Interference Cancellation Research Articles

Anti-jamming and Power Minimization Interference Nulling in Uplink MIMO-NOMA Technique

Non-orthogonal Multiple Access (NOMA) provides use of the power domain to boost system efficiency in the spectrum. This letter explores the use of a new transceiver design and non-orthogonal multiple access (NOMA) for MIMO uplinks. The overall energy use can be reduced while still meeting individual rate requirements by utilizing a new NOMA implementation scheme with group interference cancellation. Jamming attacks can target NOMA communication. MIMO technology is used to implement anti-jamming regulations in NOMA systems. While subsequent interference cancellation utilized to get rid of between groups interference, interference nulling at the transmitters and equalizers at the jointly designed receivers for improved power system efficiency. Where the transmitter is side, interference nulling techniques have been developed. By using the above technique, the total power consumption (dBm) which it required which it is less when compare to traditional technique like orthogonal multiple access (OMA). The outcomes of the simulation show that, in comparison to both signal alignment NOMA and orthogonal multiple-use communication, the proposed NOMA scheme typically requires less power.

Decision Feedback Equalization-Based Low-Complexity Interference Cancellation and Signal Detection Technique Based for Non-Orthogonal Signaling

FTN signalling is an effective communication method that achieves a high spectral efficiency. However, employing a symbol rate faster than the Nyquist rate disrupts the orthogonality between symbols, leading to unavoidable inter-symbol interference (ISI). To mitigate the effects of ISI, interference cancellation and signal detection processes are essential for FTN receivers. Conventional ISI reduction techniques often utilize trellis-based algorithms. However, as the number of states increases due to additional interference symbols, the complexity of these algorithms grows exponentially. To address this challenge, this paper explores a matrix computation-based interference cancellation technique tailored for FTN communication systems, aiming to significantly reduce the complexity of the ISI mitigation process. To execute ISI cancellation and signal detection more precisely, the proposed technique includes iterative interference cancellation and a signal detection process. When six interference symbols are considered, the complexity of the proposed technique is reduced by 97% compared with that of the conventional Viterbi algorithm. Furthermore, in the case of τ = 0.85, the performance of the proposed technique is about 1 dB better than that of the Viterbi algorithm at BER = 10−4.

Optimizing System Performance with Adaptive Algorithms for Signal Processing in Wireless Communication Networks

In modern wireless communication networks, the need for high-speed, reliable, and efficient data transmission is paramount. Signal processing algorithms play a critical role in optimizing network performance, especially under dynamic conditions such as varying network loads and environmental interference. This paper presents an in-depth study of adaptive signal processing algorithms designed to improve the performance of wireless communication systems. We examine various techniques, including adaptive filtering, channel estimation, and interference cancellation, and assess their effectiveness in optimizing signal quality and network throughput. Through simulation and real-world case studies, the paper demonstrates how these algorithms can be applied to mitigate signal distortion and reduce data transmission errors in wireless networks. The results show that adaptive algorithms significantly enhance the overall system performance, particularly in environments with fluctuating signal conditions. The paper concludes with recommendations for further development in adaptive algorithms for future wireless communication standards, particularly 5G and beyond.

Enabling grant-free multiple access through Successive Interference Cancellation

Internet of Things (IoT) is stirring a surge of interest in effective methods for sharing communication channels, with nodes transmitting sporadic, short messages. These messages are often related to control systems that collect sensor data to drive process actuation, such as in industries, autonomous vehicles, and environmental control. Traditional approaches that dominate wireless and cellular communications prove most effective when dealing with a limited number of concurrently active nodes, sending relatively large volumes of data. We address a different scenario where numerous nodes generate and transmit short messages according to non-periodic schedules. In such cases, random multiple access becomes the typical approach for sharing the communication channel. We propose a general modeling framework that enables the investigation of the impact of Successive Interference Cancellation (SIC) on two of the main random access paradigms, namely Slotted ALOHA (SA) and Carrier-Sense Multiple Access (CSMA). The key varying parameter is the target Signal to Interference plus Noise Ratio (SINR) at the receiver, directly tied to the spectral efficiency of the adopted coding and modulation scheme. Two different regimes are highlighted that bring the system to work at relative maxima of the sum-rate. We further investigate the impact of different transmission power settings and imperfect interference cancellation. Leveraging on the insight gained in the saturated node scenario, an adaptive algorithm is defined for the dynamic case, where the number of backlogged nodes varies over time. The numerical results provide evidence of a significant potential for grant-free multiple access, calling for practical algorithms to translate this promise into feasible realizations.

