Orthogonal Frequency Division Multiplexing Waveform Research Articles

Coded OFDM Waveforms for MIMO Radars

Emerging digital radar concepts such as orthogonal frequency-division multiplexing (OFDM) allow flexible signal generation. This opens up new opportunities in waveform design in a multiple-input multiple-output (MIMO) system such as introducing coding for signal multiplexing. In this article, coded MIMO OFDM waveforms are proposed and investigated that allow continuous and simultaneous wideband transmission for all transmitters of a multiple transmit and receive antenna array for spatial radar environment perception. Challenges for coded MIMO OFDM radar operation are derived, and three coded MIMO strategies are introduced and analyzed. Their potential is validated and compared to the standard subcarrier interleaving OFDM approach using simulations and measurements of an experimental 4 × <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 4$</tex-math></inline-formula> MIMO OFDM radar at 77GHz.

Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex-Valued Convolutional Networks

The (inverse) discrete Fourier transform (DFT/ IDFT) is often perceived as essential to orthogonal frequency-division multiplexing (OFDM) systems. In this paper, a deep complex-valued convolutional network (DCCN) is developed to recover bits from time-domain OFDM signals without relying on any explicit DFT/IDFT. The DCCN can exploit the cyclic prefix (CP) of OFDM waveform for increased SNR by replacing DFT with a learned linear transform, and has the advantage of combining CP-exploitation, channel estimation, and intersymbol interference (ISI) mitigation, with a complexity of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i> (N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). Numerical tests show that the DCCN receiver can outperform the legacy channel estimators based on ideal and approximate linear minimum mean square error (LMMSE) estimation and a conventional CP-enhanced technique in Rayleigh fading channels with various delay spreads and mobility. The proposed approach benefits from the expressive nature of complex-valued neural networks, which, however, currently lack support from popular deep learning platforms. In response, guidelines of exact and approximate implementations of a complex-valued convolutional layer are provided for the design and analysis of convolutional networks for wireless PHY. Furthermore, a suite of novel training techniques are developed to improve the convergence and generalizability of the trained model in fading channels. This work demonstrates the capability of deep neural networks in processing OFDM waveforms and the results suggest that the FFT processor in OFDM receivers can be replaced by a hardware AI accelerator.

A new PAPR and BER enhancement technique based on lifting wavelet transform and selected mapping method for the next generation waveforms

Orthogonal frequency division multiplexing (OFDM) is widely used in many digital communication systems because of its immunity to inter-symbol interference, high spectral efficiency and capability of handling multipath. Walsh-Hadamard transform (WHT) and discrete wavelet transform (DWT) have also been suggested in order to enhance the performances of multi-carrier wireless communication systems. In general, high peak-to-average power ratio (PAPR) is one of the biggest disadvantages of these systems and OFDM also has this disadvantage. Many techniques such as amplitude clipping and filtering, encoding, interleaving, tone reservation (TR), tone addition (TI), partial transmission sequence (PTS), and selected mapping (SLM) techniques have been proposed to reduce the high PAPR. Without any modification these techniques are useless due to the related symbol addition process. For this reason, we developed a new technique composed of Lifting wavelet transform (LWT) and SLM method in order to decrease the PAPR in multi-carrier systems. The performance of this new LWT-SLM scheme is measured by applying it to zero tail (ZT) discrete Fourier transform-spread OFDM (ZT DFT-s OFDM) and unique word OFDM (UW OFDM) waveforms, which are promising next generation waveforms. Simulation results show that, the ZT DFT-s OFDM system obtains the 3.3 dB PAPR gain and 0.8 dB better bit error rate (BER) performance compared to classical OFDM with proposed scheme without sacrificing BER performance.

OFDM Waveform Design for Interference Resistant Automotive Radars

Autonomous driving is experiencing a monumental technological shift, making it one of the most highly discussed topics of research. With novel technologies, like advanced driver assistance systems (ADAS), the automotive industry is making significant advancements in both driving comfort and safety. ADAS rely heavily on Frequency Modulated Continuous Waveform (FMCW) radar sensors for speed and range estimation. However, this technology suffers from interference management problem and an inherent ghost target detection with few specific waveforms. This paper introduces a new technique that utilizes Orthogonal Frequency-Division Multiplexing (OFDM) waveform to overcome ghost detection and increase robustness against interference. OFDM leverages maximum length sequence (MLS) (i.e., m-sequence) and provides orthogonality between different transmitted waveforms. Also, incorporating an appropriate scrambled sequence to the proposed waveform further reduces the impact of interference and improves the reliability of target detection. Simulations were conducted to demonstrate proposed algorithm performance for different scenarios, like single- and multiple-neighbors. Furthermore, results were compared and analyzed relative to conventional FMCW in similar scenarios.

