Adaptive Interference Cancellation Research Articles

Nonlinear energy harvesting based alternate cooperative nonorthogonal multiple access with adaptive interference cancellation

We consider an energy-limited network, where a source node intends to communicate with two energy harvesting (EH) near-users and one far-user. We design a nonlinear EH-based alternate cooperative nonorthogonal multiple access (CNOMA) scheme, where the source node alternately superimposes the data of each near-user and the far-user and broadcasts the composite signal. When one near-user decodes the data of both the far-user and itself by using the adaptive interference cancellation technique, the other near-user can harvest energy from the received signal. The two near-users alternately and adaptively forward data to the far-user. We properly model the energy statuses of both the two near-users by defining a group of unequally-spaced discrete energy levels. We analyze the average success probability and throughput of each user, and use the differential evolution (DE) algorithm to efficiently achieve the maximum system throughput by jointly optimizing both the time and power allocation factors. We also present two benchmark EH-based transmission schemes for comparison. Extensive simulations are conducted to validate our theoretical analysis and reveal the impacts of various parameters.

Analysis and Optimization on Weight Accuracy of the Adaptive Interference Cancellation

Analysis and Optimization on Weight Accuracy of the Adaptive Interference Cancellation

Performance evaluation on a convolutional neural network with adaptive interference cancellation for detecting a buried person's voice in a disaster situation

In a disaster situation, rapid detection of victims is critical to prevent life-threatening accidents. However, it is not easy to detect the target's sound due to noise and interference which are difficult to predict. In addition, it is difficult to collect acoustic data in disaster situations. Therefore, this study proposes a target detection scheme in which untrained noise is added through a binary classification model trained only with a clean target signal and additive white Gaussian noise (AWGN). The feature uses the Mel spectrogram of the signal, and the model adopts a convolutional neural network (CNN). Two acoustic sensors are used in this study to adaptively remove environmental noise and a CNN to detect target signals. The first process trains a CNN using the target signal and AWGN data. In the next step, environmental noise is removed by compensating for the gain difference and delay characteristics between the two acoustic sensors through adaptive filtering. The input signal passes through preprocessing to eliminate noise through an adaptive filter. This signal is converted into a Mel spectrogram, which is then detected through a CNN model. The simulation results show that the model improves from 50% to 99% in detection rate at SNR 0 dB. In a catastrophe, there are many sounds that are difficult to discern. However, the model cannot learn from noise. Therefore, it shows that the target detection method using adaptive filter-based noise cancellation is effective in disaster situations.

Modeling and analysis for group delay mismatch effect on wideband adaptive spatial interference cancellation

The adaptive interference cancellation technique has been widely utilized in radar, GPS, data link, etc., systems to address challenges from external interference, such as co-site and hostile interference. Since the anti-jamming performance of the adaptive interference cancellation technique is sensitive to group delay mismatch between channels, the group delay mismatch becomes one of the main factors that limit the system’s anti-jamming capability. However, the traditional adaptive interference cancellation system’s mathematical model cannot quantitatively characterize the group delay mismatch effect on the wideband interference cancellation performance. In this paper, the mathematical model of the wideband adaptive spatial interference cancellation (ASIC) system is established, which considers the group delay mismatch, to quantitatively analyze the impact of group delay mismatch on the hostile interference cancellation. The mathematical model utilizes the weighted multi-tone signals to fit the wideband interference, and then, delay differences are attached to each tone signal to simulate the group delay mismatch. Then, the analytic expressions of weight and interference cancellation ratio are derived, which consider the interference bandwidth and group delay mismatch, to quantitatively analyze the group delay mismatch effect on the anti-jamming performance of the wideband ASIC system. Simulation results indicate that the theoretical analysis based on the mathematical model of wideband ASIC system are accurate, which can achieve the quantitative analysis of the group delay mismatch effect on the WIC performance.

