Low-Complexity Gaussian Detection for MIMO Systems

Abstract EN

For single-carrier transmission over delay-spread multi-input multi-output (MIMO) channels, the computational complexity of the receiver is often considered as a bottleneck with respect to (w.r.t.) practical implementations.

Multi-antenna interference (MAI) together with intersymbol interference (ISI) provides fundamental challenges for efficient and reliable data detection.

In this paper, we carry out a systematic study on the interference structure of MIMO-ISI channels, and sequentially deduce three different Gaussian approximations to simplify the calculation of the global likelihood function.

Using factor graphs as a general framework and applying the Gaussian approximation, three low-complexity iterative detection algorithms are derived, and their performances are compared by means of Monte Carlo simulations.

After a careful inspection of their merits and demerits, we propose a graph-based iterative Gaussian detector (GIGD) for severely delay-spread MIMO channels.

The GIGD is characterized by a strictly linear computational complexity w.r.t.

the effective channel memory length, the number of transmit antennas, and the number of receive antennas.

When the channel has a sparse ISI structure, the complexity of the GIGD is strictly proportional to the number of nonzero channel taps.

Finally, the GIGD provides a near-optimum performance in terms of the bit error rate (BER) for repetition encoded MIMO systems.