 ICACT20260284 Slide.01
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This is my presentation outline, which includes the Introduction, Proposed Method, Simulation and Experimental Verification of the Proposed Method, and Conclusions. |
| ICACT20260284 Slide.02
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This is my prsentation outline. Including introduction, Propossed method, Simulation and experimental Verification of The Proposed method and conclusions 4 parts.
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| ICACT20260284 Slide.03
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Wireless communication systems primarily operate in half-duplex mode because of the substantial self-interference that arises from simultaneous transmission and reception on the same frequency band. Despite the potential for higher spectrum efficiency in wire-less full-duplex transmission, effectively mitigating self-interference for full-duplex wire-less receivers remains a critical challenge.
To address this problem, the present study developed an innovative approach for suppressing distortions that arise from in-phase and quadrature (IQ) imbalance, nonlinear power amplifier (PA) responses, and self-interference caused by simultaneous transmissions on the same frequency in RF communication systems.
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| ICACT20260284 Slide.04
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Existing methods for mitigating RF signal distortion, such as antenna separation and self-interference cancellation, are limited by their demands on computational capacity and by the physical size of the hardware used to run them.
To overcome these limitations, active RF cancellation architecture and compensation rules are used in the proposed method, with direct RF cancellation of self-interference signals conducted at the receiver. This method differs from the receiver-side interference suppression technique proposed and ensures that subsequent components, such as the low-noise amplifier, do not exacerbate the nonlinear distortion induced by self-interference.
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| ICACT20260284 Slide.05
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In the proposed method, an auxiliary transmission path is employed to actively cancel self-interference by combining channel response parameters with an active RF cancellation filter.
The progressive compensation for individual distortion factors, including IQ imbalance (IQI) and nonlinear PA response in the proposed method, enables sequential suppression of all types of distortion, ultimately facilitating successful full-duplex communication.
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| ICACT20260284 Slide.06
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RF distortions at the transmitter are caused by the following factors:
IQ imbalance, Nonlinearity in PA responses, Self-interference in MIMO operation, and RF cancellation
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| ICACT20260284 Slide.07
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The block diagram of the proposed multiantenna full-duplex transceiver system. This system contains a predistortion compensation system for the transmitter, which is essential for realizing robust, multiantenna full-duplex communication.
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| ICACT20260284 Slide.08
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The transceiver of the proposed system comprises distinct transmission and reception units, each of which uses similar signal-processing methodologies. At the transmitter end, the following RF distortion factors are sequentially processed.
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| ICACT20260284 Slide.09
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Steps involved in the proposed method:
Step 1: Using a linear region of the PA signal input to obtain estimated values of the IQI factor.
Then utilizing this estimated value, the IQI pre-compensation parameter values for the RF link are obtained.
Step 2:Perform IQI pre-compensation processing for multiple RF links (overcoming IQI distortion factors). Then utilize signals in the nonlinear region of the PA to obtain estimated values for the memory polynomial factors of the PA nonlinearity. Finally, Use these estimated values to determine the DPD parameters for compensating PA nonlinearity.
Step 3: Conduct DPD predistortion compensation on multiple RF chains to overcome the PA nonlinearity factor. Then perform IQI pre-compensation processing on multiple RF chains to overcome IQI distortion factors, and obtain self-interference factor estimation values using a dedicated receiving antenna. Finally, calculate the parameter values of the dedicated auxiliary transmitters reconstruction canceller using the estimated values.
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| ICACT20260284 Slide.10
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Initially, algorithms were employed from theoretical study and simulation analysis. Subsequently, the developed method was experimentally validated by implementing it on a software-defined radio (SDR) platform.
The ultimate objective was to create a platform that seamlessly integrates RF modules with FPGAs and suppresses all types of RF distortion.
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| ICACT20260284 Slide.11
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The estimated channel response, which includes the IQ imbalance, is used to calculate pre-compensation parameters for the auxiliary path. This process enables the design of an active RF generalized linear filter for distortion cancellation. Figures indicate that the transmission signals in the main path and auxiliary path are affected by IQ imbalance.
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| ICACT20260284 Slide.12
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The unknown channel response values can be estimated using the least mean square (LMS) method. The recursive relationships are expressed as follows:
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| ICACT20260284 Slide.13
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PA must achieve high efficiency and linearity. Nonlinearity in the PA response can cause spectral regrowth, leading to interference in neighboring channels. Such nonlinearity can be represented using a memory polynomial (MP) model, described in indirect learning architecture (ILA) are employed for DPD. Can be formulated as follows: |
| ICACT20260284 Slide.14
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The DPD parameter can be derived using the least squares method as follows:
The dimensions of Y are N*L, where N is the signal length and L represents the number of DPD parameters.
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| ICACT20260284 Slide.15
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The self-interference encountered in multiantenna systems by describing advanced compensation techniques for improving the overall transmission performance of multiantenna communication systems.
