TY - GEN
T1 - Energy-Based Maximum Likelihood Detector for GSSK in MIMO-ABC Systems
AU - Raghavendra, Ashwini H.
AU - Kowshik, Anagha K.
AU - Gurugopinath, Sanjeev
AU - Muhaidat, Sami
AU - Tellambura, Chintha
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We propose a novel, low complexity energy-based maximum likelihood (EML) detector for a generalized space shift keying (GSSK)-enabled multiple-input multiple-output (MIMO) ambient backscatter communication (ABC) system. The proposed scheme exploits the multiple antenna structure of the system to achieve a lower error rate performance than the conventional single-antenna ABC systems. The proposed EML GSSK detector does not require the perfect knowledge of the ambient source signal. To gain insights into the performance of the proposed scheme, we derive the exact pairwise error probability (PEP) of the EML detector, and further obtain an upper bound on the probability of error. We also derive a simple asymptotic PEP expression, as the number of antennas of the reader becomes large. We validate our analysis through Monte Carlo simulations, and show that the performance loss due to the approximations employed in our analysis is small. The performance of EML detector is also compared with the conventional ML detector and the loss in performance is studied.
AB - We propose a novel, low complexity energy-based maximum likelihood (EML) detector for a generalized space shift keying (GSSK)-enabled multiple-input multiple-output (MIMO) ambient backscatter communication (ABC) system. The proposed scheme exploits the multiple antenna structure of the system to achieve a lower error rate performance than the conventional single-antenna ABC systems. The proposed EML GSSK detector does not require the perfect knowledge of the ambient source signal. To gain insights into the performance of the proposed scheme, we derive the exact pairwise error probability (PEP) of the EML detector, and further obtain an upper bound on the probability of error. We also derive a simple asymptotic PEP expression, as the number of antennas of the reader becomes large. We validate our analysis through Monte Carlo simulations, and show that the performance loss due to the approximations employed in our analysis is small. The performance of EML detector is also compared with the conventional ML detector and the loss in performance is studied.
UR - http://www.scopus.com/inward/record.url?scp=85136177169&partnerID=8YFLogxK
U2 - 10.1109/SPCOM55316.2022.9840815
DO - 10.1109/SPCOM55316.2022.9840815
M3 - Conference contribution
AN - SCOPUS:85136177169
T3 - SPCOM 2022 - IEEE International Conference on Signal Processing and Communications
BT - SPCOM 2022 - IEEE International Conference on Signal Processing and Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Signal Processing and Communications, SPCOM 2022
Y2 - 11 July 2022 through 15 July 2022
ER -