Low Complexity Turbo Equalization Research Articles

Low-Complexity Turbo Equalization and Multiuser Decoding for TD-CDMA

The authors propose a low complexity multiuser joint parallel interference cancellation (PIC) decoder and turbo decision feedback equalizer for code division multiple access (CDMA). In their scheme, an estimate of the interference signal (both multiple-access interference and intersymbol interference) is formed by weighting the hard decisions produced by conventional (i.e., hard-output) Viterbi decoders. The estimated interference is subtracted from the received signal in order to improve decoding in the next iteration. By using asymptotic performance analysis of random-spreading CDMA, they optimize the feedback weights at each iteration. Then, they consider two (mutually related) performance limitation factors: the bias of residual interference and the ping-pong effect. The authors show that the performance of the proposed algorithm can be improved by compensating for the bias in the weight calculation, and they propose a modification of the basic PIC algorithm, which prevents the ping-pong effect and allows higher channel load and/or faster convergence to the single-user performance. The proposed algorithm is validated through computer simulation in an environment fully compliant with the specifications of the time-division duplex mode of third-generation systems, contemplating a combination of time-division multiple access and CDMA and including frequency-selective fading channels, user asynchronism, and power control. The main conclusion of this work is that, for such application, soft-input soft-output decoders (e.g., implemented by the forward-backward BCJR algorithm) are not needed to attain very high spectral efficiency, and simple conventional Viterbi decoding suffices for most practical settings.

Low-complexity Turbo-equalization for diversity channels

A low-complexity iterative receiver structure is proposed for a convolutionally coded system in a severe intersymbol interference environment where diversity reception is available. The receiver performs two successive soft decisions, first from a MMSE filter and then from a channel decoder. At each iteration, extrinsic information is extracted from the detection and decoding stages and is used as a priori information in the next iteration. Simulation results demonstrate that the proposed iterative receiver offers significant performance gain over traditional non-iterative receiver structures. Furthermore, the low complexity of the receiver permits its use in severe multipath channels (10 or more paths).