Real-time 14N NQR-based sodium nitrite analysis in a noisy field

Noise and Radio-frequency interference or RFI causes a significant restriction on the Free induction Decay or FID signal detection of the Nuclear Quadrupole Resonance procedure. Therefore, using this method in non-isolated environments such as industry and ports requires extraordinary measures. For this purpose, noise reduction algorithms and increasing signal-to-noise-and-interference ratio or SNIR have been used. In this research, sodium nitrite has been used as a sample and algorithms have been tested in a non-isolated environment. The resonant frequencies for the 150 g of test sample were measured at 303 K at about 1 MHz and 3.4 MHz. The main novelty in this study was, (1) using two types of antennas in the receiver to improve adaptive noise and interference cancellation, (2) using a separate helical antenna in the transmitter to eliminate the duplexer, (3) estimating the noise before sending the pulse to calculate the weighting factors and reduce the noise by adaptive noise cancellation, (3) reject the interference by blanking algorithm, (4) pulse integration in the frequency domain to increase the SNR, and (5) increasing the detection speed by new pulse integration technique. By interference rejection and noise cancellation, the SNIR is improved to 9.24 dB at 1 MHz and to 7.28 dB at 3.4 MHz, and by pulse integration 44.8 dB FID signal amplification is achieved, and the FID signals are detected at 1.057 MHz and 3.402 MHz at room temperature.

Development of a single LMS loop three channels analog adaptive co-site interference cancelling system

Co-site interference is becoming prominent on some independent platforms (e.g., airplanes, satellites, space stations, and vessels). Although many digital multichannel cancellation algorithms have been investigated, the saturation problem of the receiver front-end caused by severe co-site interference should be addressed first with analog RF cancellation. Many studies are currently being conducted to develop an analog adaptive co-site interference cancellation system (AACICS). However, double LMS (Least Mean Square) loop in every channel raises the complexity and implemented difficulty. Above all, the interference cancellation in the scene of antenna swaying has received little attention, which severely limits the effective suppression of wideband interference. This study developed an analog 3-channel adaptive co-site wideband interference cancellation system (AACWICS-3ch) with one LMS loop in every channel and established the equivalent model of the AACWICS-3ch. The steady-state weight and interference cancellation ratio (ICR) were obtained by analyzing and solving the equivalent model. An in-depth analysis was conducted on the quantitative relationship correlations between the interference cancellation bandwidth, ICR, system gain, and antenna swing amplitude. Results reveal that AACWICS-3ch can greatly enhance the interference cancellation performance compared to 2-channel analog adaptive co-site interference cancellation system (AACICS-2ch). The maximum improved ICR is greater than 30 dB, and it overcomes the complexity of double LMS loop cancellation system with the increasing of channel. Finally, simulations and experiments validated the improvement of interference cancellation performance in AACWICS-3ch.

High-Bit-Rate Transmission in Visible Light Communication System Based on Adaptive Successive Interference Cancellation Technique

High-Bit-Rate Transmission in Visible Light Communication System Based on Adaptive Successive Interference Cancellation Technique

Simultaneous Transmit and Receive Phased Array System Architecture and Prototype Comprehensive Verification

In the future multi-functional detection sensing and communication integrated systems, as well as 5G/6G systems, simultaneous transmit and receive technology, as an important key technology, is an important supporting measure to achieve the simultaneous work of different functions. Looking at the problem of strong self-interference in the simultaneous multi-function application of a phased array transceiver, this paper presents the integrated cancellation architecture and corresponding method of integrated transmission domain, RF domain and digital domain, and completes principle experiment verification of interference suppression and elimination by constructing the principle experiment system. Experimental results show that in the actual hardware system 0.5 db amplitude quantification and 6-bit phase quantization control conditions, through joint using passive and active beam transfer of the domain space optimization form, at the same time in the digital domain application of the adaptive system identification interference cancellation method for further interference cancellation, above 150 dB for interference suppression can be achieved. This research will provide a certain reference for the application of simultaneous transceiver technology in future 5G/6G phased array antenna systems.

