TY - GEN
T1 - Best sensor selection for an iterative REM construction
AU - Grimoud, Sebastien
AU - Sayrac, Berna
AU - Ben Jemaa, Sana
AU - Moulines, Eric
PY - 2011/12/23
Y1 - 2011/12/23
N2 - In this paper we propose a Bayesian approach for estimating parameters of the radio propagation model, and an iterative Kriging interpolation algorithm for choosing the best candidate measurement to be retrieved into the Radio Environment Map (REM). We compare the performance with a random choice of the candidate measurement and show that our algorithm reduces the amount of measurement needed by 33%. The proposed algorithm has also the merit of being fast enough to be implemented in an online fashion for REMs with a grid size of 25m and for pedestrian mobile speeds.
AB - In this paper we propose a Bayesian approach for estimating parameters of the radio propagation model, and an iterative Kriging interpolation algorithm for choosing the best candidate measurement to be retrieved into the Radio Environment Map (REM). We compare the performance with a random choice of the candidate measurement and show that our algorithm reduces the amount of measurement needed by 33%. The proposed algorithm has also the merit of being fast enough to be implemented in an online fashion for REMs with a grid size of 25m and for pedestrian mobile speeds.
UR - https://www.scopus.com/pages/publications/83755219417
U2 - 10.1109/VETECF.2011.6093004
DO - 10.1109/VETECF.2011.6093004
M3 - Conference contribution
AN - SCOPUS:83755219417
SN - 9781424483273
T3 - IEEE Vehicular Technology Conference
BT - 2011 IEEE Vehicular Technology Conference Fall, VTC Fall 2011 - Proceedings
T2 - IEEE 74th Vehicular Technology Conference, VTC Fall 2011
Y2 - 5 September 2011 through 8 September 2011
ER -