Orthogonal Frequency Division Multiplexing With Index Modulation Research Articles

Spectral efficiency improvement in cooperative RIS aided OFDM-IM system with hybrid indexing

Increasing demand for wireless communication leads to significant challenges in achieving high spectral efficiency (SE) and energy efficiency (EE). Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) is one of the considerations, although it has the inherent disadvantage of a trade-off between SE and EE. In this work, frequency-dependent control on reconfigurable intelligent surfaces (RIS) and indexing to activate or deactivate the elements of RIS have been proposed to improve the SE of OFDM-IM systems. The Upper bound pairwise error probability has been derived and confirmed by simulation. The proposed work enhances the SE and EE compared to the conventional OFDM-IM systems. For instance, SE loss of 0.5bpcu in an OFDM-IM system with quadrature phase shift keying (QPSK) compared to an OFDM system has been compensated by the proposed work by maintaining EE.

Coordinate Interleaved OFDM With Repeated In-Phase/Quadrature Index Modulation

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), which transmits information bits through ordinary constellation symbols and indices of active subcarriers, is a promising multicarrier transmission scheme and has attracted the attention of researchers due to numerous benefits such as flexibility and simplicity. Nonetheless, OFDM-IM cannot satisfy the needs of future wireless communication services such as superior reliability, high data rates, and low complexity. In this article, we propose a novel OFDM-IM scheme named coordinate interleaved OFDM with repeated in-phase/quadrature IM (CI-OFDM-RIQIM), which provides superior error performance and enhanced spectral efficiency due to its diversity order of two and clever subcarrier activation pattern (SAP) detection mechanism, respectively. In addition, CI-OFDM-RIQIM is further extended to coordinate interleaved OFDM with in-phase/quadrature IM (CI-OFDM-IQIM) by doubling information bits transmitted by IM. Furthermore, log-likelihood ratio (LLR) based low-complexity detectors are designed for both proposed schemes. Theoretical analyses are performed and an upper bound on the bit error probability is derived. Comprehensive computer simulations under perfect and imperfect channel state information (CSI), are conducted to compare the proposed and reference schemes. It is shown that CI-OFDM-RIQIM and CI-OFDM-IQIM show superior results and can be considered promising candidates for next-generation wireless communication systems.

Secure Index with OFDM-IM-based Chaotic System

Orthogonal Frequency Division Multiplexing-Index Modulation (OFDM-IM) based on chaos is a com- munication technique that uses chaotic systems to enhance the security of OFDM-IM systems. In this technique, chaotic signals are used to modulate the index values of the subcarriers and the data using DCSK, resulting in a more robust and efficient transmission. OFDM-IM uses the activated index as an information-carrying unit, which increases data rate and spectral efficiency. In this paper, we propose a secure index strategy for our system using a logistic map and Henon map to generate the chaotic signals, considering additive white Gaussian noise (AWGN) and the Raleigh fading channel. A lookup table based on the chaotic system was created using the indices of a randomized index modulation scheme with DCSK modulation. Even if the active subcarriers and their symbols are correctly calculated until the opening frame, the randomized index modulation prevents eavesdroppers from accurately determining message bits.

Vector Approximate Message Passing Based OFDM-IM Detection for Underwater Acoustic Communications.

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) has great potential for the implementation of high spectral-efficiency underwater acoustic (UWA) communications. However, general receivers consisting of the optimal maximum likelihood detection suffer from high computational load, which prohibits real-time data transmissions in underwater scenarios. In this paper, we propose a detection based on a vector approximate message passing (VAMP) algorithm for UWA OFDM-IM communications. Firstly, a VAMP framework with a non-loopy factor graph for index detection is formulated. Secondly, by utilizing the sparsity inherently existing in OFDM-IM symbols, a novel shrinkage function is derived based on the minimum mean square error criterion, which guarantees better posterior estimation. To reduce the errors from estimated non-existing indices, one trick is utilized to search the elements from the look-up table with the minimal Euclidean distance for the replacement of erroneously estimated indices. Experiments verify the advantages of the proposed detector in terms of low complexity, robustness and effectiveness compared with the state-of-art benchmarks.