A novel adaptive noise canceling system for urea NQR spectrum analysis

Due to its practical ease of use and sufficiently high reliability, Nuclear Quadrupole Resonance (NQR) has largely been used in remote sensing-based detection of quadrupole nuclei, especially Nitrogen-containing materials. Since the received signal of free induction decay (FID) is inherently weak in this technique, the noise and the interference of the environment would dramatically impair the performance of the detecting systems. To handle such challenges, an adaptive noise canceling method was employed to improve the signal to noise and interference ratio (SNIR) in FID signals. FID signals, noise, and interference were received by the main antenna, while similar noise and interference would be received by the auxiliary antenna. The proposed system significantly reduced noise and interference through the digital noise and interference cancellation algorithm, pulse integration, averaging, and singular spectrum analysis (SSA). Urea powder was empirically analyzed outdoors, suggesting that the proposed adaptive noise and interference cancellation (ANIC) system, effectively suppressed noise and interference by 41.13 dB and amplified the FID signal by 53.36 dB. The strongest signal was detected at 2870.4 kHz.

On the outage performance of multi-user NOMA system with adaptive SIC

The performance of non-orthogonal multiple-access (NOMA) is significantly determined by the successive interference cancellation (SIC) technique. However, the interference redundancy can happen during the NOMA receiver performing SIC. To tackle this issue, this paper proposes a novel adaptive successive interference cancellation (ASIC) method. Specifically, the decoding error is considered as interference during the SIC process, and an adaptive filter with various weights is introduced for detection error mitigation. For the multi-user downlink NOMA system, the outage probability is analyzed under conventional and the proposed SIC methods. Simulation results verify our analysis, which also demonstrate the superiority of the proposed ASIC method.

Adaptive Blind MPSK Constellation Recovery and Equalization for Cognitive Radio Applications

Cognitive radio is considered a relevant communication paradigm to deal with the increasing demands in modern communications systems. Adaptive schemes are required to recognize channel conditions and to properly adjust main transmission parameters to improve the quality of communications. In this direction, blind algorithms to recover constellation, from phase-modulated signals, represent a means to implement cognitive capabilities to allow automatic modulation recognition (AMR) on receivers. Commonly, the most popular approaches for blind constellation recovery are based on a two-step scheme. The first step uses to equalize channel effects and reduce inter-symbol interference (ISI). The second step carries out constellation recovery utilizing phase locked loop (PLL) systems like the Costas Loop, then to classify the incoming signal. This work proposes a novel single-step blind adaptive filter solution, inspired by an adaptive interference canceler, for joint equalization and constellation symbol recovery from received phase shift keying (PSK) waveforms. Furthermore, we propose new coefficients update mechanisms based on the constant amplitude of PSK signals. The proposed solution exhibits reduced computational complexity compared to the state of the art and a reduced time of convergence. Additionally, the proposed scheme does not require a training sequence to operate properly. The obtained results clearly show that the proposed scheme significantly improves accuracy regarding phase symbol estimation and ISI reduction.

A new adaptive co-site broadband interference cancellation method with auxiliary channel

With the boom of the communication systems on some independent platforms (such as satellites, space stations, airplanes, and vessels), co-site interference is becoming prominent. The adaptive interference cancellation method has been adopted to solve the co-site interference problem. But the broadband interference cancellation performance of traditional Adaptive Co-site Interference Cancellation System (ACICS) with large delay mismatching and antenna sway is relatively poor. This study put forward an Adaptive Co-site Broadband Interference Cancellation System With Two Auxiliary Channels (ACBICS-2A). The system model was established, and the steady state weights and Interference Cancellation Ratio (ICR) were deduced by solving a time-varying differential equation. The relationship of ICR, system gain, modulation factor, interference signal bandwidth and delay mismatching degree was acquired through an in-depth analysis. Compared with traditional adaptive interference cancellation system, the proposed ACBICS-2A can improve broadband interference cancellation ability remarkably with large delay mismatching and antenna sway for the effect of auxiliary channel. The maximum improved ICR is more than 25 ​dB. Finally, the theoretical and simulation results were verified by experiments.

