Orthogonal Frequency Division Multiplexing Parameters Research Articles

Jamming Detection and Classification in OFDM-Based UAVs via Feature- and Spectrogram-Tailored Machine Learning

In this paper, a machine learning (ML) approach is proposed to detect and classify jamming attacks against orthogonal frequency division multiplexing (OFDM) receivers with applications to unmanned aerial vehicles (UAVs). Using software-defined radio (SDR), four types of jamming attacks; namely, barrage, protocol-aware, single-tone, and successive-pulse are launched and investigated. Each type is qualitatively evaluated considering jamming range, launch complexity, and attack severity. Then, a systematic testing procedure is established by placing an SDR in the vicinity of a UAV (i.e., drone) to extract radiometric features before and after a jamming attack is launched. Numeric features that include signal-to-noise ratio (SNR), energy threshold, and key OFDM parameters are used to develop a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">feature-based</i> classification model via conventional ML algorithms. Furthermore, spectrogram images collected following the same testing procedure are exploited to build a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">spectrogram-based</i> classification model via state-of-the-art deep learning algorithms (i.e., convolutional neural networks). The performance of both types of algorithms is analyzed quantitatively with metrics including detection and false alarm rates. Results show that the spectrogram-based model classifies jamming with an accuracy of 99.79% and a false-alarm of 0.03%, in comparison to 92.20% and 1.35%, respectively, with the feature-based counterpart.

Feasibility of Modeling Orthogonal Frequency-Division Multiplexing Communication Signals with Unsupervised Generative Adversarial Network.

High-quality recordings of radio frequency (RF) emissions from commercial communication hardware in realistic environments are often needed to develop and assess spectrum-sharing technologies and practices, e.g., for training and testing spectrum sensing algorithms and for interference testing. Unfortunately, the time-consuming, expensive nature of such data collections together with data-sharing restrictions pose significant challenges that limit data set availability. Furthermore, developing accurate models of real-world RF emissions from first principles is often very difficult because system parameters and implementation details are at best only partially known, and complex system dynamics are difficult to characterize. Hence, there is a need for flexible, data-driven methods that can leverage existing data sets to synthesize additional similar waveforms. One promising machine-learning approach is unsupervised deep generative modeling with generative adversarial networks (GANs). To date, GANs for RF communication signals have not been studied thoroughly. In this paper, we present the first in-depth investigation of generated signal fidelity for GANs trained with baseband orthogonal frequency-division multiplexing (OFDM) signals, where each subcarrier is digitally modulated with quadrature amplitude modulation (QAM). Building on prior GAN methods, we developed two novel GAN models and evaluated their performance using simulated data sets with known ground truth. Specifically, we investigated model performance with respect to increasing data set complexity over a range of OFDM parameters and conditions, including fading channels. The findings presented here inform the feasibility of use cases and provide a foundation for further investigations into deep generative models for RF communication signals.

Autocorrelation Method for Cyclic Prefix OFDM Estimation

A radio system design providing various data service needs becomes one of the Software Defined Radio (SDR) system advantages. SDR technology applies software functions further to be run in hardware platforms. The need for services with greater data rates can be resolved by using multi-carrier transmission techniques, one of which is the Orthogonal Frequency Division Multiplexing (OFDM) technique. This paper discusses the detection of OFDM signals and their parameters. Multi-carrier transmission can prevent Inter-Symbol Interference (ISI) occurrence due to multi-path fading effect. The recognition can classify the correctly received signals, including the signal conditions mixed with AWGN noise. The autocorrelation method was used to estimate the OFDM parameters, namely the one symbol duration and the cyclic prefix duration. The detected cyclic prefix durations were 1/2, 1/4, 1/8, and 1/16. This method is very simple, because with the cyclic prefix presence, a different signal peak will be detected to further estimate the cyclic prefix duration. The results show the correlation method performance can detect one symbol duration with 100%, accuracy, starting at SNR 0 dB, whereas the cyclic prefix duration accuracy rate is getting more accurate by using a less cyclic prefix duration, which is 1/16 of the total symbol duration.

Experimental Evaluation of OFDM-Based Underwater Visible Light Communication System

High-speed, reliable, flexible, and cost-effective underwater wireless communication systems have a wide variety of use in scientific, civilian, and commercial domains. Visible light communication (VLC) seems to be a promising candidate in satisfying majority of the requirements listed above. From this perspective, VLC could easily be deployed in heterogeneous wireless networking scenarios with high quality of service. Therefore, in this paper, an adapted LTE frame structure is implemented for underwater VLC (UVLC) system. The performance of UVLC system employing asymmetrically clipped optical orthogonal frequency division multiplexing modulation technique is practically tested by taking channel estimation and synchronization into account. Also, the effects of varying orthogonal frequency division multiplexing parameters on the system's signal-to-noise ratio and the bit-error-rate (BER) performances are studied. The implementation is tested for quadrature phase shift keying and 16-quadrature amplitude modulation techniques supporting both 128- and 1024-points fast Fourier transform configurations, which correspond to data rates of 1.92 and 15.36 Mbps, respectively. Experimental results show that BER could be reduced down to a level on the order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> .

A New Methodology for Network Scale Simulation of Emerging Power Line Communication Standards

This paper presents the development of a new methodology for the simulation of power line communication (PLC) within the popular electromagnetic transients programme-alternative transients programme (EMTP-ATP). As a first application, the comparative performance of the emerging orthogonal frequency division multiplexing (OFDM) based Prime and G3-PLC narrowband standards is investigated. Models of both standards have been created within the EMTP-ATP and simulations performed using frequency-dependent line models and realistic transformer models as terminations. It is observed that both standards are severely affected by the highly frequency selective nature of the Medium Voltage (MV) power line channel and a more considered choice of OFDM parameters may be necessary for optimal performance on MV networks.