Strategic Optimization and Application Analysis of Orthogonal Frequency Division Multiplexing Index Modulation Systems

Orthogonal Frequency Division Multiplexing (OFDM) is a type of Multi-Carrier Modulation that operates by dividing a single channel into numerous orthogonal subchannels. By doing this, it facilitates the transformation of high-speed digital signals into parallel subdata streams. These streams are then modulated onto the subchannels, thereby enabling efficient transmission. OFDM with Index Modulation (OFDM-IM) further enhances this process by combining the benefits of OFDM with the high spectral efficiency of spatial modulation techniques, leading to significant improvements in the bit-error rate performance of the system. Despite the advantages of OFDM-IM systems, several challenges exist. For instance, the presence of inconsistent sampling rates can result in amplitude distortion. Furthermore, a high peak-to-average power ratio can adversely impact the efficiency of the RF power amplifier. These problems necessitate the exploration of diverse solutions to improve the performance of OFDM-IM systems. The focus of this thesis is to investigate and assess different strategies aimed at addressing these issues within OFDM-IM systems. We will explore these strategies, compare their effectiveness, and offer comprehensive recommendations on their optimal applications based on specific system requirements and scenarios. In doing so, the goal is to pave the way for more effective and efficient implementation of OFDM-IM systems in diverse contexts.

Optimized Greedy Detection for OFDM-IM Systems

Recently, a new transmission method has been proposed for power-efficient wireless communication systems called Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM). This method offers high spectral efficiency with good error performance. The greedy detection (GD) scheme of subcarrier indices is often used to reduce the complexity of the OFDM-IM system in comparison to other relevant detectors. In this letter, an optimized greedy detection (OGD) scheme is proposed. The received subblock is divided into mini-subblocks to decrease the risk of error. The Total Symbol Error Probability (TSEP) is derived using a closed-form expression to evaluate the performance. Simulation and analytic results demonstrate the superiority of the proposed detector.

A joint denoising and deep learning detector for OFDM‐IM

AbstractOnly a subset of subcarriers are activated in orthogonal frequency division multiplexing‐index modulation (OFDM‐IM), which achieves higher energy efficiency and resists frequency offset. In the OFDM‐IM, the energy of the received signal is computed and then combined with pre‐processed signal to create the input of detection network. Inspired by image denoising technology, this study enhances the detection performance by denoising the pre‐processed data and improving the energy distribution in the OFDM‐IM system. First, considering that the noise reduction process of the pre‐processed signal can effectively mitigate the distortion by noise which affects the detection accuracy, this study proposes a two‐phase neural network termed as Deep‐Denoising‐IM through the combination of a noise reduction network and a deep learning detection method. Then, to better determine the position of the active carriers, a joint decision method of the denoised data and the received signal is designed as the IQ signal of the denoised data may change the quadrant of original signal distribution. In addition, the pre‐processed data sample has insufficient diversity. Considering that data enhancement can increase the noise of the signal samples, this study proposes a method to strengthen the silent carriers in the model training phase, which improves the generalization ability of the model and further enhances the denoising performance. Simulation results show that Deep‐Denoising‐IM outperforms the existing detectors in terms of mean square error (MSE) and bit error rate (BER) under the Rayleigh fading channel.

Peak‐to‐average power ratio of selective mapping technology involving a phase generation mechanism based on polar codes for orthogonal frequency division multiplexing with index modulation systems

AbstractIn this paper, a novel selective mapping (SLM) method is proposed for reducing the peak‐to‐average power ratio (PAPR) of orthogonal frequency division multiplexing with index modulation (OFDM‐IM) systems. In the proposed method, polar codes are used to construct the SLM phase generation mechanism. This systematic structural design is superior to conventional methods in which phases are randomly generated. Moreover, polar codes and Reed–Muller codes are selected to protect the input data of the OFDM‐IM system. The weight distribution of the Reed–Muller codes is then used to determine the location data of the active subcarriers in the OFDM‐IM system, and these data are used to determine the error correction capacity. Simulation results indicated that the PAPR improvement achieved using the proposed method is similar to that achieved with conventional SLM methods. Moreover, linear block codes are used to construct the active subcarrier selection and SLM phase generation mechanisms to ensure that both mechanisms have systematic structural designs.

A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems

In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits.

Coding Split and Adjustment to Defend OFDM-IM Against Jamming Attacks

Jamming is a simple but efficient attack method that challenges communications while traditional physical-layer defence solutions are limited. Recently, index modulation (IM) is proposed to enable index transmission in addition to data symbol transmission, which gains resistance against jamming but with limited efficacy. This letter proposes a coding split and adjustment (CSA) framework for low-density parity-check (LDPC) coding assisted orthogonal frequency division multiplexing with IM (OFDM-IM) to enhance its anti-jamming capability. CSA splits the traditionally single system code rate into an index code rate and a data code rate, each independently adjusted based on jamming impacts to error performance. Simulation results verify that OFDM-IM with CSA exhibits superior error performance over traditional OFDM-IM and OFDM in three investigated jamming scenarios. Moreover, this letter reveals that the CSA assisted OFDM-IM can still recover signals while OFDM-IM and OFDM completely fail under high jamming power.

