Carrier Aggregation for Cooperative Cognitive Radio Networks

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 7; pp. 5904 - 5918
• Main Authors: Diamantoulakis, Panagiotis D., Pappi, Koralia N., Muhaidat, Sami, Karagiannidis, George K., Khattab, Tamer
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agglomeration; Amplify-and-forward (AF); carrier aggregation (CA); Cognitive radio; cognitive radio (CR); Convexity; decode-and-forward (DF); dynamic power allocation; Frequencies; Interference; OFDM; Optimization; Power management; Relay; relay selection; Relaying; Relays; Resource management; Throughput; User requirements; Wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2016.2635112

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints.