Decision feedback equalization for MC-CDM with channel uncertainty

• Published in: 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577) Vol. 5; pp. 2636 - 2641 Vol.5
• Main Authors: Sgraja, C., Lindner, J.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway, New Jersey IEEE 2004
• Subjects: Applied sciences; Channel estimation; Covariance matrix; Decision feedback equalizers; Detection, estimation, filtering, equalization, prediction; Detectors; Exact sciences and technology; Information technology; Information, signal and communications theory; Interference cancellation; Iterative decoding; Multiplexing; Neodymium; OFDM; Signal and communications theory; Signal, noise; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Uncertainty; Parameter estimation; Multistage method; Error estimation; Noise reduction; Two channel system; Transmission channel; Data transmission; Iterative method; Decision feedback equalizers; Covariance matrix; Interference suppression; Covariance; Simulation; Channel estimation; S matrix; Orthogonal frequency division multiplexing
• ISBN: 0780385330; 9780780385337
• DOI: 10.1109/ICC.2004.1313009

We address the problem of interference cancellation for MC-CDM when the channel is uncertain, i.e., not perfectly known. In contrast to the decision-directed schemes that iteratively improve a channel estimate, we study a simpler receiver that tries to allow for the uncertainty of a solely pilot-based estimate. For this, we first derive the optimal receiver for both OFDM and MC-CDM, which merges the two processing stages of channel estimation and data detection, and show that this receiver may be partitioned into a pilot-based channel estimator and a detector that incorporates the estimator's error covariance matrix. Such a decomposition suggests an error model on the basis of deriving a block decision feedback equalizer (BDFE) which utilizes the estimator's error covariance as a reliability information. Simulation results demonstrate the performance of the error-aware BDFE.