A Modified Selective Mapping Technique for Peak-to-Average Power Ratio Reduction in Orthogonal Frequency Division Multiplexing with Index Modulation Systems

In this study, we propose a modified selective mapping (SLM) technique to reduce the Peak-to-Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) systems. The main reason for using Reed–Muller and Polar codes is to protect the information bits to be transmitted while providing error correction capability and improved PAPR performance to the transmitted signal. Although OFDM-IM technology is a popular communication transmission technology recently, one of its disadvantages is that the transmitted signal has a high PAPR. The proposed method uses the Hamming weight distribution of the specific order Reed–Muller code to create a corresponding lookup table to select the subcarriers that are active in the OFDM-IM system. Moreover, it can correct errors in the information used. The proposed method also uses Polar codes as a channel encoder of the OFDM-IM system to analyze its performance in improving the PAPR. The simulation results show that method can not only improve the PAPR performance of OFDM-IM systems but also provide OFDM-IM transmission-signal error correction capacity.

Broad Learning System-Based Detector for OFDM With Index Modulation

This letter presents a broad learning system (BLS) based orthogonal frequency division multiplexing with index modulation (OFDM-IM) detector called BLS-IM, which achieves bit-error-rate performance improvement with less training time. In BLS-IM, in order to help the network detect the index of the active subcarrier, the received data needs to be preprocessed into polar coordinates first. The processed data is then fed into the BLS network. In particular, the BLS is built in the form of a flat network where the initial signal bits are transferred among the feature nodes. At the same time, the structure is extended in a broad sense in terms of enhanced nodes. The proposed BLS-IM detector has an advantage in training time because it avoids the time-consuming training process caused by a large number of connection parameters in the layers. Simulation results demonstrate that BLS-IM is capable of achieving better detection performance with less training time than the existing algorithms.

Chaotic-based Orthogonal Frequency Division Multiplexing with Index Modulation

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), stands out among conventional communication technologies, as it uses the indices of the available transmit entities. Thanks to such an approach, it offers a novel method for the transmission of extra data bits. Recent years have seen a great interest in chaos-based communications. The spectrum-spreading signals used in chaotic signal modulation technologies are orthogonal to the existing mixed signals. This paper presents how well a non-coherent differential chaos shift keying communication system performs across an AWGN. Different types of detection methods are simulated, bit error rate and power spectral density are calculated and then compared with standard OFDM with index modulation. The results of simulations concerning the performance of a DCSK system, adding to the security of the proposed solution and offering a comparable bit error rate performance, are presented in the paper as well.

Y-Shaped Net-Based Signal Detection for OFDM-IM Systems

This letter presents the power of deep learning for signal detection in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. In this letter, we propose the Y-shaped net-based scheme with fully connected layers (Y-FC) and with bidirectional long short-term memory units (Y-BLSTM) to further optimize the data reception. In the Y-shaped scheme, the active indices and the constellation demapping are learned by two parallel sub-neural networks respectively, the output features are then concatenated and flattened to obtain binary bits. The performance is evaluated under various system parameters, such as modulation methods, number of hidden neural nodes and channel states. Simulation results show that compared with the data-driven signal detection with direct input-output, the proposed scheme achieves several dB of bit-error-rate performance improvement with almost the same running time.

Reactive jammer detection in OFDM with index modulation

Detection of jamming attacks is an important tool to improve the resource efficiency of jammer resilient communication networks. Detecting reactive jammers is especially difficult since the attacker is cognitive and focuses only on the used channels. Orthogonal frequency division multiplexing with index modulation (OFDM-IM) consists of active and passive subcarriers. Only active subcarriers carry modulated signals while passive subcarriers are left unused. In OFDM-IM systems, information bits are also dynamically embedded in the indices of these active subcarriers. As a result, remaining passive subcarriers cause instantaneously changing and unused holes in the spectrum that a reactive jammer cannot escape from attacking. In this paper, we propose an OFDM-IM-based detection scheme to improve the detection performance against reactive jammers. The proposed method exploits the dynamically changing empty OFDM-IM subcarriers to improve detection performance. A detection mechanism that is based on the variance of received signals is considered to identify the jammed subcarriers reliably and with low complexity. We assumed a destructive and elusive reactive jammer model that applies a zero-mean Gaussian jamming signal to the occupied channels. The performance of the variance detector is investigated analytically for OFDM-IM and OFDM-based systems under the given jammer model. The results showed that passive subcarriers of OFDM-IM inherently provide a better detection performance compared to the classical OFDM. Lastly, the analytical results are verified via simulations against both full-band and partial-band reactive jammers. Also, the effect of noise and the jamming power on the detection performance is investigated via extensive simulations.

