Resource allocation for OFDM-based multiuser cooperative underlay cognitive systems

• Published in: EURASIP journal on wireless communications and networking Vol. 2017; no. 1; pp. 1 - 15
• Main Authors: Chami, Marwa, Pischella, Mylene, Le Ruyet, Didier
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 06.11.2017; Springer Nature B.V; SpringerOpen
• Subjects: Adaptive algorithms; Cognitive radio; Communications Engineering; Computer Science; Computer simulation; Decoding; Electric power distribution; Engineering; Information Systems Applications (incl.Internet); Interference; Maximum sum rate; Multiuser; Networks; OFDM; Optimization; Resource allocation; Signal and Image Processing; Signal,Image and Speech Processing; Subcarriers; Underlay; Imperfect CSI; OFDM; Multiuser; Underlay; Maximum sum rate; Cognitive radio; Optimization
• ISSN: 1687-1499; 1687-1472; 1687-1499
• DOI: 10.1186/s13638-017-0958-4

This paper investigates the resource allocation problem for a multiuser underlay cognitive system where the secondary system is allowed to transmit and cooperate with the primary system. In this scenario, the secondary users are subject to two main constraints in the presence of the primary user: their total power budget and the allowable interference threshold at the primary receiver. Power and subcarrier allocation problems are detailed in order to maximize the system sum rate. In this work, we highlight the benefits of the proposed multiuser adaptive algorithm which encompasses three phases. The first step includes the adaptive selection of the decoding strategy at the secondary receiver which is either treating interference as noise or performing successive interference cancelation or superposition coding. The second step describes the subcarrier allocation among the different users. Finally, the third step details the optimal distribution of the available power budget on the users. The problem is first treated assuming perfect channel state information (CSI). The simulation results show that our proposed scheme achieves higher secondary and sum rates compared to existing approaches with perfect CSI. The robustness of the proposed algorithm when the secondary user has only partial information about channel gains is also derived.