Orthogonal Frequency Division Multiplexing Signal Research Articles

PAPR reduction techniques Optimization-based OFDM signal for wireless communication systems

OFDM (Orthogonal Frequency Division Multiplexing) is a widely used modulation technique in many standards such as Wi-Fi (Wireless Fidelity), LTE (Long Term Evolution), and 4G. It allows for high transmission data rates and excellent spectral efficiency. However, one of the main limitations of OFDM is its high PAPR (Peak-to-Average Power Ratio). In this paper, we will first describe some methods to reduce the PAPR associated with OFDM signal. We will discuss some methods such as the clipping, the Selective mapping SLM, the Partial Transmit Sequence (PTS), and the Tone Reservation (TR). Let's list their advantages and disadvantages before focusing on the TR method which we will detail. This work aims to improve the performance of the TR method in terms of speed of convergence and reduction of the PAPR, using the conjugate different algorithms while respecting the frequency specifications of the IEEE 802.11a standard. The proposed algorithm which is based on the gradient method, Conjugate gradient methods, and Quasi-Newton method shows good performance regarding PAPR reduction and speed of convergence. The choice of an appropriate technique depends on several factors: required PAPR reduction, acceptable complexity, and performances (spectral efficiency, latency, etc.). A trade-off must be found in practice between these different criteria. It has been shown that the Quasi-Newton method algorithm with its two variants converges more quickly.

Exploring and Analyzing a Hybrid PAPR Reduction Method for OFDM Optimization

Orthogonal Frequency Division Multiplexing (OFDM) is a effective modulation technique widely used in modern communication systems, including 5G and wireless networks because of its high spectral efficiency and robustness towards multipath fading. However, OFDM signals are characterized by a high Peak-to-Average Power Ratio (PAPR), which can severely impact the power efficiency and operational cost of these systems. This research investigates and analyse effectiveness of two conventional PAPR reduction methods that is Selective Mapping (SLM), and Partial Transmit Sequence (PTS) with incorporating their approach of PAPR reduction to develop a hybrid variant: SLM-PTS. This study utilized MATLAB simulations to implement and test each PAPR reduction technique on a standard OFDM system model. Parameters such as the number of subcarriers, oversampling factor, and modulation types were systematically varied to analyze the impact on PAPR, BER, and computational complexity. The effectiveness of each technique was measured using the Complementary Cumulative Distribution Function (CCDF) of PAPR values and BER performance under different channel conditions. Key findings reveal that hybrid techniques, particularly SLM & PTS, offer significant improvements in PAPR reduction compared to traditional methods alone, without a corresponding increase in BER or computational overhead. The research underscores the potential of hybrid PAPR reduction techniques to significantly enhance the efficiency and reliability of OFDM systems. These findings have important implications for the design and optimization of next-generation wireless communication systems, suggesting that hybrid approaches can provide a balanced solution to the longstanding issue of PAPR in OFDM transmissions. This study contributes valuable insights into the practical application of combined PAPR reduction strategies, offering a pathway toward more power-efficient and robust OFDM technologies. Keywords : OFDM, PAPR, CCDF, SLM and PTS

Recovery of missing samples in Orthogonal Frequency Division Multiplexing signals with optimisation using data carriers

AbstractA method is proposed for reconstructing an Orthogonal Frequency Division Multiplexing (OFDM) signal that contains data gaps, with the aim to improve demodulation. The main objective is to use the method in a passive radar application with missing data samples and to improve target detection. The OFDM signal is assumed to comply with the Digital Video Broadcasting Terrestrial standard. The proposed recovery method is based on optimisation of a novel objective function, which consists of two parts. The first part is a function of the energy in the out‐of‐band frequencies, whereas the second, and novel part, uses the location of data carriers in the constellation diagram. The method is evaluated using both simulations and real data. The authors show that the proposed method significantly improves the OFDM signal in just a few iteration steps. The proposed method improved the condition number more than a factor ten thousand millions compared to using the least square method on the out‐of‐band frequencies only. The authors also decode the symbols with the Viterbi decoding algorithm and show how the required number of iterations with the proposed algorithm depends on the amount of missing samples and on the Signal‐to‐Noise Ratio in order to achieve a Bit Error Rate of less than one in one hundred thousand millions.

