Interference Cancellation Research Articles

Differential Modulation-Aided Practical Backscatter Communications: Interference Cancellation Strategy Design and Implementation

Differential Modulation-Aided Practical Backscatter Communications: Interference Cancellation Strategy Design and Implementation

Photonic Interference Cancellation for LiDAR Sensors

Photonic Interference Cancellation for LiDAR Sensors

A V2I and V2V Collaboration Framework to Support Emergency Communications in ABS-Aided Internet of Vehicles

Providing reliable and flexible emergency communications for the Internet of Vehicles (IoV) is challenging in post-disaster scenarios, especially when communications infrastructures are unavailable or seriously damaged. Under such circumstances, it is highly demanded to deploy the air base station (ABS) to restore connectivity in disaster areas. Although the ABS can offer improved performance, the massive access of communications devices and the rising demand for many emergency-related services will bring new challenges to the ABS-aided IoV. In this paper, we propose a vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) collaboration framework to support emergency communications. Specifically, we incorporate non-orthogonal multiple access (NOMA) into the ABS-aided IoV. By using the successive interference cancellation (SIC) technique, V2I and V2V links can operate in four spectrum reuse modes, which are the extension of the conventional underlaying reuse mode. To fully exploit the advantages of the NOMA enhanced collaboration framework, we formulate a total power consumption minimization problem by jointly considering the mode selection, power control, and the channel state information (CSI) latency. The formulated problem is constrained by the reliability and rate requirements, and the decoding threshold of the SIC technique. Due to the NP-hard characteristics of the formulated problem, we decouple it first, and then adopt the graphical method to derive the analytical solution of optimal power control policies. Afterwards, we can get every feasible spectrum reuse mode. Among the feasible modes, we select the mode with minimum power consumption as the optimal mode. Finally, simulation results demonstrate that our proposed algorithm outperforms the current works in term of the total power consumption, e.g., by adopting the ABS and the NOMA technology, the total power consumption can be reduced by 22.3% and 40.9%, respectively.

Impact of Power Consumption Models on the Energy Efficiency of Downlink NOMA Systems

While non-orthogonal multiple access (NOMA) improves spectral efficiency, it adds complexity to the receivers due to successive interference cancellation (SIC). Prior studies on the energy efficiency of NOMA overlook the SIC overhead and rely on simplistic power consumption models (PCM). To fill this gap, we first introduce PCM-κ that accounts for SIC-related power expenditure. Then, to investigate the energy efficiency of NOMA and joint transmission (JT)-coordinated multipoint (CoMP) NOMA, we formulate a power allocation problem for maximizing the energy efficiency and propose a global approach running at a centralized entity and a local algorithm running at a base station. We evaluate the energy efficiency using PCM-κ and two PCMs commonly used in the literature. Numerical analysis suggests that using simplistic PCMs leads to a few orders of magnitude overestimation of energy efficiency, especially when the receivers have low rate requirements. Despite the superiority of JT-CoMP NOMA over conventional NOMA in finding a feasible power allocation, the difference in their energy efficiency is only marginal when users have identical rate requirements and more significant in more heterogeneous settings with users having different rate requirements. Moreover, when conventional NOMA is feasible, the optimal solution for JT-CoMP NOMA converges to conventional NOMA.

An Uplink Cooperative NOMA Based on CDRT With Hardware Impairments and Imperfect CSI

Hardware impairments in wireless transceivers can cause severe performance degradation, particularly for high-rate communication networks. Few studies have explored the impact of these frameworks on recent wireless networks, such as uplink nonorthogonal multiple access (NOMA) with imperfect channel estimation. In this article, we investigate the effect of two practical and malignant imperfections on the performance of coordinated direct and relay transmission (CDRT) using uplink NOMA. Based on these imperfections, we derive an exact closed-form expression for the ergodic sum capacity and outage probability of an uplink NOMA CDRT network. Our model accounts for all the hardware distortions caused by nonideal transceiver nodes as well as residual interference from imperfect channel estimates and imperfect successive interference cancellations. Furthermore, in order to establish a benchmark, we provide analytical expressions and numerical results that demonstrate the superiority of the CDRT-assisted uplink NOMA system with respect to an orthogonal multiple access system. To verify the accuracy of the derived analytical expressions, Monte Carlo simulations are performed.

