Block-floating-point enhanced MMSE filter matrix computation for MIMO-OFDM communication systems

In this paper we present an architecture for an MMSE filter matrix computation unit for signal detection in MIMO-OFDM communication systems. We propose to compute the required matrix inverse based on a Cholesky decomposition, followed by a Gauss-Jordan matrix inversion of the resulting triangular matrix. The high dynamic range required by this approach is traditionally conquered with custom floating-point formats or with fixed-point number representations with a large number of bits. We show in this paper that a block-floatingpoint scheme with only two normalization steps throughout the computation of the MMSE filter matrix is sufficient to achieve a BER performance close to that of a double precision floatingpoint implementation for a MIMO-OFDM systems with 64-QAM modulation. The corresponding circuit complexity is superior to that of a pure fixed-point implementation.