Non pilot data-aided carrier and sampling frequency offsets estimation in fast time-varying channel

This paper considers the non pilot data-aided estimation of the carrier frequency offset (CFO) and sample frequency offset (SFO) of orthogonal frequency division multiplexing (OFDM) signals in fast time-varying channel. The main obstacle is the time-variant channel response, which deteriorates the estimation validity. A practical approach to mitigate this impact is to reduce the time consumption of one-shot estimation. In this way, we propose a method to reduce the time consumption to within one OFDM symbol duration. The maximum likelihood (ML) estimator is derived based on the observations of frequency domain constellations output of two FFTs on one symbol; its closed-form approximation is then derived to reduce the calculation burden. Remarkably, our method does not require any training symbol or pilot tone embedded in the signal spectrum, therefore achieves the highest spectral efficiency. Theoretical analysis and simulation results are employed to assess the performance of proposed method in comparison with existing alternatives.

Design and performance analysis of OAM‐based multidimensional multiplexing RoF‐PON integrated access system

AbstractThe unique advantage of orbital angular momentum (OAM) provides a novel approach to breaking through the limitations of high‐capacity and long‐distance transmission in the conventional radio‐overfiber passive optical network (RoF‐PON) hybrid access network. Introducing the OAM division multiplexing (OAM‐DM) based on Laguerre–Gaussian (LG) beams into the RoF‐PON, an innovative multidimensional system architecture is proposed, which integrates with polarization‐division multiplexing (PDM), wavelength‐division multiplexing (WDM), and orthogonal frequency‐division multiplexing (OFDM) technologies. Successful long‐distance transmission of both the downstream 40 GHz radio OFDM signal and the upstream 40 Gbps on‐off keying (OOK) signal over 80 km are achieved. Additionally, at the optical network unit side, low‐cost upstream carrier re‐modulation technology and flexible access for both wired and wireless signals are realized. The proposed RoF‐OAM‐DM‐PDM‐WDM‐OFDM‐PON architecture offers a dependable solution for high‐capacity and low‐cost future communication systems, holding great importance in achieving flexible access networks.

A Novel 4 × 1 MISO-VLC System with FBMC-OQAM Downlink Signals

A novel visible-light communication (VLC) system with 4 × 1 multi-input–single-output (MISO) channels is designed. In the system, the filter bank multicarrier (FBMC) and offset quadrature amplitude modulation (OQAM) techniques are used to generate downlink signals. The principles and implementation methods are proposed and analyzed, and the light intensity and received light power distribution of four LED emitters are discussed. The results demonstrate that it not only satisfies the requirements of indoor information access but also provides daily lighting. The used FBMC-OQAM signals exhibit better reception performance than orthogonal frequency division multiplexing (OFDM) signals. The system used has a lower bit error rate (BER) and larger access bandwidth compared to a 1 × 1 single-input–single-output (SISO) system. It has the potential for application advantages in future indoor VLC system applications.

Joint signal-to-signal beat interference mitigation for the field recovery of symmetric carrier-assisted differential detection with low carrier-to-signal power ratio

As a combination of direct detection and coherent detection technologies, self-coherent detection has the advantages of low cost and optical field recovery ability. However, most of the self-coherent detection techniques are limited to single sideband (SSB) signals. Recently, carrier-assisted differential detection (CADD) has been proposed to realize complex-valued double sideband (DSB) signals, but it requires a high carrier-to-signal power ratio (CSPR) to mitigate the signal-to-signal beat interference (SSBI). Later, a more cost-effective symmetric CADD (S-CADD) has been proposed while the required CSPR is still high. In order to alleviate the high requirements of CSPR, we propose a scheme based on the joint of digital pre-distortion (DPD) at transmitter and clipping at receiver to further improve the S-CADD system performance. This joint processing can not only solve the problem of non-uniform distribution of subcarrier signal-to-noise ratio (SNR) caused by non-ideal transfer function, but also the error propagation problem caused by enhanced SSBI under low CSPR. After the validation of the 64 Gbaud 16-ary quadrature amplitude modulation (16-QAM) orthogonal frequency division multiplexing (OFDM) signal transmitted over 80 km standard single mode fiber (SSMF), the CSPR required by the proposed scheme to reach the 20% soft decision-forward error correction (SD-FEC) and 7% hard decision-forward error correction (HD-FEC) can be reduced by 1.3 dB and 2.8 dB, respectively, with a comparison of the conventional S-CADD. The results show the potential of the proposed scheme in the short-reach optical transmissions.

