2014/01/02 by Constantin Siriteanu, Akimichi Takemura, Siriteanu, Constantin +7
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.1401.0430
32 pages, 4 figures, 1 table
openalex publication_date 2014/01/02 · arxiv created 2014/09/26 · arxiv updated 2014/09/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
For multiple-input/multiple-output (MIMO) spatial multiplexing with zero-forcing detection (ZF), signal-to-noise ratio (SNR) analysis for Rician fading involves the cumbersome noncentral-Wishart distribution (NCWD) of the transmit sample-correlation (Gramian) matrix. An approximation with a virtual CWD previously yielded for the ZF SNR an approximate (virtual) Gamma distribution. However, analytical conditions qualifying the accuracy of the SNR-distribution approximation were unknown. Therefore, we have been attempting to exactly characterize ZF SNR for Rician fading. Our previous attempts succeeded only for the sole Rician-fading stream under Rician--Rayleigh fading, by writing it as scalar Schur complement (SC) in the Gramian. Herein, we pursue a more general, matrix-SC-based analysis to characterize SNRs when several streams may undergo Rician fading. On one hand, for full-Rician fading, the SC distribution is found to be exactly a CWD if and only if a channel-mean--correlation condition holds. Interestingly, this CWD then coincides with the virtual CWD ensuing from the approximation. Thus, under the condition, the actual and virtual SNR-distributions coincide. On the other hand, for Rician--Rayleigh fading, the matrix-SC distribution is characterized in terms of determinant of matrix with elementary-function entries, which also yields a new characterization of the ZF SNR. Average error probability results validate our analysis vs.~simulation.