Experimental Evaluation of RF Waveform Designs for Wireless Power Transfer Using Software Defined Radio

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest in the field of wireless power transfer (WPT) using the RF range of the electromagnetic (EM) spectrum. In this paper, we experimentally investigate the aspect of real-time energy harvesting (EH) via different types of waveform designs such as orthogonal frequency division multiplexing (OFDM), square, triangular, sinusoidal, and sawtooth. We make use of a Software Defined Radio (SDR) and a Powercast P21XXCSR-EVB EH module to carry out the experiments on a practical device to assess performance. Specifically, we are interested in obtaining some insights based on the comparison between the aforementioned waveform designs from the perspectives of the separation distance between the USRP and P21XXCSR-EVB EH module, and power emission via USRP. In this vein, we perform additional subsequent experiments after reporting the practical effectiveness of the OFDM waveform, which also follows our intuitive analysis. Correspondingly, we study the effect on WPT with variable USRP transmit power, the separation distance between the USRP and EH antennas, number of OFDM sub-carriers, and multipath setting. As an application of OFDM, the effectiveness of fifth generation-new radio (5G-NR) and long-term evolution (LTE) waveforms are also tested for the WPT mechanism. The demonstration of the EH is provided in terms of the above-mentioned investigation metrics while seeking the best waveform to support WPT.

Time-and-Frequency Hybrid Multiplexing for Flexible Ambiguity Controls of DFT-coded MIMO OFDM Radar

A time-and-frequency hybrid multiplexing technique for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) radar is proposed. Discrete Fourier transform (DFT)-coded OFDM waveforms are introduced, which allow it to be free from range-dependent angle errors. These are readily used to provide both time-domain multiplexing and frequency-domain multiplexing in the MIMO OFDM radar. The DFT- coded frequency-domain multiplexing shortens the maximum unambiguous range, while the DFT- coded time-domain multiplexing lowers the maximum Doppler ambiguity. A hybrid of both domain multiplexing techniques can mitigate the respective limitations by adaptively selecting the proper DFT matrix size in each multiplexing domain. This allows to solve the intrinsic range and Doppler ambiguity problems of MIMO radars by controlling the hybrid ratio of the two kinds of DFT- code based multiplexing methods. Range-Doppler and range-angle maps of four examples with different hybrid multiplexing ratios are simulated with a MIMO OFDM radar numerical platform.

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets.

BER Analysis of Integrated WFRFT-OTFS Waveform Framework Over Static Multipath Channels

Orthogonal time frequency space (OTFS) modulation has been proposed to achieve outstanding performances over delay-Doppler channels in comparison with orthogonal frequency division multiplexing (OFDM) systems. Particularly, transmitter and receiver structures of OTFS are same as those of asymmetric OFDM (A-OFDM) waveforms, and OTFS is simplified as A-OFDM over static multipath channels. In this letter, we propose an integrated waveform framework based on weighted-type fractional Fourier transform (WFRFT) with two-dimensional adjustable parameters and strong scalability, called as WFRFT-OTFS, which can be reduced to OTFS, A-OFDM, hybrid carrier (HC), OFDM and other waveforms. Basically, theoretical BER expressions of integrated WFRFT-OTFS framework over multipath channels with zero forcing (ZF) and minimum mean square error (MMSE) receivers are derived through fusing different waveform components and verified by simulation results.

OFDM-Based Radar Network Providing Phase Coherent DOA Estimation

Next-generation radar sensors require imaging capabilities with high angular resolution. As for a single sensor, the aperture, and thus the achievable resolution, is limited due to the constraints of the front end, radar networks consisting of multiple sensors are a possible solution. However, their incoherency usually makes joint angle estimation impossible. This article presents a network concept consisting of an orthogonal frequency-division multiplexing (OFDM) radar and repeater elements, which receive the reflections from targets and retransmit them back to the radar. Thereby, any frequency conversion from radio frequency to baseband and vice versa is omitted such that the signal remains coherent to the initial transmit signal. To distinguish the bistatic signal transmitted by the repeater from the monostatic one of the OFDM radar, the orthogonal subcarrier structure of OFDM waveforms is exploited by combining a sparse radar transmit signal with a low-frequency modulation in the repeater. This allows to evaluate the bistatic signals at the radar with standard multiple-input-multiple-output (MIMO)-OFDM signal processing, leading to separate range-Doppler images for each virtual channel. Finally, it is shown that this method offers a coherent angular estimation based on the extended aperture of the network. For this purpose, a method to establish phase coherency by a reconstruction of the modulation phase is presented. The network concept is proved with measurements at 77 GHz.

