A Lens-Based Digital Beamforming Array With Enhanced Gain for Massive MIMO Applications

In this paper, a novel optimization framework based on ballistic simulation bifurcation within quantum-inspired algorithms is proposed to optimize the beamforming performance of lens antenna arrays. The method utilizes a quantum-inspired bifurcation algorithm grounded in the principles of quantum adiabatic computation and classical mechanics. The core optimization approach combines stochastic gradient descent (SGD) with a quantum-inspired perturbation mechanism to efficiently explore the solution space and avoid local minima. In addition, a 4×6-element base station antenna array is adopted to illuminate an 11×11- element square lens with a focal diameter ratio (F/D) of only 0.38. The simulated results show that the optimized lens antenna achieves a gain exceeding 1.5 dB over the pre-optimization gain for a single beam at 6.8 GHz, with beam scanning across the range of -30⁰∼30⁰. The proposed method is capable of enhancing directivity, reducing power loss, and providing potential advantages for beam steering applications.