SDO and LDO relaxation approaches to complex fractional quadratic optimization

This paper examines a complex fractional quadratic optimization problem subject to two constraints. The original is transformed into parametric programming by the well-known classical Dinkelbach method. Then semidefinite and Lagrangian dual approaches are presented solve nonconvex at each iteration of bisection generalized Newton algorithms. Finally, numerical results demonstrate effectiveness proposed approaches.