This work investigates the energy efficiency (EE) and the spectral efficiency (SE) performance of multi-hop full duplex cognitive relay networks (MH-FDCRNs) operating in the spectrum sharing mode, under the influence of interference from the primary source. We formulate three distinct optimization problems for finding the optimal power allocation (OPA) for the secondary nodes in MH-FDCRN: (i) EE optimization with minimum SE requirement; (ii) SE optimization with minimum EE requirement; and (iii) EE-SE trade-off optimization. The impact of residual self-interference (RSI) arising due to full duplex operation at the relay nodes and the inter relay interference (IRI) arising due to frequency re-use are considered. For the EE/SE optimization problems, we transform the original non-convex optimization problems to their convex forms by expressing the numerator of the objective function as the difference of concave functions, and by using parametric transformation. For the EE-SE trade-off optimization problem, we first transform the original multi objective optimization problem into a single objective form; and then into its convex form by introducing an auxiliary variable. Computationally efficient algorithms are proposed to solve the considered problems. The convergence properties of the proposed algorithms are established through mathematical analysis as well as through computer simulation studies. We prove that the points of convergence of the proposed iterative algorithms are the Karush-Kuhn-Tucker (KKT) points of the initial non-convex problems. With the help of detailed numerical results, the best trade-off among EE and SE can be achieved by proper selection of priority factor, compared to the individual optimization approaches.

This study investigates optimal power allocation (OPA) for maximising the energy efficiency (EE) of dual‐hop underlay full‐duplex cognitive relay network, under the influence of interference from primary source. The OPA for the EE optimisation is constrained on the maximum transmit power of the secondary nodes and the interference threshold power which can be tolerated at the primary destination. The authors convert the initial non‐convex optimisation problem to a concave fractional programming form and propose an iterative algorithm using parametric transformation to find the OPA vector. Further, they prove that the point of convergence of the proposed iterative algorithm is a Karush–Kuhn–Tucker point of the initial non‐convex problem. They numerically demonstrate the EE improvement achieved by the proposed algorithms over equal power allocation strategy.

The unique iris pattern of each human eye is complex, but easily be scanned or captured by a camera. However, the high cost infrared iris scanners used for acquisition causes inconvenience to users by distance related constraints. This restricts its widespread use in real-time applications such as airports and banks. The images captured by cameras under visible wavelength are obstructed by the presence of reflections and shadows which requires additional attention. The main objective of this paper is to propose a secure biometric iris authentication system by fusion of RGB channel information from the real-time data captured under visible wavelength and varying light conditions. The proposed system is adapted to a real-time noisy iris dataset. The effectiveness of this proposed system was tested on two different color iris datasets, namely, a public database UBIRISv1 and a newly created database SSNDS which contains images captured with any digital/mobile camera of minimum 5MP under unconstrained environments. This system supports the cross sensor acquisition and successful iris segmentation from these unconstrained inputs. The features from each channel are extracted using log Gabor filter and a matching is performed using hamming distance based on two thresholds (inter and intra class variations). The performance quality of the proposed biometric system leads to the feasibility of a new cost-effective approach for any real-time application, which requires authentication to ensure quality service, enhance security, eliminate fraud, and maximize effectiveness.