Iterative frequency-domain equalization with multipath interference cancellation for aeronautical telemetry

The increasing transmitted signal bandwidth of aeronautical telemetry systems leads to the channel’s frequency selectivity. Equalization techniques are always adopted to conquer such problems. To optimize the equalization performance, we pursue minimizing the mean square error (MSE) of the equalizers. The solution shows that equalizing the line-of-sight (LOS) signal results in a lower MSE than equalizing the received signal directly. Thus, we proposed an iterative equalization algorithm with multipath interference cancellation (MIC) in this letter. In each iteration, the MIC is used to extract the LOS signal from the received signal. Then, we equalize the LOS signal to reduce the MSE of the equalization. Finally, the symbols are detected from the equalized LOS signal to achieve bit-error-rate (BER) performance improvement. The numerical results demonstrate that the proposed method provides a superior BER performance with lower complexity compared to the state-of-the-art equalizers.

Accurate Low-Angle Tracking Using Successive Interference Cancelation and Single-Tone Frequency Estimation

This paper tackles the low-angle target tracking problem caused by surface-reflected multipaths through successive interference cancelation (SIC) and single-tone frequency (STF) estimation. The coherent specular multipath component in the received radar signal is canceled through SIC, after which the angle-of-arrival (AoA) of the direct path is accurately estimated by applying STF estimation to the interference-suppressed signal. To further improve estimation accuracy, we develop an iterative process where SIC and STF are sequentially repeated. Drawing on the AoA of the direct path estimated using STF, a more accurate AoA of the specular path is obtained by exploiting their geometrical relationship between the two paths, which is then used to suppress the specular multipath in the received radar signal more precisely during the next SIC process. Computer simulations verify that the proposed angle estimation method using SIC and STF (AE-SICSTF) outperforms conventional angle estimation methods. Furthermore, while computational complexity analysis shows that the complexity of each iteration in AE-SICSTF is comparable to that in three-dimensional beam-domain maximum likelihood, it is also found that the former requires less than 10 iterations to converge the root mean square error performance, resulting in considerably less computing time than the refined maximum likelihood and root-MUSIC algorithms.

Design and operation of a whole-body MRI scanner without RF shielding.

To investigate how a clinical MRI system can be operated without an RF cabin. Receive interference cancellation via signal processing and active transmit emission suppression are evaluated for mitigating image artifacts and achieving electromagnetic compatibility. A clinical whole-body MR scanner with B0 = 0.55 T was placed in an environment without RF shielding. The signals of 16 additional auxiliary receive antenna elements outside the scanner bore were used to remove interference from the wanted MR signal via a dedicated sidelobe cancellation algorithm. In vivo measurements with different MR sequences were performed in the presence of ambient RF noise and additional artificial interferers, covering brain and abdominal applications. To investigate the transmit electromagnetic compatibility, simulations with different auxiliary transmit antenna arrangements and body coil loading conditions were performed, and their emission suppression performance in the far field was evaluated. The MR sidelobe cancellation algorithm successfully removed interference artifacts up to more than 3 times of the wanted MR image energy; difference images carried little to no visibly removed wanted signal. According to the simulations, electromagnetic compliance can be achieved with 32 or more auxiliary transmit antennas. The number and placement of sensor points are essential. A whole-body 0.55T MR scanner can be operated without RF shielding. Image artifacts from external interference can be removed, requiring only a modest number of auxiliary antennas. Electromagnetic compliance appears to be achievable using active transmit cancellation, but the required hardware efforts may not be practical.