Successive Interference Analysis for 5G System at Mid-Band and High-Band Frequency

This research study focuses on the impact of interference on different 5G system parameters such as modulation techniques (64-QAM, 256-QAM), channel models (AWGN, Rayleigh, and Rician), and MIMO (multiple input, multiple output) in terms of Bit Error Rate (BER). After the analysis of interference for each parameter, an analysis of interference by Short Range Devices (SRDs) on the 5G system network on the downlink channel is done. Finally, successive interference cancellation (SIC) for a 5G Non-Orthogonal Multiple Access (NOMA) system with Power Division Multiplexing (PDM) is applied. A 5G NOMA has higher spectral efficiency as compared to an Orthogonal Frequency Division Multiple Access (OFDMA), so it can fulfil the needs of the Internet of Things (IoT). SIC is implemented using PDM, where each user is assigned a certain power factor and generates a signal, the generated signal is superimposed and the New-Radio (NR) transmitter that transmits the superimposed signal. Finally, the signal is detected with and without SIC on the access side with SRDs as an interferer. After simulation and analysis of different 5G system parameters, it is found that the BER is decreased with an increase in the MIMO and is more applicable to the higher order modulation. With the SIC, the BER for the NOMA users decreased as compared to OFDMA users. The power coefficients for the stronger signal user (user 1) and weaker signal user (user 2) are 0.25 and 0.75 respectively.

Wavelet-Adaptive Interference Cancellation for Underdetermined Platforms: Enhancing Boomless Magnetic Field Measurements on Compact Spacecraft

Wavelet-Adaptive Interference Cancellation for Underdetermined Platforms: Enhancing Boomless Magnetic Field Measurements on Compact Spacecraft

Side Null Analysis of the Main-Auxiliary Antenna Array for Noncooperative Interference Cancellation

In interference cancellation, the null at the angle of arrival (AoA) of interference can suppress interference. However, due to the large spacing between array elements and the periodicity of the array, some small nulls at the angles of noninterference are formed inevitably. When the AoA of the desired signal is in these small nulls, they impair the effectiveness of interference cancellation by attenuating the desired signal. This paper proposes the concept of a side null to represent these nulls in the noninterference direction. And the cancellation ratio of the desired signal (SCR) is deduced to quantitatively characterize the side null. The spatial noncooperative interference cancellation model based on the main-auxiliary antenna array is established. Based on this, the SCR is derived to evaluate the amount of desired signal attenuation. Then the simulation, respectively, in two-dimensional plane and three-dimensional space, describes the side null visually. Moreover, the method of side null reduction is discussed by modulation of the array. Finally, the existence of side null and its influence on interference cancellation are verified through the experiments. The results of the simulation and experiment are in good agreement, and both support the theoretical analysis.

Recurrent neural networks for enhanced joint channel estimation and interference cancellation in FBMC and OFDM systems: unveiling the potential for 5G networks

FBMC is a pivotal system in 5G, serving as a cornerstone for efficient use of available bandwidth while simultaneously meeting stringent requirements for high spectral efficiency. Notably, FBMC harnesses the power of multicarrier modulation (MC), a good alternative to orthogonal frequency division multiplexing (OFDM) technology that supports fourth-generation (4G) systems. The wireless communications field is full of challenges, the most important of which are channel estimation and interference cancellation, both of which deserve comprehensive study to increase the efficiency of data transmission. In this paper, our investigation takes a deliberate step towards the convergence of two prominent modulation models: OFDM and FBMC. We specifically contrast these modulation techniques with the intricate field of joint channel estimation and interference cancellation (JCEIC). In this research study, we take advantage of recurrent neural networks' (RNNs') efficiency as a vehicular channel to perform precise channel estimation and recovery of uncorrupted transmitted signals, thereby lowering the bit error rate (BER). Our channel estimation for a dual selective channel is based on the thoughtful placement of pilots scattered over the temporal and frequency dimensions, and is further improved by the interference cancellation method of low complexity that was selected. Our JCEIC proposal aims to integrate RNNs carefully, using the output sequences of JCEIC algorithms as useful inputs to this neural architecture. By clearly demonstrating a decrease in BER as compared to traditional approaches, it is evident that the performance of the novel approach is near to that of a perfect channel. Additionally, a comparison of the performance of FBMC and OFDM systems at various signal-to-noise ratios reveals a clear performance divide that favors the former in terms of system efficiency. The BER is restricted by FBMC to a commendable threshold of less than 0.1 at a modest 5 dB, continuing the higher trend started by its improved RNN-based channel estimate. The accuracy of channel estimation is clearly improved by this paradigm shift, and the computing complexity typical of 5G networks is also clearly reduced.

