Abstract
A robust resource allocation (RA) algorithm for cognitive relay networks with multiple primary users considering joint channel uncertainty and interference uncertainty is proposed to maximize the capacity of the networks subject to the interference threshold limitations of primary users’ receivers (PU-RXs) and the total power constraint of secondary user’s transmitter and relays. Ellipsoid set and interval set are adopted to describe the uncertainty parameters. The robust relay selection and power allocation problems are separately formulated as semi-infinite programming (SIP) problems. With the worst-case approach, the SIP problems are transformed into equivalent convex optimization problems and solved by Lagrange dual decomposition method. Numerical results show the impact of channel uncertainties and validation of the proposed robust algorithm for strict guarantee the interference threshold requirements at different PU-RXs.
Highlights
Cognitive radio (CR) is a promising technology to alleviate the looming spectrum scarcity crisis by opportunistic accessing the licensed spectrum [1]
In underlay mode of CR networks (CRNs), secondary users (SUs) can share the same radio spectrums allocated to primary users (PUs), provided that the interference to PUs’ receivers (PU-RXs) generated by SUs’ transmitters (SU-TXs) are below the specified interference thresholds [2]
Orthogonal frequency division multiplexing (OFDM) is widely accepted as a potential air interface physical layer technology for CRNs owing to its high flexibility for allocating radio resources [3]
Summary
Cognitive radio (CR) is a promising technology to alleviate the looming spectrum scarcity crisis by opportunistic accessing the licensed spectrum [1]. Yang and Zhao EURASIP Journal on Wireless Communications and Networking (2017) 2017:107 selection, and power allocation scheme is obtained in DF relayed OFDM-based cognitive system under the individual power constraints in source and relays These optimization problems with perfect CSI are referred as the nominal problems [11]. In [18], the authors study robust worst-case interference control and use general norm and polyhedron model to describe channel uncertainty set in underlay CRNs. Bayesian approach handles uncertainty parameters with certain statistical properties and satisfies QoS of PU-RXs in a probabilistic manner. Different from most existing literatures, this paper investigates the robust RA problem for OFDM-based cognitive relay network with multiple PUs, where channel uncertainty and interference uncertainty are all considered.
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