Secrecy performance of D2D assisted cooperative uplink NOMA system with optimal power allocation strategy

This paper investigates the physical-layer security (PLS) aspects of the uplink cooperative non-orthogonal multiple access (NOMA) system in the context of two user scenario. More specifically, this work employs device-to-device (D2D) pair users (i.e., D1, and D2) to further improve the spectral efficiency (SE) of the proposed cooperative uplink NOMA (CU-NOMA) system. One D2D user acts as a decode-and-forward relay, improving the performance of both the cell-edge user (CU) and another D2D user i.e., (D2). We analyze the secrecy performance of CU and D2 under perfect and imperfect successive interference cancellation (SIC), and optimizes power allocation (PA) to boost the performance. The proposed CU-NOMA system is evaluated in terms of its performance metrics like ergodic secrecy capacity (ESC), ergodic secrecy sum capacity (ESSC), non-zero secrecy capacity (NSC), effective secrecy throughput (EST), and secrecy outage probability (SOP) under the presence of an external eavesdropper (Eav). In addition, this work derives the closed-form analytical expressions of ESC, NSC, EST, and SOP metrics for both CU and D2 under perfect SIC (pSIC) and imperfect (ipSIC) cases in order to characterize the secrecy performance of the proposed secure CU-NOMA network. Further, the outcomes of the simulations are shown as evidence for both the validation of the mathematical analysis and the performance of the method being suggested. The simulation result analysis of this work infers that the secrecy performance of CU-NOMA system with optimal PA exhibits superior performance than that of the fixed PA scheme.

Innovative Approaches to Beam Forming Antenna Array Systems with Adaptive Partial Update NLMS Algorithms

Improvements in interference cancellation, energy economy, spectrum efficiency, and system security are among the most pressing needs for today's wireless networks. One effective technique for this is the use of a Beamforming Array Antennas (BAA). However, the complexity of the Beamforming (BF) network, the long convergence time, and the large number of adjustable weight coefficients, all work against full band BAA. The key innovation and contribution of this research was to use Partial Update (PU) instead of full band adaptive algorithms, as no previous attempt had been made to do so. A subset of the array's elements, rather than all of them, will be connected to by PU methods. This allows the system to reduce the number of active antennas across all cells while maintaining high efficiency, and low cost. In this research, a new architectural model was proposed that makes use of PU adaptive algorithms, to reduce the required number of phase shifters (PSs), and hence base station antennas. For the most part, we will be discussing PU Normalized Least Mean Square (PU NLMS) algorithms like M-max NLMS, Periodic-NLMS, and Stochastic-NLMS. Using a Uniform Linear Array (ULA) Antennas in a simulation environment, we find that the, in terms of Mean Square Error (MSE), convergence rate, and steady-state error, it is evident that all PU NLMS algorithms (with the exception of Periodic-NLMS) had performed close, and approximately equivalent performance to the full band NLMS algorithms. In other hands, these PU algorithms maintain the radiation pattern with as little change from the original (distortion-free) as possible and symmetrical of the array, while. fewer elements are needed to produce the same amount of radiation. Reducing the number of required coefficients N to M (M = 5; M: Number of coefficients to be update per iteration) compared to the full update method (N = 8), to obtain the Reduction ratio 38%.

Symbol-level scheme for combating eavesdropping: Symbol conversion and constellation adjustment

In the non-orthogonal multiple access scenario, users may suffer inter-multiuser eavesdropping due to the feature of successive interference cancellation, and the conditions of eavesdropping suppression methods in the traditional schemes may not be satisfied. To combat this eavesdropping, we consider physical layer security and propose a novel scheme by specially designing symbol conversion and constellation adjustment methods. Based on these methods, the amplitudes and phases of symbols are properly changed. When each user intercepts information as an eavesdropper, he/she has to accept high error probability, or he/she has to undergo exorbitant overhead. Analytical and numerical results demonstrate that the proposed scheme can protect the privacy of information, and this protection does not destruct the execution of successive interference cancellation and symbol transmission.

