New Constrained Quantum Optimization Algorithm for Power Allocation in MIMO

Multiple-input multiple-output (MIMO) has acquired significant interest as the demand for high data rates has increased and, it is regarded as a key technique in 5G wireless technology. Previously, the water filling algorithm (WFA) has been found as an effective method for power allocation channels in (MIMO). However, this solution is computationally intractable owing to the increasing size of channels. To address this problem, this paper applies the constrained quantum optimization algorithm (CQOA) for reducing the overall transmit power and the computational complexity of the MIMO downlink system. An analytical comparison has been performed between the CQOA and water filling algorithm-based binary searching algorithm (WFA-BSA). Numerical results show the efficiency of the CQOA against the WFA-BSA in terms of power and computation.