OAMP-Aided Joint Channel Estimation and Data Detection for ODDM Systems
This work addresses the challenge of joint channel estimation and data detection in doubly selective channels for ODDM systems, offering improved performance over existing methods.
The paper proposes an OAMP-aided joint channel estimation and data detection receiver for ODDM systems that achieves lower bit error rate than benchmark schemes and approaches the performance of OAMP with perfect channel state information.
In this work, to address the challenge of joint channel estimation and data detection (JED) for orthogonal delay-Doppler (DD) division multiplexing (ODDM) in doubly selective channels, we propose an orthogonal approximate message passing (OAMP)-aided JED (OAMP-JED) receiver. We first formulate a bilinear cross-domain JED model, which can be linearized into separate channel estimation and data detection subproblems. The proposed OAMP-JED receiver alternately executes two OAMP modules for these subproblems, effectively coupled through a variational noise term to account for model uncertainty. Leveraging OAMP's error orthogonality, we derive closed-form scalar-variance updates to enable efficient and principled soft information exchange between the modules, thereby mitigating error propagation during JED. Simulation results show that, for both uncoded and coded ODDM, OAMP-JED achieves a lower bit error rate (BER) than benchmark schemes. Moreover, its BER performance closely approaches that of OAMP with perfect CSI.