A Hybrid PAPR Reduction Scheme in OFDM-IM Using Phase Rotation Factors and Dither Signals on Partial Sub-Carriers

As a multi-carrier modulation technique, a high peak-to-average power ratio (PAPR) is a common issue suffered by orthogonal frequency division multiplexing with index modulation (OFDM-IM) due to its system structure. High PAPR may cause signal distortion, which affects correct symbol transmission. This paper tries to inject dither signals to the inactive (idle) sub-carriers, which is a unique transmission structure of OFDM-IM, to reduce PAPR. Unlike the previous works, which utilize all idle sub-carriers, the proposed PAPR reduction scheme utilizes selected partial sub-carriers. This method performs well in terms of bit error rate (BER) performance and energy efficiency, which are obvious drawbacks of the previous PAPR reduction works due to the introduction of dither signals. In addition, in this paper, phase rotation factors are combined with the dither signals to compensate for the PAPR reduction performance degradation due to the insufficient use of partial idle sub-carriers. Moreover, an energy detection scheme is designed and proposed in this paper in order to distinguish the index of phase rotation factor used for transmission. It is shown by extensive simulation results that the proposed hybrid PAPR reduction scheme is able to implement an impressive PAPR reduction performance among existing dither signa-based schemes as well as classical distortion-less PAPR reduction schemes. In addition, the proposed method obtains better error performance and energy efficiency than that of the previous works. At the error probability , the proposed method can achieve around 5 dB gain compared to the conventional dither signal-based schemes

Iterative Hard Thresholding Algorithm-Based Detector for Compressed OFDM-IM Systems

A low-complexity iterative hard thresholding (IHT) algorithm-based detector is proposed for the compressed orthogonal frequency division multiplexing with index modulation (OFDM-IM) system. To improve recovery accuracy and reduce the number of iterations, detection is embedded into the iterations of the IHT algorithm, and the block energy information is used to identify subblocks that are more likely to be error-recovered. Compared with the existing methods for improving spectral efficiency, the new method does not expand the detection search space and not need extra pseudo-inverse calculations during iterations. Theoretical and simulation results show that the proposed scheme can considerably reduce computational complexity while improving spectral efficiency and preserving significant BER performance gain.

Coordinate Interleaved OFDM With Power Distribution Index Modulation

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), which transmits information bits via <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary constellation symbols and indices of the active subcarriers, is a promising OFDM-based multicarrier transmission scheme. Recently, several new schemes have been proposed by utilizing the flexibility of the OFDM-IM to meet the diverse needs of 5G networks. Coordinate interleaved OFDM-IM (CI-OFDM-IM) that conveys the real and imaginary part of the data symbols over different subcarriers and OFDM with power distribution IM (OFDM-PIM) that transmits the data symbols over high and low power subcarriers, are two OFDM-IM based schemes with additional diversity gain and improved bit error rate (BER) performance. In this letter, we propose a novel transmission scheme named as coordinate interleaved OFDM with power distribution IM (CI-OFDM-PIM), which applies coordinate interleaving and power distribution in subcarriers to achieve a higher diversity gain. The average bit error probability (ABEP) for the CI-OFDM-PIM is derived and the superior error performance of the proposed scheme over benchmarks are shown via computer simulations.

Rectangular Differential OFDM With Index Modulation Using Coordinate Interleaving

Differential subcarrier index modulation (DSIM) is an emerging OFDM with index modulation (OFDM-IM) technique, which does not require channel state information (CSI) at the receiver. However, the DSIM scheme has two drawbacks of lower spectral efficiency and lacking transmit diversity. In this letter, by combining rectangular differential coding and coordinate interleaving orthogonal design, a novel rectangular differential OFDM-IM using coordinate interleaving (CI-OFDM-RDIM) scheme is proposed. In this scheme, the dispersion matrix is projected to a dispersion vector that is transmitted in a single symbol interval, so that CI-OFDM-RDIM improves spectral efficiency compared with DSIM. Since the symbols in two adjacent differential groups are interleaved, the proposed scheme obtains diversity gain. Furthermore, owing to the orthogonality of its processing matrix, a low-complexity decoupled maximum likelihood (D-ML) detector is proposed. Theoretical performance analysis and simulation results show that CI-OFDM-RDIM outperforms DSIM in terms of the bit error rate (BER) performance.

Transformer-Based Detector for OFDM With Index Modulation

A deep learning (DL)-based detector utilizing the Transformer framework is proposed for orthogonal frequency-division multiplexing with index modulation (OFDM-IM) systems, termed as TransIM. Concretely, TransIM adopts a two-step detection method. First, the neural networks with the Transformer block as the core provide soft probabilities of different transmitted symbols. Then, conventional signal detection methods are performed based on those probabilities to make final decisions. This method is verified to improve system error performance significantly, albeit at the cost of slightly increased complexity. Simulation results indicate that the proposed TransIM detector fares better than existing DL-based ones regarding bit error rate (BER) performance.