Optimal power allocation for CRN-NOMA systems with adaptive transmit power

In this paper, we derive the throughput of non-orthogonal multiple access NOMA with adaptive transmit power for cognitive radio networks (CRN). The secondary source and relay adapt their power to not generate high interference at primary destination. We evaluate the packet error probability and the throughput at the packet level, while previous studies compute it at the symbol level. We also optimize the powers allocated to near and far users to maximize the throughput of CRN-NOMA. Besides, optimal power allocation of CRN-NOMA with adaptive transmit power has not been yet suggested and previous studies deal with fixed transmit power.

[1]  H. Vincent Poor,et al.  Cooperative Non-Orthogonal Multiple Access in 5G Systems , 2015, IEEE Communications Letters.

[2]  Zhiguo Ding,et al.  Nonorthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks , 2016, IEEE Transactions on Vehicular Technology.

[3]  Anass Benjebbour,et al.  System-level performance evaluation of downlink non-orthogonal multiple access (NOMA) , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[4]  Guan Gui,et al.  A New Definition of Fairness for Non-Orthogonal Multiple Access , 2019, IEEE Communications Letters.

[5]  Zhiguo Ding,et al.  Non-orthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks , 2016, ArXiv.

[6]  In-Ho Lee,et al.  Non-Orthogonal Multiple Access in Coordinated Direct and Relay Transmission , 2015, IEEE Communications Letters.

[7]  H. Vincent Poor,et al.  Relay Selection for Cooperative NOMA , 2016, IEEE Wireless Communications Letters.

[8]  Yuan Wu,et al.  Optimal Power Allocation and Scheduling for Non-Orthogonal Multiple Access Relay-Assisted Networks , 2018, IEEE Transactions on Mobile Computing.

[9]  Geng Wu,et al.  5G Network Capacity: Key Elements and Technologies , 2014, IEEE Vehicular Technology Magazine.

[10]  Jinjin Men,et al.  Non-Orthogonal Multiple Access for Multiple-Antenna Relaying Networks , 2015, IEEE Communications Letters.

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

[12]  Alister G. Burr,et al.  A General Upper Bound to Evaluate Packet Error Rate over Quasi-Static Fading Channels , 2011, IEEE Transactions on Wireless Communications.

[13]  Victor C. M. Leung,et al.  Resource Allocation for Secure MISO-NOMA Cognitive Radios Relying on SWIPT , 2018, 2018 IEEE International Conference on Communications (ICC).

[14]  Li Su,et al.  Exploiting multi-hop relaying to overcome blockage in directional mmwave small cells , 2015, Journal of Communications and Networks.

[15]  Uma Bhattacharya,et al.  NOMA inspired multicasting in cognitive radio networks , 2018, IET Commun..

[16]  Azam Khalili,et al.  An incremental LMS network with reduced communication delay , 2016, Signal Image Video Process..

[17]  Lajos Hanzo,et al.  Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT , 2019, IEEE Journal on Selected Areas in Communications.

[18]  Octavia A. Dobre,et al.  Power Allocation for Cognitive Radio Networks Employing Non-Orthogonal Multiple Access , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[19]  Ping Wang,et al.  Max-Min Resource Allocation for Video Transmission in NOMA-Based Cognitive Wireless Networks , 2018, IEEE Transactions on Communications.

[20]  W. N. Venables,et al.  Permanent Expressions for Order Statistic Densities , 1972 .

[21]  Hasan Abu Hilal,et al.  Performance of ZF and MMSE decoders for massive multi-cell MIMO systems in impulsive and Laplacian noise channels , 2019, Signal, Image and Video Processing.

[22]  Caijun Zhong,et al.  Non-Orthogonal Multiple Access With Cooperative Full-Duplex Relaying , 2016, IEEE Communications Letters.