Morphology engineering of heterogeneous carbon particles toward boosted dielectric polarization for ultrathin and strong loss absorber

Micron-carbon particles with polymorphous concave polyhedron have been easily prepared via high-efficiency spray drying-carbonization process, which is aimed at boosting dielectric polarization toward the feature of high the real part of the complex permittivity accompanied with low level dielectric loss for achieving ultrathin absorber. In addition, the effect of geometry on the microstructure and microwave absorption (MA) performances was systematically studied for the first time. A minimum reflection loss (RLmin) of −55.07 dB under ultrathin thickness of 1.23 mm and a broad effective absorption bandwidth (<-10 dB) of 4.0 GHz at 1.3 mm were obtained for composites filled with polymorphous concave polyhedral carbon particles, meanwhile the loading contents have been reduced from 30 wt% spherical filler to 22.5 wt% polymorphous concave polyhedral filler. Optimized MA performance with strong loss and ultrathin thickness has been identified as attenuation mechanism dominated by interference cancellation and assisted by dielectric loss for the first time. This work not only provides an insight to realize engineering applications of carbonaceous absorbents but also reveals the intrinsic attenuation mechanism of microwave absorbing materials.

On the performance of intelligent reflecting surfaces-assisted OAM with NOMA under imperfect SIC

In this paper, intelligent reflecting surface (IRS)-assisted orbital angular momentum (OAM) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI) is proposed. Importantly, the communication links of both cell-center user (CCU) and cell-edge user (CEU) are developed through IRS when they are in the non-line-of-sight (NLoS) of the transmitter. The aim of developing the proposed system is the accommodation of massive connectivity and enhancement of sum capacity as well as user capacities with the help of NOMA. The performance of the proposed IRS-OAM-NOMA system is evaluated and compared with the existing techniques such as IRS-assisted OAM with orthogonal multiple access (OMA) OMA-OAM-IRS and NOMA-IRS. The simulation results show that the proposed IRS-OAM-NOMA system outperforms the existing techniques in terms of user capacity and sum capacity under ideal conditions and with imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI).

MREDNet: A Multi-Residual Encoder-Decoder Network for recovering LFM interfered by intra-pulse retransmission interferences

Retransmission interference in radar and communication signal processing significantly threatens the received linear frequency modulation signal. With the advancement in the hardware capabilities of interference devices, they can intercept and retransmit signals within the duration of a single pulse. Therefore, we refer to this type of interference as intra-pulse retransmission interference, which includes retransmission modes smeared spectrum, interrupted sampling repeater jamming, and interrupted nonuniform sampling repeater jamming. Although traditional interference cancellation techniques offer optimal solutions under the assumption of fully known interference parameters, practical scenarios often involve unknown parameters, estimation errors, random parameters, and multiple interferences, leading to performance degradation. To address these problems, we propose a Multi-Residual Encoder-Decoder Network (MRDENet), a novel approach for effectively mitigating intra-pulse retransmission interferences and recovering the signal of linear frequency modulation. In contrast to parameter estimation and interference cancellation, MREDNet extracts crucial features of both the target and interference and performs reconstruction. More specifically, MREDNet acquires information about the retransmission pattern of interference and the modulation frequency through its multi-level residual shortcut connections. To address the issue of network parameters being real while the signals are complex, we devised decomplexification—a data preprocessing approach enabling neural networks for direct utilization in front-end complex signal processing. Besides, we evaluate the performance of MREDNet comprehensively. The experimental conditions encompassed single and multiple interferences, incomplete data sets, varying signal-to-noise ratios, and jamming-to-signal ratios. The computational simulations demonstrate that MREDNet successfully solves the problem of recovering linear frequency modulation signals interfered with by intra-pulse retransmission interference. According to the boundary condition of MREDNet, the proposed method exhibits valuable applications in real-world scenarios.

