Joint resource allocation for cognitive OFDM-NOMA systems with energy harvesting in green IoT

Abstract In order to enhance the capacity and extend the lifetime of nodes for green Internet of Things (IoT), the non-orthogonal multiple access (NOMA) is applied to cognitive orthogonal frequency-division multiplexing (OFDM) systems, along with simultaneous wireless information and power transfer (SWIPT). Firstly, an uplink SWIPT-based cognitive OFDM-NOMA system model is proposed where the power splitting (PS) mode is applied to harvest energy from radio frequency signals. Then, we investigate the problem of maximizing the sum data rate of uplink transmission by jointly optimizing sensing duration, user matching, and power allocation constrained by the transmit power and harvested energy. In order to decouple the strong relations among variables, the proposed optimization problem is decomposed into three sub-problems, i.e., the optimization of sensing duration, the optimization of user matching based on the matching theory, and the optimization of power allocation. We propose an alternate iteration algorithm to jointly solve the three sub-problems. Furthermore, two cognitive modes are employed in this paper: overlay mode and underlay mode. The performance of sum rate as well as harvested energy is evaluated, while simulation results are shown to verify the convergence of the proposed algorithm. It is shown that the proposed algorithm can not only perform the subcarrier allocation efficiently, but also behave well in terms of sum data rate subject to the required energy.

[1]  Guan Gui,et al.  Deep Cognitive Perspective: Resource Allocation for NOMA-Based Heterogeneous IoT With Imperfect SIC , 2019, IEEE Internet of Things Journal.

[2]  Anass Benjebbour,et al.  Non-Orthogonal Multiple Access (NOMA) for Cellular Future Radio Access , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[3]  Derrick Wing Kwan Ng,et al.  Simultaneous wireless information and power transfer in modern communication systems , 2014, IEEE Communications Magazine.

[4]  Yanyi Rao,et al.  Deep Learning-Based Channel Prediction for Edge Computing Networks Toward Intelligent Connected Vehicles , 2019, IEEE Access.

[5]  Weidang Lu,et al.  5G-based green broadband communication system design with simultaneous wireless information and power transfer , 2018, Phys. Commun..

[6]  Chen Qian,et al.  Nonorthogonal Interleave-Grid Multiple Access Scheme for Industrial Internet of Things in 5G Network , 2018, IEEE Transactions on Industrial Informatics.

[7]  Weidang Lu,et al.  QoS-Guarantee Resource Allocation for Multibeam Satellite Industrial Internet of Things With NOMA , 2021, IEEE Transactions on Industrial Informatics.

[8]  Gerhard Fettweis,et al.  Generalized Frequency Division Multiplexing for 5th Generation Cellular Networks , 2014, IEEE Transactions on Communications.

[9]  George K. Karagiannidis,et al.  Secure Cache-Aided Multi-Relay Networks in the Presence of Multiple Eavesdroppers , 2019, IEEE Transactions on Communications.

[10]  H. Vincent Poor,et al.  Application of Non-Orthogonal Multiple Access in LTE and 5G Networks , 2015, IEEE Communications Magazine.

[11]  Kang G. Shin,et al.  Connectivity of Cognitive Device-to-Device Communications Underlying Cellular Networks , 2015, IEEE Journal on Selected Areas in Communications.

[12]  George K. Karagiannidis,et al.  Outage Probability and Optimal Cache Placement for Multiple Amplify-and-Forward Relay Networks , 2018, IEEE Transactions on Vehicular Technology.

[13]  Zhenyu Na,et al.  Subcarrier allocation based Simultaneous Wireless Information and Power Transfer algorithm in 5G cooperative OFDM communication systems , 2018, Phys. Commun..

[14]  Weidang Lu,et al.  A Novel Multichannel Internet of Things Based on Dynamic Spectrum Sharing in 5G Communication , 2019, IEEE Internet of Things Journal.

[15]  Paul J. Kolodzy,et al.  Interference temperature: a metric for dynamic spectrum utilization , 2006, Int. J. Netw. Manag..

[16]  Naziha Glei,et al.  Power Allocation for Energy-Efficient Downlink NOMA Systems , 2019, 2019 19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).

[17]  Chao Li,et al.  Cache-aided mobile edge computing for B5G wireless communication networks , 2020, EURASIP J. Wirel. Commun. Netw..

[18]  S. Sasipriya,et al.  An overview of cognitive radio in 5G wireless communications , 2016 .

[19]  Hua Qu,et al.  Fairness Based Power Allocation optimization of Cooperative NOMA with SWIPT Network , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).

[20]  Anass Benjebbour,et al.  Concept and practical considerations of non-orthogonal multiple access (NOMA) for future radio access , 2013, 2013 International Symposium on Intelligent Signal Processing and Communication Systems.

[21]  Jie Xu,et al.  Multiantenna Wireless Powered Communication With Cochannel Energy and Information Transfer , 2015, IEEE Communications Letters.

[22]  Shuangfeng Han,et al.  Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends , 2015, IEEE Communications Magazine.

[23]  Xueyan Zhang,et al.  NOMA-Based Resource Allocation for Cluster-Based Cognitive Industrial Internet of Things , 2020, IEEE Transactions on Industrial Informatics.

[24]  Dan Deng,et al.  Intelligent Secure Communication for Internet of Things With Statistical Channel State Information of Attacker , 2019, IEEE Access.

[25]  Zhu Han,et al.  Energy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA With Wireless Power Transfer , 2018, IEEE Transactions on Green Communications and Networking.

[26]  Mustafa Cenk Gursoy,et al.  NOMA-Based Energy-Efficient Wireless Powered Communications in 5G Systems , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[27]  Daniel Benevides da Costa,et al.  Effect of CCI on WPC With Time-Division Energy and Information Transmission , 2016, IEEE Wireless Communications Letters.

[28]  Feifei Gao,et al.  A new cognitive radio strategy for SWIPT system , 2014, 2014 International Workshop on High Mobility Wireless Communications.

[29]  Muhammad Ali Imran,et al.  Receiver and resource allocation optimization for uplink NOMA in 5G wireless networks , 2015, 2015 International Symposium on Wireless Communication Systems (ISWCS).

[30]  Zhenyu Na,et al.  Join trajectory optimization and communication design for UAV-enabled OFDM networks , 2020, Ad Hoc Networks.

[31]  Weidang Lu,et al.  Incentive Mechanism Based Cooperative Spectrum Sharing for OFDM Cognitive IoT Network , 2020, IEEE Transactions on Network Science and Engineering.

[32]  Zhenyu Na,et al.  Joint Subcarrier and Subsymbol Allocation-Based Simultaneous Wireless Information and Power Transfer for Multiuser GFDM in IoT , 2019, IEEE Internet of Things Journal.

[33]  Zhenyu Na,et al.  GFDM Based Wireless Powered Communication for Cooperative Relay System , 2019, IEEE Access.

[34]  Mario A. Góngora,et al.  Optimized artificial neural network using differential evolution for prediction of RF power in VHF/UHF TV and GSM 900 bands for cognitive radio networks , 2014, 2014 14th UK Workshop on Computational Intelligence (UKCI).