Characterisation of nonlinear distortion and intermodulation in passive devices and antennas

Shitvov, Alexey; Schuchinsky, Alexander; Steer, M.B.; Wetherington, Joshua M.

doi:10.1109/eucap.2014.6902055

Cited by 22 publications

(6 citation statements)

References 14 publications

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“…If the source of the nonlinearity is a passive device, the distortion is called passive intermodulation (PIM) [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]. Typically, loose connections of cables, filters, switches, antennas [12], [13], [14], [15], [18], [19], [20], [21], or even external metallic objects in the radiation field of the antennas [16], [17] can be the cause of PIM. The PIM caused by external sources is in focus in this work, and such distortion is referred to as airinduced PIM.…”

Section: Introductionmentioning

confidence: 99%

Air-Induced Passive Intermodulation in FDD MIMO Systems: Algorithms and Measurements

Lampu

Anttila

Turunen

et al. 2023

IEEE Trans. Microwave Theory Techn.

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In this article, we model and develop effective cancellation schemes for passive intermodulation (PIM) distortion induced by external objects in the vicinity of the transmitterreferred to as air-induced PIM-in frequency-division duplex (FDD) multiple-input-multiple-output (MIMO) systems. PIM is interference generated from the transmitted signals undergoing nonlinear transformation, which, in FDD systems, may cause desensitization of the receiver chain. First, we present a general model of the received air-induced PIM signal, with an arbitrary number of dual-carrier TX chains active and an arbitrary number of PIM sources causing interference, on all the intermodulation frequencies. Then, the derived model is used to develop a cancellation scheme based on a complete set of basis functions (BFs) in a rank-2 dual-carrier MIMO system with four active carriers. To alleviate the high complexity of the aforementioned scheme, we then propose a novel alternative cancellation scheme with much reduced complexity, leveraging on the physical modeling of the system, which is capable of handling any number of PIM sources in the system. RF measurementbased experimentations carried out with real-life equipment evidence excellent cancellation capabilities of the complete BF model, which can be retained with much reduced complexity with the proposed alternative technique.

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Section: Introductionmentioning

confidence: 99%

Air-Induced Passive Intermodulation in FDD MIMO Systems: Algorithms and Measurements

Lampu

Anttila

Turunen

et al. 2023

IEEE Trans. Microwave Theory Techn.

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“…This work showed that PIM interference could be mitigated by clean contact surfaces and stable contact pressures. Shitvov et al [9] and Shitvov and Kozlov [10] explored the characteristics of PIM generated by the distributed passive nonlinearities of a transmission line. They characterised the impact of PIM in terms of fidelity metrics for analogue and digitally modulated signals in the receiver path of an RF front-end circuit.…”

Section: Introductionmentioning

confidence: 99%

Identification and location of PIM faults in radio‐frequency circuits with multiple coaxial connectors using a neural network approach

Jin

Gao

Flowers

et al. 2019

IET Microwaves, Antennas & Propagation

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Coaxial connectors are widely used in radio‐frequency circuits and are a major non‐linear source of passive intermodulation (PIM), especially when they are subjected to environmental degradation. Accordingly, an effective and accurate method to locate the position of the PIM source in a communication system is of substantial value. By analysing the characteristics of different connectors, equivalent circuit models were developed to generate dynamic harmonics powers. On the basis of transmission line theory and simulations, the features of the IM products (IM3, IM5, and IM7) in a series circuit with the selected PIM source points were investigated. Using this information, a PIM fault diagnosis method for coaxial connectors in a circuit was developed employing a neural network. The IM products powers were obtained as feature parameters using a scattering parameter simulation of series circuit for three different connectors. Simulations were then conducted to generate training and testing samples. Finally, using the back‐propagation neural network algorithm, the fault modes were classified and the results show diagnosis accuracy was 96.72%.

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“…Because of the very large power level difference between transmit and receive signals and the limitation of frequency allocation, intermodulation (IM) interference due to passive residual nonlinearities in the high-power transmission path can be a real problem. The passive intermodulation products (PIMP) that fall into the receiving band will seriously degrade system performance [1, 2]. With the rapid development of communication technology and the extensive application of passive microwave devices, the passive intermodulation (PIM) gradually becomes more and more valued [3].…”

Section: Introductionmentioning

confidence: 99%

Passive intermodulation model and experimental verification of cascaded microwave devices

Zhang

Jiang

2017

Int. J. Microw. Wireless Technol.

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Passive intermodulation (PIM) is a complex problem in high-power microwave devices and satellite communications. In this paper, an effective calculation method is proposed for predicting PIM power levels of the cascaded microwave devices. First of all, the analytical formula of intermodulation voltage is derived based on the nonlinear I–V characteristics of microwave devices. Then, the mathematical model of point sources is constructed by the transmission line theory and extended to the cascaded microwave devices. The passive intermodulation products (PIMP) of the cascaded microwave devices are evaluated based on the point-source model. The relationship of PIM between a single microwave device and the cascaded system is revealed. Eventually, the corresponding experiments are designed to verify the accuracy of point-source model and the cascaded model to predict the third-order PIM power level, which address the problem of PIM prediction of the cascaded microwave devices.

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Characterisation of nonlinear distortion and intermodulation in passive devices and antennas

Cited by 22 publications

References 14 publications

Air-Induced Passive Intermodulation in FDD MIMO Systems: Algorithms and Measurements

Air-Induced Passive Intermodulation in FDD MIMO Systems: Algorithms and Measurements

Identification and location of PIM faults in radio‐frequency circuits with multiple coaxial connectors using a neural network approach

Passive intermodulation model and experimental verification of cascaded microwave devices

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