Low‐complexity symbol‐level combining for hybrid automatic repeat request in multiple‐input multiple‐output systems with linear detection

Abstract

In this study, the authors propose a low-complexity symbol-level combining (SLC) scheme for Chase combining-based hybrid automatic repeat request in multiple-input multiple-output systems with a linear receiver. In the proposed scheme, a subset of all row vectors in the channel matrix is selected and used for combining and detection of retransmitted symbols, where the Sherman–Morrison–Woodbury lemma is applied for the utilisation of each selected row vector. Therefore, compared with the existing SLC schemes using the entire channel matrix, the proposed scheme can have an advantage in computational complexity. Furthermore, they develop a row vector selection criterion for the proposed SLC scheme to calculate the amount of the signal-to-interference-noise ratio improvement based on the squared norm of each row vector with a significantly low complexity. Simulation results verify that compared with the existing SLC schemes, the proposed SLC scheme achieves similar or better error performance, while its computational complexity is lower or in the worst-case similar.