2013 Asilomar Conference on Signals, Systems and Computers 2013
DOI: 10.1109/acssc.2013.6810578
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On scalability, robustness and accuracy of physical layer abstraction for large-scale system-level evaluations of LTE networks

Abstract: We present an in-depth performance analysis of the gains of physical layer (PHY) abstraction when compared to a full implementation of the physical layer. The abstraction model uses either effective signal to noise plus interference (SINR) mapping or mutual information effective SINR mapping and covers different transmission modes as well as support for hybrid automatic repeat request. Using the OpenAirInterface LTE system level simulator we show that for a simple network with one base station and two user equ… Show more

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Cited by 9 publications
(9 citation statements)
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“…procedure called SNR compression in [13]. The SNR γ n for each symbol period is calculated for the different MIMO modes as:…”
Section: System Modelmentioning
confidence: 99%
“…procedure called SNR compression in [13]. The SNR γ n for each symbol period is calculated for the different MIMO modes as:…”
Section: System Modelmentioning
confidence: 99%
“…• SISO: a single polarization is used. Thus, the system model is expressed as y n = h n x n + w n and therefore γ n = |h n | 2 [19], the SINR can be expressed as γ n = H n 2 /σ 2 w , where H n 2 is the Frobenius norm. • Polarization Multiplexing (PM): each polarization conveys a symbol and thus, two symbols are transmitted in each channel access.…”
Section: B Physical Layer Abstraction and Mimomentioning
confidence: 99%
“…To avoid actual signal processing, in system-level simulations, a link-to-system interface composed of a suitable PHY layer abstraction is typically used. Because the parameters of the PHY abstraction models such as frequency, symbol duration, and error correcting codes do not depend on the channel models or the multi-antenna techniques employed, the SISOabstracted PHY layer can be used for MIMO configurations in the system-level simulations [21]. The goal of this PHY layer abstraction is essentially to obtain a block error rate (BLER) for a transport block (TB) without having to carry out real signal processing.…”
Section: Phy Layermentioning
confidence: 99%
“…where β FR ρ ð Þ denotes the normalized BW in the FR zone, while the other parameters are as described in (21).…”
Section: Proposed Qos-based Dynamic Ffr Schemementioning
confidence: 99%
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