Silicon photonic integrated wideband radio frequency self-interference cancellation chip for over-the-air in-band full-duplex communication

Compared with the traditional frequency division duplex and time division duplex, the in-band full-duplex (IBFD) technology can double the spectrum utilization efficiency and information transmission rate. However, radio frequency (RF) self-interference is a key issue to be resolved for the application of IBFD. The photonic RF self-interference cancellation (SIC) scheme has the advantages of wide bandwidth, high amplitude and time delay tuning precision, and immunity to electromagnetic interference. To meet the requirements of the new generation of mobile terminals and satellite payloads, the photonic RF SIC system is desired to be miniaturization, integration and low power consumption. In this paper, the integrated photonic RF SIC scheme is proposed and demonstrated on silicon-based platform. By utilizing the opposite bias points of the on-chip dual Mach-Zehnder modulators, the phase inversion relationship for SIC is realized over a broad frequency band. The time delay structure combining the optically switched waveguide and compact spiral waveguide enables continuous tuning of time over a wide bandwidth. The optical amplitude adjuster provides efficient amplitude control with a large dynamic range. After being packaged with optical, direct current and RF design, the photonic RF SIC chip exhibits the interference cancellation capabilities across L, S, C, X, Ku, K, and Ka bands. In the S and C bands, a cancellation depth exceeding 20 dB was measured across a bandwidth of 4.8 GHz. An impressive cancellation depth of over 40 dB was achieved within a bandwidth of 80 MHz at central frequency of 2 GHz. For the application of over-the-air IBFD communication at the newly promulgated center frequency of 6 GHz for 5G communication, the cancellation depth of 21.7 dB was demonstrated in the bandwidth of 100 MHz and the low power signals of interest were recovered successfully.

Modeling and Performance Evaluation of a Cellular Network with OMA and NOMA Users with Batch Arrivals by Means of an M[X]/M/S/0 Model

Nowadays, efficient spectrum usage is one of the most important design principles to take into account in wireless communications due to the exponential growth of mobile devices. In that sense, solutions such as Non-Orthogonal Multiple Access (NOMA) and cognitive radio (CR) have been proposed. In essence, NOMA allows some interference level by using non-orthogonal resource allocation with a tolerable increase in receiver complexity employing successive interference cancellation (SIC). In this work, a novel mathematical model of teletraffic for users performing accessment, simultaneously, by means of Orthogonal Multiple Access (OMA) and NOMA, is developed using a Markovian process that considers bursts of arrivals to model the access schemes. This novel procedure implies a closed-form solution of the proposed system compared to other works where these parameters are estimated assuming the moment generating function obtained with approximation models. The model is validated with a discrete event simulator, considering different scenarios and simulation conditions. The simulation results are in agreement with the mathematical solution proposed.

Tridiagonal Weighting‐Based Interference Cancellation Method in High‐Mobility OFDM Systems

ABSTRACTIn orthogonal frequency division multiplexing (OFDM) systems, the time‐selective fading channel causes the signal Doppler expansion in high‐mobility scenarios, leading to intercarrier interference (ICI) in the received signals. People had employed a full‐dimensional weighting matrix method to reduce the Doppler‐assisted ICI, though it required a high implementation complexity. In order to reduce the ICI and produce lower complexities, this paper proposes to exploit the tridiagonal weighting matrix to suppress ICIs, in which an optimization problem is constructed to design the tridiagonal weighting matrix, and the nonzero coefficients within the tridiagonal matrix denote optimization variables. Moreover, the optimization objective exploits the system bit error rate (BER) instead of the conventional signal to interference plus noise ratio (SINR), which results in a highly nonlinear optimization problem. Therefore, an iterative solving approach is proposed according to the successive convex approximation (SCA). Simulations show that the proposed method can achieve a good balance between the complexity and BER degradation, especially in the scenario with moderate Doppler spreads.

