second part of the thesis, we employ the turbo processing principle and study iterative demodulation and decoding of a convolutionally coded and orthogonally modulated asynchronous DS-CDMA system. Several iterative schemes based on soft demodulation and decoding algorithms are presented. The performance of different strategies are evaluated and proved to achieve substantial performance gains compared to the conventional hard decision based scheme, especially when the soft demodulator is assisted by decision directed channel estimation and interference cancellation techniques, and also when demodulation and decoding are performed jointly in an iterative manner. It is also shown that iterative decoding with properly corrected extrinsic information or with non-extrinsic/extrinsic adaptation enables the system to operate reliably in the presence of severe multiuser interference. Additional gain is noticed when soft information rather than hard decision feedback is used for channel estimation and interference cancellation.