SINR Analysis of a Narrowband Interference Cancellation Scheme in OFDM Communication Systems

Han

IEEE Trans. Veh. Technol.

et al. 2022

Wireless communication in vehicular networks is highly vulnerable to electromagnetic interference, which seriously undermines the communication effectiveness. Thus, interference estimation and elimination are essential in vehicular communications. To solve the multitasking problem of interference estimation and cancelation within the transformation domain of vehicular communications where they are divided into the consistency and inconsistency based on the different conditions of spectrum sensing, the present study proposes an iterative Bayesian sparse learning approach for simultaneous interference recovery and elimination which applies multiple Bayesian learning for measured signals, and the structured sparse learning method for simultaneous interference mitigation with signal recovery. Furthermore, the updating optimization based on Bayesian estimation framework is performed to facilitate the learning process and improve the performance of interference estimation and signal reconstruction. Simulation results show that the proposed algorithms achieved more rapid convergence and more accurate recovery (31.84% and 27.88% higher in spectrum sensing with consistency and inconsistency, respectively) than conventional algorithms. During all iterations, the proposed algorithms, because of updating optimization, were more robust than conventional ones, but the computational complexity remained largely the same. To explore the correlation between the parameters and the interference recovery performance, we performed experiments, which revealed linear, logarithmic, and exponential regression correlations for particular forms of interference. We also compared the demodulation performance of the proposed algorithm with existing methods, and it turned out the proposed algorithm also obtained higher gains on average in the bit error rate.

Section: A Structured Sensing With Consistent Spectrummentioning

confidence: 99%

Section: A Structured Sensing With Consistent Spectrummentioning

confidence: 99%

Maintaining the Status Quo: Simultaneous Estimation and Elimination for Multiple Interference in Transform Domain Vehicular Communication

Han

IEEE Trans. Veh. Technol.

et al. 2022

“…Because the NBI with low SIR will seriously affect the performance of OFDM systems, this article focuses on the NBI with low SIR, that is, the power of NBI is much greater than the power of signal and noise. Multiple NBIs can be expressed by the sum of multiple single-tone interferences [1]. In this paper, multiple NBIs are uniformly modeled as:…”

Section: System Model and Interference Spectral Leakage A Systemmentioning

confidence: 99%

“…The orthogonal frequency division multiplexing (OFDM) technology has the characteristics of anti-frequency selective fading and high spectrum utilization, and it has been extensively used in WLAN, 4G, 5G, and other wireless communication systems. However, OFDM systems are very sensitive to narrowband interference (NBI) with low signal to interference ratio (SIR), and a small number of in-band NBI can bring significant performance loss to OFDM systems [1]- [3]. With the development of narrowband wireless communication systems, there are more and more types of NBIs that affect the performance of OFDM systems.…”

Section: Introductionmentioning

confidence: 99%

Multiple Interacting Narrowband Interferences Suppression Algorithm for OFDM Systems

Zhang

Liu

et al. 2020

IEEE Access

The OFDM technology is widely used in wireless communication systems, but it is highly sensitive to narrowband interference (NBI). The existing NBI suppression algorithms are mainly for single NBI or multiple NBIs with an assumption that the frequency distance of the multiple NBIs is large enough. However, in reality, there are more and more multiple interacting NBIs with small frequency distance, such as NB-IoT. Unfortunately, due to the interaction of multiple NBIs, the performance of existing NBI suppression algorithms is degraded. Aiming at this problem, we propose a multiple interacting NBIs suppression algorithm jointed time-frequency domain for OFDM systems. First, in order to achieve a high-precision and low-complexity frequency estimate for a single NBI, an interference frequency estimation method based on chirp-z transform (CZT-IFE) is studied. Then, for multiple interacting NBIs, based on the analysis of NBI frequency distance and spectral aliasing, a highly robust interference frequency estimation method combining IIR notch filter and CZT-IFE (NF-CZT-IFE) is given. It eliminates the interaction of multiple NBIs and obtains the accurate frequency estimates of the NBIs. Finally, based on NF-CZT-IFE, the multiple interacting NBIs are suppressed by using IIR notch filters. Simulation results demonstrate that the proposed multiple interacting NBIs suppression algorithm has better interference suppression performance on the NBIs with different frequency distances and different interference numbers. The proposed algorithm improves the robustness of OFDM systems in complex NBI environments.

“…This technique requires prior knowledge of the interference model and estimation of its parameters in either the time or the frequency domains (e.g. amplitude, phase and frequency for a single-tone interferer) [24], [25]. Cancellation performance strongly depends on the accuracy of the estimated parameters.…”

mentioning

confidence: 99%

Improving Soft Decoding by Spectral Leakage Reduction in Presence of Narrow Band Interference in PLC

et al. 2019

Communications over power lines (PLC) is a promising technology for a variety of applications. The use of a single network for power and data transmission with PLC provides weight, space, and cost savings for vehicular communications. Current work focuses on broadband PLC (BPL) systems compliant with the IEEE 1901 standard. Given that transmissions occur on a physical medium not designed for data communication, the channel and noise characteristics are mostly unfavorable. To deal with these conditions, turbo codes have been widely employed due to their high performance. However, their performance strongly depends on the accuracy of the noise estimation. This work addresses the estimation of the noise power spectral density (PSD) to perform soft-decoding. A general background noise (GBN) model and a narrowband interference (NBI) model is considered. To the best of our knowledge, this is the first work that analyzes the effects of the NBI leakage on noise estimation when it is performed during the reception of the data frame. We propose the use of the frame control (FC) symbol to reduce interference leakage on noise estimation. In addition, we investigate the use of payload symbols to further reduce spectral leakage. Finally, we show that system performance considerably improves by using the FC-based estimation in soft-decoding procedures. INDEX TERMS Frame control symbol, IEEE Std. 1901, narrowband interference, noise power spectral density estimation, soft-decoding, spectral leakage. I. INTRODUCTION Data communication over power lines is a promising technology for a variety of applications. At the turn of the century, power line communications (PLC) received a renewed interest driven by the increased popularity of Automatic Meter Reading (AMR) systems, Smart Grids and building automation [1]. As a result of this development a variety of standards emerged between 2010 and 2013 [2]-[5]. Specifically, technical advances in broadband PLC (BPL) systems enable a variety of applications besides AMR due to its higher data rate compared to older PLC systems. This work focuses on PLC systems operating in the 1.8-50 MHz range compliant with the IEEE 1901 Std. [2]. The associate editor coordinating the review of this manuscript and approving it for publication was Andrea M. Tonello.