Your browser doesn't support javascript.
loading
Outage Performance Improvement by Selected User in D2D Transmission and Implementation of Cognitive Radio-Assisted NOMA.
Do, Dinh-Thuan; Nguyen, Minh-Sang Van; Lee, Byung Moo.
Affiliation
  • Do DT; Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam.
  • Nguyen MV; Faculty of Electronics Technology, Industrial University of Ho Chi Minh City (IUH), Ho Chi Minh City 700000, Vietnam.
  • Lee BM; School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea.
Sensors (Basel) ; 19(22)2019 Nov 06.
Article in En | MEDLINE | ID: mdl-31698856
ABSTRACT
In this paper, we investigate the outage performance in secondary network of cognitive radio (CR) employing non-orthogonal multiple access (NOMA) wireless networks over Rayleigh fading channels. The considered system model adopts device-to-device (D2D) transmission together with traditional communication to form a new system model, namely CR-D2DNOMA network. The specific user is selected from multiple D2D-Tx users (D2Ds) to communicate with far NOMA users to form qualified D2D connection with assistance of the Relay user ( R U ). The main metric in such CR-D2DNOMA network needs to be considered and we particularly introduce the closed-form expressions for outage probability in the secondary network where it is designed to serve two far NOMA users. The perfect Successive Interference Cancellation (SIC) and imperfect SIC can be further examined at the second NOMA user who detects signal based on the ability of SIC. The results show the positive impact of increasing the fading parameters on the system performance. More importantly, numerical results are provided to verify the correctness of our derivations. Additionally, the effects of asymptotic expressions on insights evaluation are also further analyzed.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2019 Document type: Article Affiliation country: Vietnam

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2019 Document type: Article Affiliation country: Vietnam