TY - GEN
T1 - Self-Interference Channel Characterization for Reconfigurable Antenna Based Systems
AU - Shaboyan, Sergey
AU - Behbahani, Alireza S.
AU - Eltawil, Ahmed M.
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2020/3/31
Y1 - 2020/3/31
N2 - This paper presents experimental characterization of the self-interference (SI) channel for In-Band Full-Duplex (IBFD) communication systems that employ beam steering, Multi reconfigurable antennas (MRA), for passive SI suppression. First, we describe a system model of a full-duplex base station while highlighting channel impairments associated with each signal component. We present the SI channel power delay profiles measured by IBFD system operating on 5MHz, 10MHz and 20MHz bandwidths. We compare the measurements for beam patterns that result in line of sight suppression (and non-suppression) in both static and dynamic environments. We then statistically model the SI channel by performing probability distribution fitting to SI channel data, which is collected in dynamic environment, under high and low SI suppression conditions provided by MRA. Finally, candidate probability distribution models are compared using goodness of fit test.
AB - This paper presents experimental characterization of the self-interference (SI) channel for In-Band Full-Duplex (IBFD) communication systems that employ beam steering, Multi reconfigurable antennas (MRA), for passive SI suppression. First, we describe a system model of a full-duplex base station while highlighting channel impairments associated with each signal component. We present the SI channel power delay profiles measured by IBFD system operating on 5MHz, 10MHz and 20MHz bandwidths. We compare the measurements for beam patterns that result in line of sight suppression (and non-suppression) in both static and dynamic environments. We then statistically model the SI channel by performing probability distribution fitting to SI channel data, which is collected in dynamic environment, under high and low SI suppression conditions provided by MRA. Finally, candidate probability distribution models are compared using goodness of fit test.
UR - http://hdl.handle.net/10754/662657
UR - https://ieeexplore.ieee.org/document/9048850/
UR - http://www.scopus.com/inward/record.url?scp=85083318963&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF44664.2019.9048850
DO - 10.1109/IEEECONF44664.2019.9048850
M3 - Conference contribution
SN - 9781728143002
SP - 1154
EP - 1158
BT - 2019 53rd Asilomar Conference on Signals, Systems, and Computers
PB - IEEE
ER -