Millimeter-wave over fiber integrated sensing and communication system using self-coherent OFDM

Orthogonal frequency-division multiplexing (OFDM) waveform is highly preferred as a dual-function candidate for integrated sensing and communication (ISAC) systems. However, the sensitivity to both carrier frequency offset (CFO) and phase noise greatly impedes its applications in millimeter-wave ISAC systems. Here, we propose and experimentally demonstrate a photonic millimeter-wave ISAC system employing the virtual-carrier-aided self-coherent OFDM technique, wherein a digitally-generated local oscillator is transmitted along with the OFDM signal. Then, a compact CFO-immune and phase noise-immune envelope detection method is implemented for down-converting millimeter-wave communication and radar echo signals. In experiments, a V-band ISAC system is successfully implemented with a simplified remote radio unit, using the remote photonic millimeter-wave heterodyning up-conversion for downlink and the envelope detection-assisted down-conversion for uplink (or radar echoes). In the converged transmission link with a 5-km fiber link and 2-m space link, the Kramers–Kronig (KK) receiver supports a communication data rate up to 16-Gbit/s by mitigating signal-signal beat interference (SSBI). More significantly, the SSBI leads to negligible effects on the sensing performance when classic matched filtering is adopted for target identification. Consequently, a 4.8-cm range resolution and a 4-mm range accuracy are obtained for the radar sensing function.

Physical layer security scheme for key concealment and distribution based on carrier scrambling

The purpose of this study is to present a physical layer security scheme for key concealment and distribution based on carrier scrambling. The three-dimensional (3D) Lorenz system is used to generate independent chaotic sequences that encrypt the information with bit, constellation and subcarrier. In order to realize the flexible distribution of the key and ensure its security, the key information is loaded into a specific subcarrier. While key subcarrier and the ciphertext subcarrier are scrambled simultaneously. The encrypted key position information is processed and transmitted in conjunction with the training sequence (TS) to facilitate demodulation by the legitimate receiver. The processed TS can accommodate up to 10 key position information, thereby demonstrating the scheme's exceptional scalability. Experimental results show that the proposed scheme can safely transmit 131.80 Gb/s Orthogonal frequency division multiplexing (OFDM) signals across 2 km 7-core fiber. Meanwhile, the scheme enables simultaneous flexible distribution and concealment of the key, thereby offering a promising solution for physical layer security.

Dual high-order QAM-modulated mm-wave signal transmission in the Q-band enabled by simple IM/DD architecture and bandpass delta-sigma modulation.

The intensity-modulation (IM)/direct-detection (DD) systems have been proven effective and low-cost due to their simple system architecture. However, the Mach-Zehnder modulator (MZM) of the IM/DD systems only reserves its driving signal intensity. Therefore, the IM/DD systems are generally unable to transmit vector signals and have a restricted spectrum efficiency and channel capacity. Similarly, the radio-over-fiber (RoF) transmission systems based on IM/DD are limited by their simple architecture and generally cannot transmit high-order quadrature amplitude modulation (QAM) signals, which hinders the improvement of their spectrum efficiency. To address the challenges, we propose a novel, to the best of our knowledge, scheme to simultaneously transmit the dual independent high-order QAM-modulated millimeter-wave (mm-wave) signals in the RoF system with a simple IM/DD architecture, enabled by precoding-based optical carrier suppression (OCS) modulation and bandpass delta-sigma modulation (BP-DSM). The dual independent signals can carry different information, which increases channel capacity and improves spectrum efficiency and system flexibility. Based on our proposed scheme, we experimentally demonstrate the dual 512-QAM mm-wave signal transmission in the Q-band (33-50 GHz) under three different scenarios: 1) dual single-carrier (SC) signal transmission, 2) dual orthogonal-frequency-division-multiplexing (OFDM) signal transmission, and 3) hybrid SC and OFDM signal transmission. We achieve high-fidelity transmission of dual 512-QAM vector signals over a 5 km single-mode fiber (SMF) and a 1-m single-input single-output (SISO) wireless link operating in the Q-band, with the bit error rates (BERs) of all three scenarios below the hard decision forward error correction (HD-FEC) threshold of 3.8 × 10-3. To the best of our knowledge, this is the first time dual high-order QAM-modulated mm-wave signal transmission has been achieved in a RoF system with a simple IM/DD architecture.