A Novel OFDM Waveform With Enhanced Physical Layer Security

This letter proposes a secure orthogonal frequency division multiplexing (OFDM) waveform based on two physical-layer secrecy enhancing methods. The first method is time-domain pre-coding that involves interleaving and scaling based on a key shared between two legitimate parties adopting the OFDM waveform. The second method is a random change of the cyclic prefix (CP) size resulting in the randomization of the OFDM symbol time. The CP size is also changed based on a key agreed upon between the legitimate parties. The proposed methods not only increase the detection complexity at the eavesdropping node, but also suppress any cyclic features that distinguish OFDM waveforms. The evaluation of the proposed methods is carried out by deriving a closed-form expression for the ergodic secrecy rate of the system. Then, the effect of pre-coding on the quality-of-service performance is analyzed. The proposed methods achieve a considerable secrecy performance gain when proper equalization is implemented at the legitimate receiver.

Piecewise Digital Predistortion for mmWave Active Antenna Arrays: Algorithms and Measurements

In this paper, we describe a novel framework for digital predistortion (DPD) based linearization of strongly nonlinear millimeter-wave active antenna arrays. Specifically, we formulate a piecewise (PW) closed-loop (CL) DPD solution and low-complexity gradient-adaptive parameter learning algorithms, together with a region partitioning method, that can efficiently handle deep compression of the PA units. The impact of beamsteering on the DPD performance is studied, showing strong beam-dependence, thus necessitating frequent updating of the DPD. In order to facilitate fast adaptation, an inexpensive, non-iterative, pruning algorithm is introduced, which allows to significantly reduce the amount of model coefficients. The proposed methods are validated with extensive over-the-air RF measurements on a 64-element active antenna array transmitter operating at 28 GHz carrier frequency and transmitting a 400 MHz 5G New Radio (NR) standard-compliant orthogonal frequency division multiplexing waveform. The obtained results demonstrate the excellent linearization capabilities of the proposed solution, conforming to the new 5G NR requirements for frequency range 2 (FR2) in terms of both inband waveform quality and out-of-band emissions. The proposed PW-CL DPD is shown to outperform the state-of-the-art PW DPD based on the indirect learning architecture, as well as the classical single-polynomial based DPD solutions in terms of linearization performance and computational complexity by a clear margin.

A Novel Spaceborne MIMO-SAR Imaging Scheme Based on Improved OFDM Waveforms

In recent years, the multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) concept has been widely researched because it can provide more degrees of freedom to dramatically improve SAR system performance. However, the echo separation issue of different transmit antennas is the most challenging issue and it stirs up extensive discussions. In this letter, a novel MIMO-SAR imaging scheme based on the improved orthogonal frequency-division multiplexing (OFDM) waveforms is proposed. The main contributions of this work are that: <list list-type="ordered" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><list-item><label>1)</label> Improved generation method for <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> OFDM waveforms is presented. This method can compensate the extra carrier frequency deviation and compared with the other compensation methods, this method is more general and suitable for <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> OFDM waveforms. </list-item><list-item><label>2)</label> Based on the proposed OFDM waveforms, a novel and low-cost spaceborne MIMO-SAR imaging scheme is proposed. </list-item> </list> In this scheme, a simple time-shift weighting process and a bandpass filter bank are employed to separate the echoes from the close arrival angles. Then, the digital beamforming (DBF) on receive in elevation is employed to separate the echoes from far arrival angles. Furthermore, the distributed scene simulation results are presented to verify the practicability of the proposed scheme.