Deep-Neural-Network-Based Receiver Design for Downlink Non-Orthogonal Multiple-Access Underwater Acoustic Communication

The excavation of the ocean has led to the submersion of numerous autonomous vehicles and sensors. Hence, there is a growing need for multi-user underwater acoustic communication. On the other hand, due to the limited bandwidth of the underwater acoustic channel, downlink non-orthogonal multiple access (NOMA) is one of the fundamental pieces of technology for solving the problem of limited bandwidth, and it is expected to be beneficial for many modern wireless underwater acoustic applications. NOMA downlink underwater acoustic communication (UWA) is accomplished by broadcasting data symbols from a source station to several users, which uses superimposed coding with variable power levels to enable detection through successive interference cancellation (SIC) receivers. Nevertheless, comprehensive information of the channel condition and channel state information (CSI) are both essential for SIC receivers, but they can be difficult to obtain, particularly in an underwater environment. To address this critical issue, this research proposes downlink underwater acoustic communication using a deep neural network utilizing a 1D convolution neural network (CNN). Two cases are considered for the proposed system in the first case: in the first case, two users with different power levels and distances from the transmitter employ BPSK and QPSK modulations to support multi-user communication, while, in the second case, three users employ BPSK modulation. Users far from the base station receive the most power. The base station uses superimposed coding. The BELLHOP ray-tracing algorithm is utilized to generate the training dataset with user depth and range modifications. For training the model, a composite signal passes through the samples of the UWA channel and is fed to the model along with labels. The DNN receiver learns the characteristic of the UWA channel and does not depend on CSI. The testing CIR is used to evaluate the trained model. The results are compared to the traditional SIC receiver. The DNN-based DL NOMA underwater acoustic receiver outperformed the SIC receiver in terms of BER in simulation results for all the modulation orders.

Interference Cancellation and Wavelet Denoising for Magnetometers in Electric Work-Class ROVs

Interference Cancellation and Wavelet Denoising for Magnetometers in Electric Work-Class ROVs

Joint Waveform Design and Detection in Symbiotic Ambient Backscatter NOMA Systems

Non-orthogonal multiple access (NOMA) and symbiotic ambient backscatter communications (AmBC) are both considered promising technologies for beyond 5G mobile communication technology by enabling low-powered and spectrum-efficient access in large-scale Internet of Things. In this paper, we investigate the uplink symbiotic communication in AmBC enabled NOMA system. In contrast with existing works, we assume the carrier transmitter (CT) transmits information while providing energy to the backscatter devices (BDs), which improves the energy efficiency. However, the signal power transmitted by the CT to integrated receiver (IR) through the direct link is much larger than the signal reflected by the BD, which can seriously affect the detection of the reflected signal by BD. Therefore, we jointly design the signal waveforms of CT and BDs, and propose a multi-user blind detection algorithm based on interference cancellation at IR. The simulation results demonstrate that the proposed multi-user detection algorithm achieves improved performance even the active BD number is unknown or without direct link.

Regulation of microwave absorbing performance of magnetic alloy/ferrite/carbon ternary composites by changing polydopamine-induced carbothermal reduction

Magnetic alloy/ferrite/nitrogen-doped carbon composites (CoFe/CoFe2O4/N–C) spheres were synthesized by controlled carbothermal reduction of Co-doped Fe2O3 nanospheres wrapped in polydopamine. Different dopamine hydrochloride dosages not only affected components and nanostructures, but also regulated the electromagnetic properties of CoFe/CoFe2O4/N–C composites. The results show that with the increase of dopamine hydrochloride dosage, graphitic degree of N-doped carbon layer would decrease after an initial increase, while the Ms values exhibit an opposite trend. All samples show similar μr spectra, and negative μ″ values can be obtained at high frequency, which should be related to eddy current and dielectric resonance. With the increment of polydopamine, εr would first increase due to generation of CoFe and the increase in graphitic degree, and then decrease owing to the agglomeration of spherical particles. Further research on microwave absorption shows that RL peak frequency coincides with the frequency of perfect impedance matching when good impedance matching has been achieved across a wide range of frequencies. Thanks to the synergistic effects of conduction loss, interfacial polarization, dipole polarization, natural resonance, eddy current, and complete interference cancellation, S-100 has a wide effective absorption bandwidth of 4.88 GHz at 2.0 mm and a low RL peak value of −70.48 dB at 1.95 mm. This work could offer new insights into multi-component magnetic MAMs design and illuminate the relationships between reflection loss, impedance matching, interference cancellation, phase composition, and composite structure.

QoS-based resource allocation for uplink NOMA networks

Nowadays, several next-generation multiple access technologies are proposed, and non-orthogonal multiple access (NOMA) is one of the candidates. In NOMA systems, since the utilization of successive interference cancellation (SIC), the SIC order is one of the significant factors to be considered. In the literature, the SIC order is usually determined by the channel gains, which is not stable especially when the users are with similar channels. In this paper, we creatively propose the quality-of-service-based SIC order in the uplink NOMA system, and focus on the resource allocation to maximize the rate. Specifically, we first optimize the powers with given user grouping and provide solutions for different cases of channel gains. Furthermore, the Hungarian algorithm is jointly exploited with the optimized powers. Simulation results show that the proposed algorithm outperforms traditional orthogonal multiple access and even achieves similar rate with the exhaustive search.

