TY - JOUR
T1 - Opportunistic ambient backscatter communication in RF-Powered cognitive radio networks
AU - Kishore, Rajalekshmi
AU - Gurugopinath, Sanjeev
AU - Sofotasios, Paschalis C.
AU - Muhaidat, Sami
AU - Al-Dhahir, Naofal
N1 - Funding Information:
Manuscript received October 9, 2018; revised January 2, 2019; accepted January 30, 2019. Date of publication March 22, 2019; date of current version June 7, 2019. This paper was presented in part in IEEE WCNC 2019, Marrakech, Morocco. This work was supported in part by Khalifa University under Grant No. KU/RC1-C2PS-T2/8474000137 and Grant No. KU/FSU-8474000122. This work will appear in part in [1]. The associate editor coordinating the review of this paper and approving it for publication was D. B. da Costa. (Corresponding author: Sami Muhaidat.) R. Kishore is with the Department of Electrical and Computer Engineering, Khalifa University, Abu Dhabi 127788, UAE, and also with the Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani (K. K. Birla Goa Campus), Goa 403726, India (e-mail: [email protected]).
Publisher Copyright:
© 2015 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - In the present contribution, we propose a novel opportunistic ambient backscatter communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) networks. This framework considers opportunistic spectrum sensing (SS) integrated with ABC and harvest-then-transmit (HTT) operation strategies. Novel analytic expressions are derived for the average throughput, the average energy consumption and the energy efficiency (EE) in the considered set up. These expressions are represented in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition, we formulate an optimization problem to maximize the EE of the CR system operating in mixed ABC - and HTT - modes, for a given set of constraints, including primary interference and imperfect SS constraints. Capitalizing on this, we determine the optimal set of parameters which in turn comprise the optimal detection threshold, the optimal degree of trade-off between the CR system operating in the ABC - and HTT - modes and the optimal data transmission time. Extensive results from respective computer simulations are also presented for corroborating the corresponding analytic results and to demonstrate the performance gain of the proposed model in terms of EE.
AB - In the present contribution, we propose a novel opportunistic ambient backscatter communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) networks. This framework considers opportunistic spectrum sensing (SS) integrated with ABC and harvest-then-transmit (HTT) operation strategies. Novel analytic expressions are derived for the average throughput, the average energy consumption and the energy efficiency (EE) in the considered set up. These expressions are represented in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition, we formulate an optimization problem to maximize the EE of the CR system operating in mixed ABC - and HTT - modes, for a given set of constraints, including primary interference and imperfect SS constraints. Capitalizing on this, we determine the optimal set of parameters which in turn comprise the optimal detection threshold, the optimal degree of trade-off between the CR system operating in the ABC - and HTT - modes and the optimal data transmission time. Extensive results from respective computer simulations are also presented for corroborating the corresponding analytic results and to demonstrate the performance gain of the proposed model in terms of EE.
KW - Ambient backscatter communication
KW - cognitive radio networks
KW - energy detection
KW - energy efficiency
KW - wireless power transfer
UR - http://www.scopus.com/inward/record.url?scp=85063386334&partnerID=8YFLogxK
U2 - 10.1109/TCCN.2019.2907090
DO - 10.1109/TCCN.2019.2907090
M3 - Article
AN - SCOPUS:85063386334
SN - 2332-7731
VL - 5
SP - 413
EP - 426
JO - IEEE Transactions on Cognitive Communications and Networking
JF - IEEE Transactions on Cognitive Communications and Networking
IS - 2
M1 - 8672817
ER -