Reducing Successive Interference Cancellation Iterations in Hybrid Beamforming Multiuser Massive Multiple Input Multiple Output Systems Through Grouping Users with Symmetry Channels

This paper presents a comprehensive exploration of advanced beamforming techniques tailored for millimeter-wave (mm-Wave) communication systems. In response to the burgeoning demand for higher data rates, coupled with the constraints of power consumption and hardware complexity, this study focuses on developing a hybrid beamforming framework optimized for downlink scenarios, specifically targeting groups of users based on the approximate symmetry of their channels. The primary innovation of this research lies in leveraging the symmetry of channels among near users to develop a group-based successive interference cancellation (SIC) algorithm. Unlike traditional approaches that address interference on a per-user basis, this algorithm utilizes channel symmetry within clusters of users to reduce computational complexity and improve the efficiency of SIC. By grouping users with symmetrical channel characteristics, the algorithm simplifies the interference management process while maintaining system performance. The proposed system demonstrates notable advantages over existing non-linear algorithms through extensive simulations and performance evaluations, particularly in terms of spectral efficiency and computational complexity. In this study, we further emphasize the importance of balancing spectral efficiency improvements with reduced computational demands, offering a nuanced trade-off that accommodates various operational requirements. The flexible optimization framework provided showcases the system’s adaptability to diverse deployment scenarios and network configurations.

STAR-RIS-NOMA empowered vehicle-to-vehicle communications: Outage and ergodic capacity analysis

This paper delves into the performance evaluation of a non-orthogonal multiple access (NOMA) enabled vehicle-to-vehicle (V2V) communication system empowered by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Herein, we consider that a moving access point (AP) transmits superimposed signals to nearby and distant NOMA vehicles simultaneously via reflection and transmission through a STAR-RIS equipped vehicle with 2N reconfigurable elements, respectively. Specifically, by characterizing all V2V channels as double-Rayleigh fading distributed, we derive the outage probability (OP) and ergodic capacity (EC) expressions for each NOMA vehicle, by employing both perfect and imperfect successive interference cancellation (SIC) at nearby vehicle user. Furthermore, we present the asymptotic OP behavior at high signal-to-noise ratio (SNR) regime to gain deeper insights into the diversity order of NOMA vehicles. The findings reveal that the nearby vehicle under perfect SIC and far vehicle experience a diversity order of Nπ4256−π2, which is the function of number of reconfigurable elements (N) in the STAR-RIS. Whereas, a zero diversity order is obtained for nearby user under imperfect SIC case. Moreover, we analytically discuss the high SNR slopes of EC for both user vehicles. Furthermore, Monte-Carlo simulations are conducted to validate our analytical results under various channel and system parameter configurations. We also provide a comparison between the proposed scheme and STAR-RIS based orthogonal multiple access and cooperative relaying systems.

Interference cancellation for cell-edge users in massive MIMO-NOMA systems: a contemporary overview

Interference cancellation for cell-edge users in massive MIMO-NOMA systems: a contemporary overview

Review on Preamble-Based Channel Estimation Method for FBMC/OQAM Toward 6G: Advantages, Challenges and Future Works

Filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM) is a multicarrier modulation that is expected to replace orthogonal frequency division multiplexing (OFDM) in future sixth-generation (6G) networks. FBMC/OQAM has high spectrum efficiency, cyclic prefix (CP)-free transmission, decreased out-of-band emission (OOBE), and asynchronous environment robustness. However, the orthogonality criteria of FBMC/OQAM are only in the real field. Therefore, imaginary components of complex-valued OQAM symbols cause imaginary interferences among subcarriers, affecting channel estimation (CE) processing operations. Channel estimation is a critical component of wireless communication systems. Channel estimate allows the receiver to approximate channel impulse response (CIR) to determine the impacts of the communication channel on the sent symbols. So, an accurate channel estimate is critical in FBMC/OQAM. In this review, we focus on the Preamble-based method, one of the basic methods for channel estimation in FBMC. Three preamble-based approaches have been studied: the interference approximation method (IAM), the interference cancellation method (ICM), and pairs of pilots (POP) using a single antenna and multiple input multiple outputs (MIMO). Compare them regarding bit error rate (BER) and mean square error. Also, it compares different interference approximation methods in terms of bit error rate (BER), magnitude, and peak average power ratio (PAPR). The review found the superiority of M-IAM and NPS in spectrum efficiency and PAPR. Future work that can help the researcher in this field.

