Modeling ordered subcarrier SNR in MIMO-OFDM wireless links

Recent research has shown that the detected bit error-rate of coded and bit-interleaved multiple-input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) links is characterized by the ordered post-processing signal-to-noise ratio (SNR). In this paper, we show that the per-stream ordered SNR converges asymptotically (with delay spread) to the inverse, marginal cumulative distribution function (CDF) of post-processing SNR. We derive a new approximation of the post-processing SNR inverse marginal CDF through an approximation of the marginal CDF for ordered eigenvalues in Wishart random matrices. By evaluating the independence of subcarriers in terms of the power delay profile, we show that the inverse marginal CDF is also an important characterization of post-processing SNR in practice. We exploit this structure to improve principal component regression algorithms that empirically infer a low-dimension basis for ordered SNR. Numerical simulations show high accuracy of this basis with just three dimensions for arbitrary power delay profiles. The consequences of this work include high-resolution limited channel feedback, simpler channel models for system simulation and algorithm design, as well as the reduction of dimension in link quality metrics for link adaptation. Simulations demonstrate the application to link adaptation in IEEE 802.11n with constellations that may be adapted per spatial stream.