Multichannel Adaptive Interference Cancellation for Full-Duplex High Power AM Radios

In space-limited co-located communication systems, wideband transmitters and receivers are deployed for various applications. The strong coupling between transmitters and receivers becomes a major concern. It is crucial to suppress the high power self-interference (SI) to prevent the receiver from working in the nonlinear area, or even saturating. As an effective approach to achieve this, the adaptive interference cancellation (AIC) technology is proposed in the context of a complex high power amplitude modulation radios. In this article, the system-level performance including the interference cancellation ratio requirements and the impact of the AIC on the receiving system is comprehensively studied for the first time. The operating mechanism of a single channel AIC system (AICS) and the configuration of a multichannel AICS are discussed. The performance analysis of the receiving system when implementing the AICS is performed, in terms of the noise figure and the sensitivity. By employing the proposed AICS, very limited effect is observed on the receivers, while the SI is successfully reduced with a high ICR, which fully satisfies the requirements for AM systems. The realization of the multichannel AICS as well as the measured cancellation performance are presented, verifying the proposed concept.

Cellular-Connected UAV With Adaptive Air-to-Ground Interference Cancellation and Trajectory Optimization

This letter studies a cellular-connected unmanned aerial vehicle (UAV) scenario, in which a UAV user communicates with ground base stations (GBSs) in cellular uplink by sharing the spectrum with ground users (GUs). To deal with the severe air-to-ground (A2G) co-channel interference, we consider an adaptive interference cancellation (IC) approach, in which each GBS can decode the GU’s messages by adaptively switching between the modes of IC (i.e., precanceling the UAV’s resultant interference) and treating interference as noise (TIN). By designing the GBSs’ decoding mode, jointly with the wireless resource allocation and the UAV’s trajectory control, we maximize the UAV’s data-rate throughput over a finite mission period, while ensuring the minimum data-rate requirements at individual GUs. We propose an efficient algorithm to solve the throughput maximization problem by using the techniques of alternating optimization and successive convex approximation (SCA). Numerical results show that our proposed design significantly improves the UAV’s throughput as compared to the benchmark schemes without the adaptive IC and/or trajectory optimization.

Frequency-Based Maternal Electrocardiogram Attenuation for Fetal Electrocardiogram Analysis

Fetal electrocardiogram (ECG) waveform analysis along with cardiac time intervals (CTIs) measurements are critical for the management of high-risk pregnancies. Currently, there is no system that can consistently and accurately measure fetal ECG. In this work, we present a new automatic approach to attenuate the maternal ECG in the frequency domain and enhance it with measurable CTIs. First, the coherent components between the maternal ECG and abdominal ECG were identified and subtracted from the latter in the frequency domain. The residual was then converted into the time domain using the inverse Fourier transform to yield the fetal ECG. This process was improved by averaging multiple beats. Two fetal cardiologists, blinded to the method, assessed the quality of fetal ECG based on a grading system and measured the CTIs. We evaluated the fetal ECG quality of our method and time-based methods using one synthetic dataset, one human dataset available in the public domain, and 37 clinical datasets. Among the 37 datasets analyzed, the mean average (± standard deviation) grade was 3.49 ± 1.22 for our method vs. 2.64 ± 1.26 for adaptive interference cancellation (p-value < 0.001), thus showing the frequency-based fetal ECG extraction was the superior method, as assessed from our clinicians’ perspectives. This method has the potential for use in clinical settings.

Adaptive Beamforming With Software-Defined-Radio Arrays

Digital beamforming is the holy grail of antenna array technologies, however implementing digital beamforming into practical antenna arrays has been slow due to hardware complexity and cost. We propose a relatively inexpensive new approach to digital beamforming using software defined radios. Using this system, we carried out experiments on adaptive interference cancellation. We present detailed description of the beamformer system along with the developed control software and experimentally verify the beamformer performance. Our results show that in high-interference and high-multipath environments, where carrier frequency offsets cannot be measured, conventional interference cancellation algorithms fail. We propose two new robust solutions to this problem and compare the results with multiple techniques, including the minimum variance distortionless response beamformer, which outputs the highest possible signal-to-interference-plus-noise-ratio (SINR). We experimentally demonstrate that both our approaches work well in the face of these types of signal corruptions and are capable of interference cancellation without degrading SINR or other system performance factors, and without the need for transmitter and receiver synchronization.

