Considerations When Using RX Window Filters

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Considerations When Using RX Window Filters

Multi-pole window filters are commonly used as front-end filters in receive multicouplers. EMR Multicouplers always come equipped with a standard multi-pole front-end filter. In contrast, other OEMs often require an additional line item and cost to integrate a front-end filter into their multicouplers. Multi-pole filters are well-suited for applications with a receive bandwidth of at least 2 MHz, extending up to 10 MHz. However, when the bandwidth falls below 2 MHz, both the insertion and return loss of the multi-pole window filter are compromised. In such cases, a 1/4 wave cavity assembly should be considered as a replacement for the standard multi-pole filter.

Selecting the appropriate front-end filter for a receive multicoupler entails conducting a thorough site Desense Study. This study encompasses factors such as transmit frequencies, transit power, receive frequencies, and antenna decoupling between TX and RX antennas. The goal is to determine the ideal front-end filter set that can deliver the required rejection (RX-TX isolation) to prevent a 1 dB reduction in a 12 dB SINAD ratio due to transmitter carrier interference. The Desense Study also prescribes the necessary filtering for each transmit channel, and it should encompass an evaluation of an Intermodulation (IM) Study as well!

Cavity front-end filter sets offer a versatile solution, capable of incorporating both bandpass and pass notch cavity elements. These elements work to enhance RX-TX isolation. Moreover, they afford the flexibility to provide pass bandwidths ranging from a few tens of kHz to 2 MHz in VHF or UHF, extending up to 5 MHz for frequencies like 700, 800, and 900 MHz.When site conditions necessitate, we will recommend replacing the standard multi-pole window filter with a configuration comprising either a 1/4 wave or 3/4 wave front-end filter set. The selection between 1/4 wave, 3/4 wave, bandpass cavities, pass notch cavities, and their quantities depends entirely on the the Desense Study matrix.

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