Design of sub-6 GHz BPF using chained even and odd mode admittance polynomials for 5G C-band applications

• The paper introduces a new filter topology using chained filtering functions (CFFs) for fourth-order filters, resulting in a compact design. • The filter demonstrates reduced sensitivity to fabrication variations, a critical improvement for high-frequency components. • The designed filter exhibits better performance than traditional Chebyshev filters in terms of insertion loss, selectivity, and stability. • The research employs both circuit simulation (ADS) and electromagnetic simulation (HFSS) for design and verification, followed by prototype fabrication and measurement to validate the theoretical findings. This paper presents the design of a Bandpass filter (BPF) using chained even and odd mode admittance polynomials for 5G sub-6 GHz C-band applications. The filter will offer a reduced sensitivity to fabrication tolerance and still maintain its response in comparison to traditional Chebyshev filters. A new transfer function based on chained filtering functions (CFFs) for fourth-order filters is derived in even and odd mode admittances and the synthesis methods are presented. To demonstrate the feasibility of the proposed approach, a 4 th -order chained-function filter (CFF) operating at the center frequency of 3.5GHz with a bandwidth of 40MHz is designed, synthesized, and fabricated. The circuit simulation is carried out in advanced simulation software (ADS). The filter prototype is fabricated in parallel-connected topology using an open-loop microstrip resonator, the size of the filter is 2.5cm x 4cm. The simulation and measured insertion/return loss are 0.40dB / 20dB and 2.5dB/18.08dB, and the achieved selectivity is 87.5. Considerable Sensitivity analysis to prove the filter fabrication tolerance is conducted and its reliability is proven by theoretical analysis. The prototype result in this work is validated and agrees well with the theoretical results. In terms of practical implementation, this design technique will serve as a very useful mathematical tool for filter design engineers.