OFDM waveform for distributed radar sensing in automotive scenarios

AbstractIn this paper, an orthogonal frequency-division multiplexing (OFDM) waveform radar sensing approach is demonstrated based on field measurements at C-band. We demonstrate a concept that is based on the exploitation of typical wireless communication transmissions to perform passive, distributed radar sensing. Our concept is based on an OFDM radar that operates in the modulation symbol domain and can be well integrated into existing OFDM receivers. The measurement setup and the signal processing steps for the OFDM radar are described. The results show that the passive, distributed radar sensing approach can be used to detect and localize moving cars and even pedestrians in automotive intersection scenarios.

Ground Moving Target Imaging (GMTIm) Algorithm in OFDM SAR Based on First-Order Keystone Transform

The use of Orthogonal Frequency Division Multiplexing (OFDM) waveform in place of Linear Frequency Modulation (LFM) signal is one of the latest topics in the field of Synthetic Aperture Radar (SAR) imaging. The advantages of imaging by this technique include resistance to certain types of radar jamming techniques, reduced ambiguity in Doppler spectrum with an increase in the number of sub-bands, and extraction of target phase history based on phase approximation of all OFDM subcarriers. In conventional SAR imaging algorithms, it is assumed that the targets are stationary in the imaging zone as these algorithms do not have the required efficiency to image moving targets, leading to blurred images and high Integrated Side Lobe Ratio (ISLR). To circumvent these problems, there is a requirement of designing appropriate imaging algorithms, keeping in mind the important issues related to the moving targets in the imaging zone. Thus, in this study, we propose the implementation of the OFDM waveform for imaging moving targets alongside the first-order keystone transform to solve the above-mentioned problems.

An edge computing framework based on OFDM radar for low grazing angle target tracking

In this paper, a novel adaptive algorithm to detect and track targets with low grazing angle is addressed. For this purpose, an orthogonal frequency division multiplexing (OFDM) radar signal is employed through an edge computing framework over the radar platform. However, detecting the targets in the low grazing angle area is a great challenge due to severe multipath reflection effects. The Earth’s curvature geometry model is presented as the multipath propagation model. Based on the fact that the different scattering centers of a target resonate at different frequencies, we use the optimized OFDM waveform and propose a novel target tracking procedure for low grazing angle target tracking scenarios. The obtained results show that using an OFDM radar waveform provides a more uniform detection coverage in the presence of multipath propagation such that this will fill in the nulls. Finally, simulations are used to compare the performance of the proposed OFDM waveform with the conventional equal-power, the generalized likelihood ratio (GLR)-based and single-carrier waveforms.

OFDM Based RADAR-Communication System Development

Abstract This paper highlights the hardware implementation of orthogonal frequency division multiplexing (OFDM) based joint radar and communication (RADCOM) system for the vehicular application. Improvement of the communication system due to the application of OFDM is well established and the same advantages can be exploited to enhance the radar performance. The frequency diversity of the OFDM signal improves the radar performance significantly. This motivates the authors to develop a RADCOM system based on OFDM waveform. This paper includes the performance analysis of the OFDM based RADCOM system under the dynamic vehicular channel conditions. Communication system performance is analyzed based on the bit error rate (BER) and the performance of the radar system is evaluated based on target detection.

Adjacent Channel Compatibility Evaluation and Interference Mitigation Technique Between Earth Station in Motion and IMT-2020

The millimeter wave band is becoming popular for mobile broadband usage such as fifth-generation (5G) mobile and mobile satellite services utilizing earth stations in motion (ESIM). According to the 2019 World Radiocommunication Conference (WRC-19), the 5G and ESIM systems will operate in adjacent frequency bands bounded by 27.5 GHz; therefore, the adjacent channel compatibility between ESIM and 5G should be verified. Both, the minimum coupling loss (MCL) and Monte-Carlo (MC) methods are applied to assess the worst and most practical interference effects, respectively, for all types of ESIM including the following: maritime ESIM (M-ESIM), land ESIM (L-ESIM), and aeronautical ESIM (A-ESIM). The distance and guard band between the two systems are indicated by the compatibility conditions. In addition to the conventional interference-to-noise ratio ( $I/N$ ), the throughput loss of a 5G system is proposed to assess the performance degradation caused by the ESIM interference. Two orthogonal frequency division multiplexing (OFDM) waveforms are proposed to suppress ESIM power leakage into an adjacent channel. A mathematical expression regarding the power spectral density (PSD) and frequency dependent rejection (FDR) is derived for these waveforms, suggesting that the interference can be alleviated. A measured single carrier waveform of a commercial ESIM equipment is used as the benchmark against the proposed OFDM waveforms. The windowed OFDM is able to reduce the guard band by 50–77%. The results obtained for various elevation angles of the ESIM antenna are determined to be applicable to various regions globally.