Purposeful co-design of OFDM signals for ranging and communications

This paper analyzes the fundamental trade-offs that occur in the co-design of pilot resource allocations in orthogonal frequency-division multiplexing signals for both ranging (via time-of-arrival estimation) and communications. These trade-offs are quantified through the Shannon capacity bound, probability of outage, and the Ziv–Zakai bound on range estimation variance. Bounds are derived for signals experiencing frequency-selective Rayleigh block fading, accounting for the impact of limited channel knowledge and multi-antenna reception. Uncompensated carrier frequency offset and phase errors are also factored into the capacity bounds. Analysis based on the derived bounds demonstrates how Pareto-optimal design choices can be made to optimize the communication throughput, probability of outage, and ranging variance. Different pilot resource allocation strategies are then analyzed, showing how Pareto-optimal design choices change depending on the channel.

DMCNet-Pro: A Model-Driven Multi-Pilot Convolution Neural Network for MIMO-OFDM Receivers

Nowadays, wireless communication technology is evolving towards high data rates, a low latency, and a high throughput to meet increasingly complex business demands. Key technologies in this direction include multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM). This research is based on our previous work DMCNet. In this article, we focus on studying the deep learning (DL) application of neural networks to solve the reception of single-antenna OFDM signals. Specifically, in multi-antenna scenarios, the channel model is more complex compared to single-antenna cases. By leveraging the characteristics of DL, such as automatic learning of parameters using deep neural networks, we treat the reception process of MIMO-OFDM signals as a black box and utilize neural networks to accomplish the signal reception task. Moreover, we propose a data-driven multi-pilot convolution neural network for MIMO-OFDM receivers (DMCNet). By incorporating complex convolution and complex fully connected structures, we design a receiver network to recover the transmitted signals from the received signals. We validate the accuracy and robustness of DMCNet under different channel conditions, comparing the bit error rates with different schemes. Additionally, we discuss the factors influencing various channel effects. At the same time, we also propose a model-driven scheme, DMCNet-pro, which has a higher accuracy and fewer parameters in some scenarios. The experimental results demonstrate that the DL-based reception scheme exhibits promising feasibility in terms of accuracy and interference resistance when compared to traditional approaches.

Modified Method of PAPR Reduction Using Clipping and Filtering for Image Transmission with OFDM

Due to the capability of OFDM (Orthogonal Frequency Division Multiplexing) to handle difficult channels, the most agreeable modulation for the multi-carrier scheme in present wireless communications is to improve an all-purpose modulation scheme, especially with high data rates. The image in this research article was transmitted and received on a noisy channel using an OFDM simulation technique. Since the average peak power ratio (PAPR) is one of the main disadvantages of OFDM, a new method has been proposed to reduce the PAPR using the clipping and filtering (CF) method. When the OFDM signal has a high PAPR, it means that many subcarrier components will be added through the operation of IFFT. Also, choosing the type of modulation to examine and getting a perfect type of OFDM system that is used for transmitting the image. Furthermore, signal-to-noise ratio (SNR) was considered to find the PAPR effect on the OFDM signal. The new method was tested to get a reduction of PAPR concerning CF and without CF. This method depends on clipping the signal before transmitting it, by using a method to overcome a nonlinear distortion, and therefore, decrease the bit error rate (BER). Then a filter with multi-stages was used to minimize the noise. This whole process was repeated several times to overcome the difficulties of transmitting/receiving the signal including PAPR. BER and SNR show wonderful outcomes when BPSK is chosen. Control over transmission and reception is also considered to be the type of modulation. All simulation results were defined using an Additive White Gaussian Noise (AWGN) channel.