Application of OFDM in Diffusion-Based Molecular Communication

In this letter, the application of orthogonal frequency division multiplexing (OFDM) in the area of diffusion-based molecular communication is studied. The focus is on direct current biased optical OFDM, asymmetrically clipped optical OFDM, and pulse amplitude modulation discrete multi-tone transmission known from optical communications. Simulation results show that the OFDM parameters have to be chosen carefully and that the bit error rate performance is in-between that of standard on-off keying transmission with maximum-likelihood sequence estimation and fixed threshold detection. In addition, it is demonstrated that a proposed bit-loading algorithm can further improve the OFDM performance.

Detection and Classification of OFDM Waveforms Using Cepstral Analysis

Cepstral analysis has been widely used in audio and speech processing applications because of its ability to reveal periodicities in a signal. The presence of cyclic prefix (CP) in orthogonal frequency division multiplexing (OFDM) signals induces periodicities. Motivated by this, the paper focuses on cepstral analysis of OFDM signal. The distributions of cepstral coefficients are derived for two scenarios of noise only and OFDM signal in noise. It is shown that the OFDM cepstrum is significantly different from the additive white Gaussian noise (AWGN) cepstrum and can be used to detect OFDM waveforms. It is also shown that the cepstrum of OFDM is rich in features and can be used to estimate OFDM parameters such as number of subcarriers and length of the CP in an OFDM symbol. These OFDM waveform parameters can be used to automatically recognize or classify different OFDM waveforms, which are important for cognitive radios, coexistence of heterogeneous networks and signal intelligence. Two schemes are proposed to detect OFDM based primary user (PU) signals in cognitive radio systems. The distributions of the test statistics under the two hypotheses are established. Neyman-Pearson detection strategy is employed. Algorithms for estimating the number of subcarriers and the length of the CP are proposed and their performances studied through simulations. Later the proposed schemes are extended to cooperative sensing scenario with multiple secondary users (SUs) and it is shown that the collaboration between them significantly improve the performance of the proposed cepstrum based detection and estimation schemes.

Stepped OFDM radar technique to resolve range and doppler simultaneously

Recent developments involving the orthogonal frequency division multiplexing (OFDM) structure call for new potentials in radar. In this paper, a novel wideband OFDM based waveform is presented and the high range resolution (HRR) processing is derived.We show by means of comparisons with standard wideband waveforms the benefits of this concept. Radial velocities can be retrieved unambiguously and high velocities can be handled at no extra computational effort since the range migration constraint is related to the small pulse bandwidth as opposed to the large synthetic bandwidth. In our analysis, we inspect the impact of Doppler modulation on the processing and give recommendations for improvement in terms of the OFDM parameters. We address the problem caused by a correlation artefact and discuss the risk of intersymbol interference (ISI) typical with OFDM. Lastly, we show that our concept has inherent low probability of detection (LPD) characteristics.

Blind STBC Identification for Multiple-Antenna OFDM Systems

This paper addresses the problem of space-time block code (STBC) identification for multiple-antenna (MA) orthogonal frequency-division multiplexing (OFDM) systems operating over frequency-selective channels for the first time in literature. Previous investigations published on the topic of STBC identification were restricted to single-carrier systems operating over frequency-flat channels. OFDM systems make this topic more challenging to handle since the identifiers work in frequency-selective channels with little or no knowledge of the beginning of the OFDM blocks, OFDM parameters, and frequency-selective channel coefficients. We show that, by taking advantage of the space-time redundancy, STBC identification can be performed by exploiting the cross-correlation of the signals received from different antennas as a discriminating feature. Using this feature, we develop a binary hypothesis test for decision making. The proposed method does not require information about the channel coefficients, modulation format, noise power, or timing of the OFDM and STBC blocks. Moreover, it does not need accurate knowledge of either clock-timing information or OFDM parameters, including the number of sub-carriers and cyclic prefix length. Extensive simulation experiments have verified the effectiveness of the proposed method.

Blind Estimation of OFDM Parameters in Cognitive Radio Networks

This paper presents a blind parameter estimation algorithm for orthogonal frequency division multiplexing (OFDM) signal affected by a time-dispersive channel, timing offset, carrier frequency offset and additive Gaussian noise. Unlike the previous studies, this paper presents the second-order cyclostationarity of OFDM signal considering the effect of time-dispersive channel. The cyclostationarity properties of received OFDM signal in time-dispersive channel is exploited to estimate the OFDM parameters. These parameters includes OFDM symbol period, useful symbol period, cyclic prefix factor, number of subcarriers and carrier frequency offset. Simulations are performed to investigate the performance of OFDM parameter estimation algorithm in diverse channel conditions.

Reconfigurable simulator using graphical user interface (GUI) and object-oriented design for OFDM systems

In this paper, a design of a new object-oriented simulation environment and graphical user interface (GUI) for versatile orthogonal frequency division multiplexing (OFDM) systems is presented. This is achieved using high-level design, parallelism and usability for the simulation environment. GUI interface can serve as a learning/research tool for students or practiced professionals to investigate particular designs. It is evident that OFDM systems intended to be used in dynamic environments must be tested under various conditions in order to be designed for optimality. Hence, a simulation design is proposed coupling the GUI, parallelism, and high-level object-oriented design techniques to be beneficial to the researcher. A high-level design and GUI layouts of the proposed simulator is shown in details. Important OFDM parameters needed for reconfiguration of transmitter components, channel condition parameters, and receiver components are discussed. In addition, this paper provides a simple technique to implement simulation partitioning for increased parallel performance of reconfigurable object-oriented OFDM simulators. This simple technique applies to scenarios where there is disproportionate simulation duration between different OFDM configurations. It is shown to decrease total simulation time considerably.