Low-complexity code-aided estimation techniques for multi-user DS-CDMA systems

We describe a class of low-complexity channel parameter and frequency offset estimation algorithms, applied to a space-time bit-interleaved coded modulation (ST-BICM) scheme for burst-mode asynchronous DS-CDMA uplink transmission over frequency selective channels. Conventional estimation algorithms rely mainly on the presence of training symbols within the data stream, reducing both the energy- and bandwidth efficiency. Our main goal is to remove the need for long training sequences by exploiting the presence of an underlying error-correcting code. We derive an iterative estimation technique, based on the Space Alternating Generalized Expectation Maximization (SAGE) Algorithm, which iterates between detection and estimation stages. Performance results are illustrated through computer simulations.