A Novel Intrapulse Beamsteering SAR Imaging Mode Based on OFDM-Chirp Signals

The multiple-input multiple-output synthetic aperture radar (MIMO SAR) system has developed rapidly since its discovery. At the same time, the low-disturbance and high-gain requirements of the MIMO system are continuing to increase. Through the application of digital beamforming (DBF) techniques, the multidimensional waveform encoding (MWE) technique can play a key role in MIMO systems, which can greatly improve the system’s performance, especially the multi-mission capability of radar. Intrapulse beamsteering in elevation is a typical form of multi-dimensional waveform encoding which can greatly improve the transmitting efficiency and multi-mission performance of radar. However, because of the high sensitivity of the DBF technique to height, there is significant deterioration in performance in the presence of terrain undulations. The OFDM (Orthogonal Frequency Division Multiplexing) technique is widely used in communication. Due to the similarity of radar and communication systems and the great waveform diversity of OFDM signals, the OFDM radar has recently begun to emerge as a new radar system, simultaneously, the orthogonality of OFDM signals is in the time and frequency domains, and is not affected by terrain undulation. So, this paper proposes a novel radar mode combining intrapulse beamsteering in elevation and OFDM-Chirp signals, that is, the combination of “beam orthogonality” and “waveform orthogonality”, which can greatly improve the performance and fault tolerance to interference signals. In this manuscript, the system working mode and signal processing flow are introduced in detail, and simulations for both point targets and distributed targets are carried out to verify the feasibility of the proposed mode. Simultaneously, a comparison experiment is carried out, which shows the high level of fault tolerance to terrain undulation and the high potential of the proposed radar mode in Earth observation.

Improved Algorithm of Partial Transmit Sequence Based on Discrete Particle Swarm Optimization

Orthogonal frequency division multiplexing (OFDM) in 5G has many advantages; however, one of the disadvantages is that the superposition of a large number of subcarriers leads to a high peak-to-average power ratio (PAPR) of the transmit signal. A high PAPR results in high-power amplifier distortion and performance degradation. The partial transmit sequence (PTS) algorithm is commonly used for PAPR reduction. It enumerates all combinations of phase factors, weighs the signal using each phase factor combination, and finds the set of phase factors that minimizes the PAPR value of the OFDM signal. The advantage of the PTS is that it determines the optimal solution through enumeration; however, its major drawback is the higher complexity caused by the use of enumeration. Some studies have introduced the discrete particle swarm optimization (DPSO) algorithm instead of enumeration to determine the optimal solution of the PTS algorithm. As an excellent optimization method, the DPSO algorithm represents each individual as a solution during the optimization. Through iterative updates of the initial population, individuals in the population continuously move closer to the optimal solution. This approach significantly reduces complexity compared with the exhaustive enumeration used in the traditional PTS algorithm. However, the disadvantage of the general DPSO algorithm is that it can result in premature and early convergence, which leads to degradation of the PAPR reduction performance. In this study, we propose an improved method based on the general DPSO-based PTS algorithm, and the improved algorithm MDPSO-PTS adopts dynamic time-varying learning factors, which can find the optimal combination of phase factors more efficiently. The MDPSO-PTS algorithm expands the search space when seeking the optimal combination of phase factors. This avoids the drawback of premature convergence commonly observed in general DPSO-PTS algorithms, preventing early consideration of local optima as global optima. A comparative simulation of the improved MDPSO-PTS algorithm with the general DPSO-PTS algorithm shows that the improved algorithm has stronger PAPR reduction, whereas the complexity remains basically unchanged. A comparative simulation with the traditional PTS algorithm shows a significant reduction in complexity, with only a slight, acceptable loss of reduction performance.

Parallel implement of real-time delta-sigma modulation for digital mobile fronthaul.

We propose and experimentally demonstrate a novel FPGA-based parallel architecture for delta-sigma modulation (DSM) for digital mobile fronthaul employing the DSM interface. This architecture breaks the limitations of the feedback loop in DSM, is not constrained by critical paths, and supports fully parallel processing, so it can deal with high sampling rates at low hardware operating speeds. In contrast to other parallel schemes, the proposed bit-by-bit quantization DSM avoid significant storage resources requirements for buffering. A real-time experimental system using Xilinx Kintex Ultrascale FPGA was implemented to validate the feasibility of the proposed architecture. 14 carrier aggregated orthogonal frequency division multiplexing (OFDM) signals are digitized by DSM into a 5Gb/s PAM4 signal and transmitted over a 20 km single-mode fiber (SMF). As a waveform-agnostic digitization interface, we also experimentally demonstrated the DSM with 14 carrier aggregated filter-bank-multicarrier (FBMC) signals, which can achieve better EVM performance.

Secure RoF system based on key nested polar code and feedback neural network.