The architecture of a generalized linear cancellation filter for the pre-compensation parameters in the auxiliary path.
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| ICACT20260284 Slide.16
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The parameters are determined through the least squares method by using a pseudoinverse matrix as follows:
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| ICACT20260284 Slide.17
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First, I would like to show the simulation verification of the elimination of RF IQ Imbalance
The PA operates in its linear region, where the IQ imbalance parameter estimation and pre-compensation are performed. The condition assumed a phase imbalance of 2° and an amplitude imbalance of 2 dB.
The convergence curve of the estimated parameters shows that convergence was achieved after approximately 300 samples.
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| ICACT20260284 Slide.18
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After applying IQ imbalance pre-compensation, the image tone of the single-tone signal was suppressed by about –61 dB, with its amplitude reduced from 6546.76 to 5.83. The above simulations confirm the excellent IQ imbalance suppression performance achieved in Step 1.
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| ICACT20260284 Slide.19
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Second, I would like to show the experimental verification of the compensation for nonlinear PA response. This scenario corresponded to the integrated process of Step 1 and Step 2. Where IQ imbalance pre-compensation was first applied, followed by nonlinear PA pre-compensation. The spectra before and after IQ imbalance/DPD preprocessing.
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| ICACT20260284 Slide.20
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To validate the proposed method, we used a software-defined radio (SDR) platform. The signal modified based on the compensation parameters was transmitted through the M3Force C1065B transceiver module to the spectrum.
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| ICACT20260284 Slide.21
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First, an original 16-QAM signal with an IQ imbalance was generated using MATLAB. This signal was transmitted through the M3force C1065B transceiver module, including a nonlinear PA response into it.
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| ICACT20260284 Slide.22
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Second, a 16-QAM signal that was pre-compensated for IQ imbalance was generated. This signal was then passed through the DPD block of the PA DPD to obtain DPD coefficients.
Third, the signal with DPD coefficients was transmitted through the transceiver module, including the PA, to add a nonlinear PA response to it. |
| ICACT20260284 Slide.23
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The compensation effects were then analyzed using a spectrum analyzer. The results reveal a reduction of approximately 4 dB in adjacent channel power.
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| ICACT20260284 Slide.24
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Third, I would like to show the experimental verification of the compensation for IQI, nonlinear PA response and MIMO Linear self-interference. Step 3 of the proposed method was performed using the channel response parameters for the main and auxiliary transmission paths. The main path contained a 16-QAM signal with an IQ imbalance that was corrected for the IQ imbalance and pre-compensated for a nonlinear PA response. The auxiliary path contained the 16-QAM signal with a different training code.
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| ICACT20260284 Slide.25
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Both signals were simultaneously transmitted through the transceiver module, with the coupled signal affected by self-interference.
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| ICACT20260284 Slide.26
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The coupled signal was received by the transceiver module at the receiver end, and MATLAB was used to calculate the preprocessing parameters for self-interference compensation.
The aforementioned filter began computation after the switch was activated to enable the cancellation function. Moreover, the switch function “clear” was changed to “cancellation ”.
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| ICACT20260284 Slide.27
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The main path contained a 16-QAM signal with IQ imbalance, compensation parameters for the IQ imbalance, and pre-compensation parameters for the nonlinear PA response.
The auxiliary path contained the 16-QAM signal with a preprocessing parameter for self-interference compensation.
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| ICACT20260284 Slide.28
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The signals from both paths were combined using the coupler, and the combined signal was examined using the spectrum analyzer. The preprocessing parameters for the self-interference compensation reduced the power of the coupled signal by 34 dBm. This result confirms that self-interference can be eliminated through direct RF reception after transmission.
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| ICACT20260284 Slide.29
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This study developed a method for eliminating distortion arising from IQ imbalance, a nonlinear PA response, and MIMO self-interference in wireless RF signal transmission. In this method, a precoding signal is generated through digital signal-processing techniques and then transmitted through an auxiliary signal transmission path.
The proposed method involves three steps, with each step sequentially addressing the aforementioned distortion factors without requiring complex mathematical modelling of distortion components.
The proposed method also ensures that signal saturation does not occur, thereby preventing the generation of nonlinear components.
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| ICACT20260284 Slide.30
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The proposed distortion cancellation method was experimentally validated on SDR platform. The experimental results suggested that the proposed method reduced the distortion by approximately 20 dBm, thus demonstrating excellent performance.
The proposed method can be employed in full-duplex communication technology to effectively suppress the distortion caused by IQ imbalance, nonlinear PA responses, and self-interference in multiple channels.
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| ICACT20260284 Slide.31
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The following references are provided for your reference. |
| ICACT20260284 Slide.32
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This is the end of my presentation. Thanks for your listening. |
