| Summary: | This paper provides a concise overview of recent developments in sparse antenna arrays, with a specific focus on techniques for reducing mutual coupling. It explores the concept and definitions of sparse arrays in different applications, highlighting their historical significance in antenna theory. The paper addresses the mutual coupling problem and presents reduced coupling geometrical configurations through illustrative examples. Various mutual coupling compensation techniques are discussed. The paper conducts a comprehensive comparison of multiple array design optimisation techniques, including genetic algorithm, covariance matrix adaptation evolution strategy, particle swarm optimisation, trust-region framework, Nelder-Mead simplex algorithm, interpolated Quasi-Newton, and classic Powell. The comparison emphasizes achieving desired radiation performance and evaluates the mutual coupling coefficient using <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> planar arrays and <inline-formula> <tex-math notation="LaTeX">$16\times 1$ </tex-math></inline-formula> linear arrays with typical patch antennas in the mmWave bands. Notably, the paper considers optimised non-uniform antenna element positioning within the arrays, which has shown promising results in reducing mutual coupling. The study also introduces the application of beam steering to these optimised non-uniform arrays, demonstrating resilience to beam steering degradation and potential performance improvements. The findings indicate that particle swarm optimisation generally provides the most consistent performance across the discussed optimisation problems.
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