Journal ArticleDOI
On the distribution of SINR for the MMSE MIMO receiver and performance analysis
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TLDR
A Gamma distribution and a generalized Gamma distribution are proposed as approximations to the finite sample distribution of T and simulations suggest that these approximate distributions can be used to estimate accurately the probability of errors even for very small dimensions.Abstract:
This correspondence studies the statistical distribution of the signal-to-interference-plus-noise ratio (SINR) for the minimum mean-square error (MMSE) receiver in multiple-input multiple-output (MIMO) wireless communications. The channel model is assumed to be (transmit) correlated Rayleigh flat-fading with unequal powers. The SINR can be decomposed into two independent random variables: SINR=SINR/sup ZF/+T, where SINR/sup ZF/ corresponds to the SINR for a zero-forcing (ZF) receiver and has an exact Gamma distribution. This correspondence focuses on characterizing the statistical properties of T using the results from random matrix theory. First three asymptotic moments of T are derived for uncorrelated channels and channels with equicorrelations. For general correlated channels, some limiting upper bounds for the first three moments are also provided. For uncorrelated channels and correlated channels satisfying certain conditions, it is proved that T converges to a Normal random variable. A Gamma distribution and a generalized Gamma distribution are proposed as approximations to the finite sample distribution of T. Simulations suggest that these approximate distributions can be used to estimate accurately the probability of errors even for very small dimensions (e.g., two transmit antennas).read more
Citations
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Macrodiversity MIMO Transceivers
TL;DR: This thesis presents some systematic performance metrics and approaches to multiuser scheduling which only require the long term channel state information (CSI) and provides a double advantage over scheduling using instantaneous CSI.
Proceedings ArticleDOI
Performance analysis of SIMO and MIMO system with equalization
T. Deepa,S. Rajaguru,R. Kumar +2 more
TL;DR: Simulation result shows that ML detection algorithm outperforms the equalizer based detection algorithms namely, ZF, MMSE in MIMO systems and they are compared based on BER performance.
Journal ArticleDOI
Efficient Codebook Design for Co-Operative MIMO Systems With Decode-and-Forward Relay
TL;DR: The proposed design criterion mitigates the eigen-spreads of the exact CSI and the quantized CSI, and the bit-error-rate approaches the lower-bound within 1.3-dB at $\text{BER} ={10-5}}$ by using 0-bit feed-forward.
Book ChapterDOI
A primer on information theory and MMSE estimation
Robert W. Heath,Angel Lozano +1 more
Proceedings ArticleDOI
Power control and low-complexity receiver for uplink massive MIMO systems
TL;DR: Numerical results show that the transmit power consumed by the system using the uplink power control strategy with the TPE receiver is close to that with the MMSE receiver when the polynomial degree is properly high.
References
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TL;DR: This book is an accessible introduction to every fundamental aspect of space-time wireless communications and a powerful tool for improving system performance that already features in the UMTS and CDMA2000 mobile standards.