Joint Decoding Technique for Collision Resolution in Non-orthogonal Multiple Access Environment

Multiple access technologies have grown hand in hand from the first generation to the 5th Generation (5G) with both performance and quality improvement. Non-Orthogonal Multiple Access (NOMA) is the recent multiple access technology adopted in the 5G communication technology. Capacity requirements of wireless networks have grown to a large extent with the penetration of ultra-high-definition video transmission, Internet of Things (IoT), and virtual reality applications taking ground in the recent future. This paper develops the Physical Layer Network Coding (PNC) for collision resolution in a NOMA environment with two users. Traditionally NOMA uses Successive Interference Cancellation (SIC) for collision resolution. While additionally a decoding algorithm is added along with SIC to improve the performance of the collision resolution. MATLAB-based simulation is developed on the NOMA environment with two users using Viterbi coding, Low-Density Parity Check (LDPC), and Turbo coding. Performance parameters of Bit Error Rate (BER) and throughput are compared for these three algorithms. It is observed that the Turbo coding performed better among these three algorithms both in the BER and throughput. The BER obtained from the SIC- Turbo is found to be performing well with an increase of about 14% from the ordinary SIC implementation. The performance of the collision resolution has increased by 13% to 14% when joint decoding techniques are used and thus increasing the throughput of the NOMA paradigm.

MRI at low field: A review of software solutions for improving SNR.

Low magnetic field magnetic resonance imaging (MRI) ( <1T) is regaining interest in the magnetic resonance (MR) community as a complementary, more flexible, and cost-effective approach to MRI diagnosis. Yet, the impaired signal-to-noise ratio (SNR) per square root of time, or SNR efficiency, leading in turn to prolonged acquisition times, still challenges its relevance at the clinical level. To address this, researchers investigate various hardware and software solutions to improve SNR efficiency at low field, including the leveraging of latest advances in computing hardware. However, there may not be a single recipe for improving SNR at low field, and it is key to embrace the challenges and limitations of each proposed solution. In other words, suitable solutions depend on the final objective or application envisioned for a low-field scanner and, more importantly, on the characteristics of a specific low field. In this review, we aim to provide an overview on software solutions to improve SNR efficiency at low field. First, we cover techniques for efficient k-space sampling and reconstruction. Then, we present post-acquisition techniques that enhance MR images such as denoising and super-resolution. In addition, we summarize recently introduced electromagnetic interference cancellation approaches showing great promises when operating in shielding-free environments. Finally, we discuss the advantages and limitations of these approaches that could provide directions for future applications.

A robust double-channel affine projection sign algorithm for blind acoustic interferences cancellation

This brief proposes a double-channel direct affine projection sign (DC-DAPS) algorithm for blind speech enhancement applications, especially in the presence of strong acoustic noise, and intensive non-Gaussian impulsive interferences. We also derive a full analysis of the stability of the proposed DC-DAPS algorithm. The performance evaluation of the proposed algorithm confirms its accuracy even under different noisy scenarios, and demonstrates that our approach outperforms the double-channel direct affine projection (DC-DAP), and the double-channel direct normalized least mean square (DC-DNLMS) algorithms. Simulation results showed that the proposed DC-DAPS algorithm could effectively achieve improved performance in combating acoustic noise and impulsive interferences, and speeding up the convergence rate even with highly correlated input signals such as the speech signal.