With the development of 6 G network, the issue of information security is becoming more and more significant. In this paper, a secure RoF system based on key nested polar code and feedback neural network (FNN) is proposed. For the nested polar code, the original key is randomly selected from the constructed codebook and the index of key is encoded by inner polar code which is placed at the location with better channel quality bit of the frozen bit of outer polar code, for the other part of outer polar code, information bits are encrypted by chaotic sequence generated by 4-D cellular neural network. The polar coded sequence is mapped to the 16-QAM symbol for orthogonal frequency division multiplexing (OFDM) and then the OFDM signal is modulated to the optical pulse, which is delivered to users through 50 km standard single-mode fiber and 5 m wireless channel. In the receiver, successive cancellation list (SCL) decoder is used for decoding outer polar code and FNN is used for decoding inner polar code to reduce the latency. The experimental results show that, compared with the existing scheme, when the bit err rate is 10-3, the received optical power (ROP) gain of the proposed scheme with SCL2 decoder and SCL4 decoder is ∼1.2 dB and ∼1.6 dB, respectively. And compared with the traditional OFDM signal with polar code, when the bit err rate is 10-3, the ROP gain of the proposed scheme with SCL4 decoder is ∼1 dB. What's more, the randomness of the chaotic key sequence, the ability to resist brute-force attacks and the ability to resist chosen-plaintext attacks are elaborated. Therefore, the proposed scheme can greatly improve the security of the system while ensuring the correct transmission of information.

Performance optimization and parameters estimation for MIMO-OFDM dual-functional communication-radar systems

Dual-function communication radar systems use common Radio Frequency (RF) signals are used for both communication and detection. For better compatibility with existing communication systems, we adopt Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals. First, we analyze the Cramer-Rao Lower Bound (CRLB) of parameter estimation. Then, the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance. Finally, we propose a more accurate estimation method that uses Canonical Polyadic Decomposition (CPD) of the third-order tensor to obtain the parameter matrices. Due to the characteristic of the column structure of the parameter matrices, we only need to use DFT / IDFT to recover the parameters of multiple targets. The simulation results show that tensor-based estimation method can achieve a performance close to CRLB, and the estimation performance can be improved by optimizing the transmit powers.

A novel PAPR reduction scheme based on time-delay neural network for CO-OFDM systems

In this paper, we propose a low-complexity peak-to-average power ratio (PAPR) reduction scheme based on time-delay neural network (TDNN) for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems to reduce the limitation of PAPR on the total power of laser diodes and the impact of fiber nonlinear effects. The proposed scheme is jointly trained on traditional iterative clipping and filtering (ICF) scheme and simplified clipping and filtering (SCF) scheme, and changes the objective function by adjusting the given training weight α. Compared to the original orthogonal frequency division multiplexing (OFDM) signal of existing system, our method achieves an adjustable PAPR reduction of 5.31 dB to 6.12 dB for 10−4 complementary cumulative distribution function (CCDF). When bit error rate (BER) Pe=10−3, the proposed scheme (α=0.5) achieves additional transmission distances of 220 km, 55 km, 105 km, and 100 km, compared to the original OFDM signal, partial transmission sequence (PTS) scheme, ICF scheme, and feedforward neural network (FNN)-based ICF scheme, respectively. Besides, our method achieves 86.3% and 80.0% floating-point operations (FLOPs) reductions, compared with PTS scheme and ICF scheme, respectively, which effectively reduces the complexity of PAPR reduction module, saving the system computational time.

Dendrogram-based Heterogeneous Learners for Automatic Modulation Classification in DSTBC-OFDM Systems

Software-Defined Radios (SDRs) have a crucial role in dynamic spectrum sensing and sharing as they can quickly adapt to changes in their environment. Digital Modulation Recognition (DMR) enables this process by giving SDR the ability to recognize the received signal modulation format to make intelligent and autonomous decisions to switch on the optimal modulation scheme. However, with the deployment of the Distributed Space-Time Block Coding Orthogonal Frequency Division Multiplexing (DSTBC-OFDM) signals that support MIMO systems, that provides spatio-temporel multiplexing, new and challenging signal identification problems have emerged.This paper proposes a robust DMR method for relaying Space-Time Block Coding (STBC) Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed classifier is built using heterogeneous base classifiers namely, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RFC), based on a Dendrogram or decision tree structure.The Dendrogram-based Heterogeneous Learners (DHL) classifier were obtained via Ascendant Hierarchical Clustering (AHC) and by employing Higher-Order Moment (HOMs) and Higher-Order Cumulants (HOCs) as features. Moreover, we propose a grid search-based hyperparameter tuning for DHL to produce the best structure and optimize the performance.