TY - GEN
T1 - SINR model for MBSFN based mission critical communications
AU - Daher, Alaa
AU - Coupechoux, Marceau
AU - Godlewski, Philippe
AU - Kelif, Jean Marc
AU - Ngouat, Pierre
AU - Minot, Pierre
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Multicast/Broadcast Single Frequency Network (MBSFN) is envisioned to be a key technology for business and mission critical communications. The need arises to define simple and efficient dimensioning rules for such networks. The Signal to Interference plus Noise Ratio (SINR) is an important key performance parameter since other metrics such as outage probability and capacity can be deduced from it. In this work, we propose an analytical model to derive an approximate closed-form formula of the SINR in a MBSFN. Our model takes into account Inter-Symbol Interference (ISI) due to the different propagation delays between the User Equipment (UE) and its serving evolved Nodes-B (eNBs). The comparison with Monte Carlo simulations shows that our approach provides accurate results when shadowing standard deviation is low. When shadowing is highly variable, our model, while less accurate, outperforms the traditional approach based on Fenton-Wilkinson. This phenomenon is due to the fact that several eNBs serve the same UE so that shadowing on every individual link compensate.
AB - Multicast/Broadcast Single Frequency Network (MBSFN) is envisioned to be a key technology for business and mission critical communications. The need arises to define simple and efficient dimensioning rules for such networks. The Signal to Interference plus Noise Ratio (SINR) is an important key performance parameter since other metrics such as outage probability and capacity can be deduced from it. In this work, we propose an analytical model to derive an approximate closed-form formula of the SINR in a MBSFN. Our model takes into account Inter-Symbol Interference (ISI) due to the different propagation delays between the User Equipment (UE) and its serving evolved Nodes-B (eNBs). The comparison with Monte Carlo simulations shows that our approach provides accurate results when shadowing standard deviation is low. When shadowing is highly variable, our model, while less accurate, outperforms the traditional approach based on Fenton-Wilkinson. This phenomenon is due to the fact that several eNBs serve the same UE so that shadowing on every individual link compensate.
U2 - 10.1109/VTCFall.2017.8288234
DO - 10.1109/VTCFall.2017.8288234
M3 - Conference contribution
AN - SCOPUS:85045285061
T3 - IEEE Vehicular Technology Conference
SP - 1
EP - 5
BT - 2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 86th IEEE Vehicular Technology Conference, VTC 2017-Fall
Y2 - 24 September 2017 through 27 September 2017
ER -