Mohammad Jaleel Akhtar

Battery-free Internet of Things (IoT) systems require wireless power transfer (WPT) receivers that are robust to variations in orientation and polarization. Conventional rectennas, however, exhibit strong directional sensitivity and limited adaptability, which constrains their practical deployment. This review presents a unified synthesis of three emerging rectenna architectures developed to mitigate angular misalignment, flat-beam rectennas, multidirectional rectennas, and metasurface-assisted lens rectennas. A comparative taxonomy is developed to systematically evaluate these approaches in terms of angular coverage, RF–DC conversion efficiency (ηRF-DC), implementation complexity, and scalability. Beyond summarizing recent advances, this paper analyzes persistent research gaps common to all techniques, including narrowband operation, limited system-level validation, and manufacturing constraints. A decision-oriented framework is further proposed to guide architecture selection for application-specific scenarios, such as mobile, wearable, and fixed IoT deployments. Convergent future research directions are outlined, including adaptive and broadband designs, multifunctional integration, and emerging concepts such as dynamic metasurfaces, to support the development of pervasive, orientation-independent wireless power solutions for next-generation IoT networks.

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Near-field microwave imaging is a promising non-contact method for detecting subsurface anomalies. However, the impact of the air gap between the antenna and target on the image quality has not been systematically studied. In addition, many reconstruction techniques require background data, making reference-free imaging important for practical applications. This study investigates how antenna-to-target spacing affects imaging using a 1-port reflection-based setup with four patch antennas operating at 1.5, 2.43, 3, and 4 GHz. A distinct “null-point”- the standoff distance where the reflection coefficient is minimized - is identified and validated as the optimal spacing via simulations and experiments. ABS, clay, and water were used as dielectric targets with a water-filled container embedded in clay to simulate anomalies. For solid ABS, the first null-point ranges from 0.125λ₀ at 1.5 GHz to 0.03λ₀ at 4 GHz, with a larger range for the water-filled ABS block. The simulation and experimental results were in close agreement. A novel multi-spacing reference-free approach to near-field microwave imaging for subsurface anomaly detection with high contrast was presented. At optimal spacing, the Michelson contrast for water anomaly detection at 3 GHz increased to 74.5% compared to 42.4% at non-optimal spacing. The final reference-free images produced using the multi-spacing algorithm provided a contrast of 93.6% in the simulation and 91.2% in the measurement, validating the superior contrast performance of this approach. The Dice Loss also decreased from 0.251 to 0.116, demonstrating improved localization accuracy. This approach offers a cost-effective and practical solution for real-world deployment, without requiring reference data.