Performance Investigation of Peak Shrinking and Interpolating the PAPR Reduction Technique for LTE-Advance and 5G Signals

Orthogonal frequency division multiplexing (OFDM) has become an indispensable part of waveform generation in wideband digital communication since its first appearance in digital audio broadcasting (DAB) in Europe in 1980s, and it is indeed in use. As has been seen, the OFDM based waveforms work well with time division duplex operation in new radio (NR) systems in 5G systems, supporting delay-sensitive applications, high spectral efficiency, massive multiple input multiple output (MIMO) compatibility, and ever-larger bandwidth signals, which has demonstrated successful commercial implementation for 5G downlinks and uplinks up to 256-QAM modulation schemes. However, the OFDM waveforms suffer from high peak to average power ratio (PAPR), which is not desired by system designers as they want RF power amplifiers (PAs) to operate with high efficiency. Although NR offers some options for maintaining the efficiency and spectral demand, such as cyclic prefix based (CP-OFDM), and discrete Fourier transform spread based (DFT-S-OFDM) schemes, which have limiting effects on PAPR, the PAPR is still as high as 13 dB. This value increases when the bandwidth is increased. Moreover, in LTE-Advance and 5G systems, in order to increase the bandwidth, and data-rate, carrier aggregation technology is used which increases the PAPR the same way that bandwidth increment does; therefore, it is essential to employ PAPR reduction in signal processing stage before passing the signal to PA. In this paper, we investigate the performance of an innovative peak shrinking and interpolation (PSI) technique for reducing peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) based signals at waveform generation stage. The main idea behind the PSI technique is to extract high peaks, scale them down, and interpolate them back into the signal. It is shown that PSI technique is a possible candidate for reducing PAPR without compromising on computational complexity, compatible for existing and future telecommunication systems such as 4G, 5G, and beyond. In this paper, the PSI technique is tested with variety of signals in terms of inverse fast Fourier transform (IFFT) length, type of the signal modulation, and applications. Additional work has been carried out to compare the proposed technique with other promising PAPR reduction techniques. This paper further validates the PSI technique through experimental measurement with a power amplifier (PA) test bench and achieves an adjacent channel power ratio (ACPR) of less than –55 dBc. Results showed improvement in output power of PA versus given input power, and furthermore, the error vector magnitude (EVM) of less than 1 % was achieved when comparing of the signal after and before modification by the PSI technique.

Adaptive OFDM Waveform Design for Cognitive Radar in Signal-Dependent Clutter

The problem of adaptive orthogonal frequency division multiplexing (OFDM) waveform design in the case of stochastic extended targets in the presence of strong and nonstationary interferences is an essential part of a cognitive radar system. In this article, a new approach is developed based on maximizing the mutual information between the random target impulse response and the received echoes with respect to the transmitted waveform. We use the advantage of OFDM signals and present an adaptive structure to match the complex weights of OFDM signal with the radar scene for making complete use of the transmission power. The interference reflections are utilized rather than eliminating them to design the weights of the transmitted OFDM signal. The optimization algorithm for designing transmitted signals is based on adaptive learning whose essential information is obtained by a feedback between receiver and transmitter. This feedback includes essential target and interference characteristics which extracted from the reflected echoes. Based on changes in interference features, the weights of the transmitted OFDM signal on each subcarrier are designed and transmitted in the next coherent processing interval. Experimental results reveal that the proposed approach achieves a higher rate of performance compared to nonadaptive waveform design approaches.

Integrated Communication and Localization System With OFDM-Chirp Waveform

This paper proposes an integrated communication and localization system scheme using orthogonal frequency division multiplexing (OFDM) chirp waveform. A new and efficient generation method is proposed to produce the OFDM-chirp waveform. The OFDM-chirp waveform is quantitatively compared with conventional OFDM waveform with respect to complementary cumulative distribution function of the peak-to-average power ratio. The OFDM-chirp waveform is analyzed by the ambiguity function together with its matched filtering performance. Furthermore, we implemented the OFDM-chirp waveform for integrated communication and localization with the universal software radio peripheral platform. Experimental results show that it outperforms conventional OFDM waveform for integrated communication and localization applications.