This paper considers the resource allocation for cognitive decode-and-forward (DF) relay networks, where a cognitive radio (CR) can access the spectrum under the coexistence constraints. This CR user is assumed to adopt the celebrated orthogonal frequency division multiplexing (OFDM) technique. Our objective is to maximize the rate of the CR user by appropriate power allocation and subcarrier pairing under the individual power constrains at the source and the relay; while the interference to the primary user (PU) must be kept below a target. To resolve the corresponding mixed integer programming (MIP) problem with reasonable cost, new heterogeneous genetic algorithms (HGA) with initialization methods inspired by convex optimization are proposed. To further reduce complexity, an efficient two-stage implementation of the HGA is also presented. Conducted simulations show that our HGA provides superior performance to previous works.
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