Broadband cancellation method in an adaptive co-site interference cancellation system

With the boom of communication systems on independent platforms (such as, airplanes and vessels), co-site interference has become prominent. Currently, extensive research has been conducted on the development of an adaptive co-site interference cancellation system (ACICS); however, the related interference cancellation bandwidth characteristics have not been adequately investigated, thereby critically restricting the further optimisation of the ACICS design. In this study, the bandwidth signal calculation formula of the ACICS interference cancellation ratio is derived, and the quantitative relationships among the interference cancellation bandwidth, interference cancellation ratio, system gain, and delay-matching degree are analysed exhaustively. The results reveal that the higher the required interference cancellation ratio, the smaller is the interference cancellation bandwidth; the interference cancellation bandwidth can be enhanced to a limited degree by increasing the system gain. Furthermore, the interference cancellation bandwidth and the delay-matching distance follow an approximately inverse relation, and the interference cancellation bandwidth can be improved by delay matching. The nearest matching method can be employed for broadband interference. Finally, the conducted simulations and experiments validate the correctness and effectiveness of the theoretical analysis.

A criterion based adaptive RSIC scheme in underwater communication

Multi-access interference (MAI) is the main source limiting the capacity and quality of the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Therefore, multi-user detection (MUD) is needed at the receiver of the MIMO-OFDM system to suppress the effect of MAI. In this research, MUD is achieved by using a criterion based adaptive recursive successive interference cancellation (RSIC) scheme at the receiver of a MIMO-OFDM system whose transceiver model in underwater communication is implemented by using the Bellhop simulation system. The proposed scheme estimates and eliminates the MAI through user signal detection and subtraction from received signals at the receiver of the MIMO-OFDM system in underwater environment. The bit error rate (BER) performance of the proposed scheme is analyzed by using weight filtering and weight selection criteria. By Matlab simulation, it is shown that the BER performance of the proposed scheme outperforms the conventional matched filter(MF) detector, the adaptive successive interference cancellation(SIC) scheme, and the adaptive RSIC scheme in the UWA network.

Nonorthogonal Multiple Access With Energy Harvesting-Based Alternate Relaying

For a downlink communication system, we propose a nonorthogonal multiple access scheme with two energy harvesting relays. The base station (BS) transmits the data of both near and far users simultaneously using the superposition coding technique. Two relays alternately amplify and forward the data to the far-user. Each relay can harvest wireless energy from the signals of both the BS and the other transmitting relay, so each relay can achieve more opportunities to accumulate more energy for a higher-quality cooperative relaying. The near-user performs adaptive interference cancelation to retrieve its desired data. Numerical results show that the nonorthogonal scheme greatly outperforms the orthogonal scheme in terms of throughput.

Adaptive Interference Cancellation Using Atomic Norm Minimization and Denoising

The rapid increase in the number of wireless devices in modern communication networks has significantly increased the number of interference sources, which severely impacts communication reliability. Adaptive interference cancellation is rapidly becoming a necessity for modern wireless networks. For interference cancellation, a digital beamformer adaptively adjusts its weight vector using an array processing algorithm. This, in turn, shapes the radiation pattern in a manner that minimizes interference power and maximizes the desired signal power. In this letter, we propose two atomic-norm-minimization-based methods to design a weight vector that can be used to cancel interference. We present numerical and experimental studies and compare with the minimum variance distortionless response beamformer, which outputs the highest possible signal-to-interference-plus-noise ratio (SINR). We show that our approach is robust to signal corruptions arising from carrier frequency offsets. Uniquely, our algorithm extracts the offset frequencies, thus enabling interference cancellation with maximum SINR.