TY - JOUR
T1 - Adaptive refined random orthogonal matching pursuit algorithm for FBMC/OQAM MIMO framework
AU - Hassan, Beenish
AU - Baig, Sobia
AU - Aslam, Saad
AU - Asif, Hafiz M.
AU - Mumtaz, Shahid
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2024/1/1
Y1 - 2024/1/1
N2 - The fifth generation of wireless communication is anticipated to provide improved quality of service and enhanced data rates to the end users. One such technology that stands out as a potential transmission scheme for 5G systems is Filter Bank Multicarrier using Offset Quadrature Amplitude Modulation (FBMC/OQAM) with an effective channel estimation technique for improved performance. However, due to the inherent imaginary interference, channel estimation methods relying on preamble structures in FBMC/OQAM systems exhibit sub-optimal performance, particularly within Multiple-Input Multiple-Output (MIMO) setups. For channel estimation schemes based on compressed sensing, the inherent sparsity of wireless channels can be exploited for accurate channel reconstruction and overall performance improvement. We propose a novel compressed sensing based algorithm namely, Adaptive Refined Random Orthogonal Matching Pursuit (ARROMP), for MIMO-FBMC system with Coordinated MultiPoint (CoMP) scheduling. This algorithm adaptively selects a support set by utilizing a double threshold for the minimization of mean squared error and for accurate channel reconstruction. The proposed algorithm's performance is compared with existing Orthogonal Matching Pursuit (OMP) schemes such as random OMP, refined random OMP, and least square-based estimation. The numerical simulations suggest that the proposed adaptive algorithm provides performance improvement in terms of reduced Mean Squared Error (MSE) of channel reconstruction and Bit Error Rate (BER). Moreover, the proposed ARROMP algorithm for MIMO-FBMC is rigorously tested with CoMP scheduling for a cellular network using frequency division duplex mode. The proposed system presents significant improvements in throughput and spectral efficiency for all types of cell users, including cell-edge users. The simulation results validate the improved performance of the proposed algorithm with CoMP scheduling over the existing single-cell system with no coordination.
AB - The fifth generation of wireless communication is anticipated to provide improved quality of service and enhanced data rates to the end users. One such technology that stands out as a potential transmission scheme for 5G systems is Filter Bank Multicarrier using Offset Quadrature Amplitude Modulation (FBMC/OQAM) with an effective channel estimation technique for improved performance. However, due to the inherent imaginary interference, channel estimation methods relying on preamble structures in FBMC/OQAM systems exhibit sub-optimal performance, particularly within Multiple-Input Multiple-Output (MIMO) setups. For channel estimation schemes based on compressed sensing, the inherent sparsity of wireless channels can be exploited for accurate channel reconstruction and overall performance improvement. We propose a novel compressed sensing based algorithm namely, Adaptive Refined Random Orthogonal Matching Pursuit (ARROMP), for MIMO-FBMC system with Coordinated MultiPoint (CoMP) scheduling. This algorithm adaptively selects a support set by utilizing a double threshold for the minimization of mean squared error and for accurate channel reconstruction. The proposed algorithm's performance is compared with existing Orthogonal Matching Pursuit (OMP) schemes such as random OMP, refined random OMP, and least square-based estimation. The numerical simulations suggest that the proposed adaptive algorithm provides performance improvement in terms of reduced Mean Squared Error (MSE) of channel reconstruction and Bit Error Rate (BER). Moreover, the proposed ARROMP algorithm for MIMO-FBMC is rigorously tested with CoMP scheduling for a cellular network using frequency division duplex mode. The proposed system presents significant improvements in throughput and spectral efficiency for all types of cell users, including cell-edge users. The simulation results validate the improved performance of the proposed algorithm with CoMP scheduling over the existing single-cell system with no coordination.
KW - CoMP scheduling
KW - Compressed sensing
KW - FBMC/OQAM
KW - MIMO
KW - Refined random OMP
UR - http://www.scopus.com/inward/record.url?scp=85181175873&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85181175873&partnerID=8YFLogxK
U2 - 10.1016/j.aej.2023.12.026
DO - 10.1016/j.aej.2023.12.026
M3 - Article
AN - SCOPUS:85181175873
SN - 1110-0168
VL - 87
SP - 319
EP - 328
JO - Alexandria Engineering Journal
JF - Alexandria Engineering Journal
ER -