Union bound based performance evaluation of turbo-coded uplink MIMO systems

Mysore, Naveen; Bajcsy, J.

doi:10.1109/milcom.2005.1606094

Cited by 2 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [26], an average bound has been proposed for the performance of turbo coded systems with correlated and uncorrelated Rayleigh fading channels. In [10], [27], the authors have proposed an upper-bound for the performance of the turbo coded MIMO system with correlated and uncorrelated Rayleigh, slow-fading channels, and the proposed bound approached the simulation results within 0.2-0.5 dB at a BER of 10 −5 .…”

Section: Introductionmentioning

confidence: 86%

Performance Analysis of Coded Massive MIMO-OFDM Systems Using Effective Matrix Inversion

Al-Askery

Tsimenidis

Boussakta

et al. 2017

IEEE Trans. Commun.

View full text Add to dashboard Cite

In this paper, we derive the bit error rate (BER) and pairwise error probability (PEP) for massive multipleinput multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems for different M -ary modulations based upon the approximate noise distribution after channel equalization. The PEP is used to obtain the upper-bounds for convolutionally coded and turbo coded massive MIMO-OFDM systems for different code generators and receive antennas. In addition, complexity analysis of the log-likelihood ratio (LLR) values is performed using the approximate noise probability density function (PDF). The derived LLR computations can be timeconsuming when the number of receive antennas is very large in massive MIMO-OFDM systems. Thus, a reduced complexity approximation is introduced using Newton's interpolation with different polynomial orders and the results are compared with the exact simulations. The Neumann large matrix approximation is used to design the receiver for a zero-forcing equalizer (ZFE) by reducing the number of operations required in calculating the channel matrix inverse. Simulations are used to demonstrate that the results obtained using the derived equations match closely the Monte-Carlo simulations.

show abstract

Section: Introductionmentioning

confidence: 86%