Approximate Gram-Matrix Interpolation for Wideband Massive MU-MIMO Systems

Abstract

Linear and non-linear data-detection and precoding algorithms for wideband massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems that rely on orthogonal frequency-division multiplexing (OFDM) or single-carrier frequency-division multiple access (SC-FDMA) often require computation of the Gram matrix for each active subcarrier. Computing the Gram matrix for each active subcarrier, however, results in excessively high computational complexity. In this paper, we propose novel, approximate algorithms that significantly reduce the complexity of Gram-matrix computation by simultaneously exploiting channel hardening and correlation across subcarriers. We show analytically that a small fraction of Gram-matrix computations in combination with approximate interpolation schemes are sufficient to achieve near-optimal error-rate performance at low computational complexity in massive MU-MIMO systems. We furthermore demonstrate that our approximate interpolation algorithms are more robust against channel-estimation errors than exact Gram-matrix interpolation algorithms that require high computational complexity.