Mixed-Signal Based Enhanced Widely Linear Cancellation of Modulated Spur Interference in LTE-CA Transceivers

Kanumalli, Ram Sunil; Elmaghraby, Ahmed; Gebhard, Andreas; Paireder, Thomas; Auer, Christina; Huemer, Mario

doi:10.1109/acssc.2018.8645528

Cited by 7 publications

(8 citation statements)

References 5 publications

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“…Mixed signal solutions employ an auxiliary receiver with less stringent requirements than a normal receiver, which often leads to designs, where low IRR is even more an issue [22], [23]. Digital signal processing is then used to improve the IRR [24]. More general algorithms consider a frequency selective imbalance.…”

Section: A Prior Approaches For I/q Imbalance Compensationmentioning

confidence: 99%

Ultra-Low Complex Blind I/Q-Imbalance Compensation

Paireder¹,

Kanumalli²,

Sadjina³

et al. 2019

IEEE Trans. Circuits Syst. I

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Direct-conversion transceivers are the predominating architecture in current mobile communication systems. Despite many advantages, this topology suffers from unavoidable mismatches in the analog part, which causes imbalance between the in-phase and quadrature (I/Q) component. In this paper, we present a novel fully digital, blind I/Q imbalance compensation algorithm that features extremely low computational complexity and high compensation performance for a wide range of input signal types. Different to many state-of-the-art compensation schemes, the approach is not based on a gradient descent optimization and does not require any global feedback. This simplifies the implementation at high data rates and reduces the configuration effort to a minimum. For comparison, we examine an existing method of moment-based estimator with similar properties, for which we also provide the detailed insights beyond available literature. For both algorithms, we provide a rigorous mathematical analysis, which is supported by simulations with a focus on various long-term evolution (LTE) signal types. In addition, hardware architectures, including field-programmable gate array (FPGA) verification, are presented for both algorithms.

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Section: A Prior Approaches For I/q Imbalance Compensationmentioning

confidence: 99%

Ultra-Low Complex Blind I/Q-Imbalance Compensation

Paireder¹,

Kanumalli²,

Sadjina³

et al. 2019

IEEE Trans. Circuits Syst. I

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“…We conclude our investigations with an interference cancellation example from cellular communications [5], where the inference function f is non-holomorphic. The goal is to suppress an unwanted signal of the form y main , x[n].…”

Section: Widely-linear Estimation Examplementioning

confidence: 80%

Normalized stochastic gradient descent learning of general complex‐valued models

Paireder

Huemer

2021

Electronics Letters

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The stochastic gradient descent (SGD) method is one of the most prominent first-order iterative optimisation algorithms, enabling linear adaptive filters as well as general nonlinear learning schemes. It is applicable to a wide range of objective functions, while featuring low computational costs for online operation. However, without a suitable step-size normalisation, the convergence and tracking behaviour of the stochastic gradient descent method might be degraded in practical applications. In this letter, a novel general normalisation approach is provided for the learning of (non-)holomorphic models with multiple independent parameter sets. The advantages of the proposed method are demonstrated by means of a specific widely-linear estimation example.

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“…For low noise levels and practical signal lengths, the performance of the estimator hardly depends on the initial IRR. We chose a rather low value of 15 dB, which could, for example, result from a low-cost design of the analog (Aux) receiver components [18], [19]. The simulations were performed in floating-point arithmetic on LTE-20 signals with a length of 21 symbols or approximately 46 000 samples [28].…”

Section: B Performance Simulationsmentioning

confidence: 99%

“…A much more important metric is SNR s , which is commonly lower than SNR r . To quantify the performance loss due to noise, we consider three different antisymmetric allocations The initial IRR was set to 15 dB, which matches a low-cost Aux receiver [18], [19]. The signal length for estimation is 1 symbol or about 2200 samples.…”

Section: E Performance Simulationsmentioning

confidence: 99%

“…With its low computational complexity, the moment-based estimator is perfectly suitable for user equipment (UE), which is the focus of this paper. The target application of this work is imbalance cancellation in a lowcost auxiliary (Aux) receiver that provides the reference signal for mixed-signal self-interference cancellation (SIC) [18], [19], as depicted in Fig. 1.…”

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confidence: 99%

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