User pairing impact on the performance of hybrid beamforming NOMA system

This paper proposes a new user pairing technique for a power domain nonorthogonal multiple access (NOMA) deploying fully connected and subconnected hybrid beamforming (HBF) structures for a typical urban microcell downlink of line-of-sight (LOS) and non-line-of-sight (NLOS) surroundings. NOMA system’s configurations are set up for two (multiple input single output) users per cluster down- linking base station equipped with 128 antennas. HBF processing adopts phased zero forcing (P-ZF) for both fully connected (HBFNOMA) structure (FCS) and sub-connected (HBF-NOMA) structure (SCS) precoders’ optimization, and successive interference cancellation zero forcing (SIC-ZF) schemes to optimize the SCS-HBF-NOMA precoder exploiting dynamic power allocation. The new users’ pairing exploits users’ distance to the base station, namely near and far clusters different from the benchmark angle of arrival- based users’ pairing. The proposed users’ pairing and the precoding schemes’ impact are investigated for finite-resolution HBF structures operating in LOS and NLOS surroundings. The execution under New York University (NYU) mmW channel model is explored for two users in a cluster with different angles of arrival. Results show that the users’ pairing based on AoA performs better than the newly proposed users’ pairing. However, the proposed users’ pairing scheme performs better than their corresponding OMA counterparts, which still make them beneficial for multiple access technique and a scenario, where one of the far cluster users need to access the base station for high data rate service and vice versa. Finally, the modified Liang processing scheme for quantizing SCS-HBF-NOMA precoder is capable of mitigating the quantization error arising from the NLOS environment and the nature of sub-connected (HBF) structure under a low SNR regime.

A Novel Compute-and-Forward Relaying Method for Multi-Antenna Wireless Relay Networks.

Compute-and-Forward (CoF) is an innovative physical layer network coding strategy, designed to enable receivers in wireless communications to effectively utilize interference. The key idea of CoF is to implement integer combinations based on the codewords from multiple transmitters, rather than decoding individual source codewords. Although CoF is widely used in wireless relay networks, there are still some problems to be solved, such as rank failure, single antenna reception, and the shortest vector problem. In this paper, we introduce a successive extended CoF (SECoF) as a pioneering solution tailored for multi-source, multi-relay, and multi-antenna wireless relay networks. First, we analyze the traditional CoF, and design a SECoF method combining the concepts of matrix projection and successive interference cancellation, which overcomes the problem of CoF rate tending to zero and rank failure and improves the network performance. Secondly, we obtain an approximate solution to the integer-value coefficient vectors by using the LLL lattice-based resolution algorithm. In addition, we deduce the corresponding concise formulas of SECoF. Simulation results show that the SECoF has strong robustness and the approaches outperform the state-of-the-art methods in terms of computation rate, rank failure probability, and outage probability.

Nonlinear symbolic regression for bit error rate prediction of NOMA systems in 5G cellular communications

Machine learning (ML) has been suggested as a promising tool in the design of telecommunication systems to overcome the challenges of traditional methods and meet the requirements regarding future cellular networks. As an enabler of 5G communications, Non-orthogonal multiple access (NOMA) has emerged to adaptively manage the existing resources and received huge attention in terms of performance analysis to confirm its efficiency in resource management. This work addresses the applications of nonlinear symbolic regression (NLSR) techniques to evolve mapping models for bit error rate (BER) prediction in the downlink NOMA systems with perfect and imperfect successive interference cancellation (SIC) receivers. In this regard, a multi-stage structure is proposed to evaluate the BER using the related inputs as well as the output of the previous stages for imperfect SIC signal decoding. Each step consists of an NLSR block with different inputs and an output, which inputs include the effective parameters and the output of the previous stages. Experimental results confirm that the NLSR techniques are able to establish modeling expressions with good prediction accuracy compared to other benchmark methods. In particular, these ML-based techniques overcome the limitation of the classical approaches in modeling a closed-form BER formula, especially for the NOMA systems with more than two users. In addition, this BER prediction tool can be utilized by the NOMA base station as new side information for more optimal resource management.