Multicarrier Transmission Research Articles

A novel SLM scheme for peak-to-average power ratio reduction in WOLA-OFDM system

This paper addresses high peak-to-average power ratio (PAPR) issue in the recently invented weighted overlap and add-orthogonal frequency division multiplexing (WOLA-OFDM) system. The selective mapping (SLM), one of the most widely used PAPR reduction schemes in OFDM-based multicarrier transmission strategies, can be used to reduce the PAPR of WOLA-OFDM signals. However, the overlapping of symbol extensions in the WOLA-OFDM transmitter considerably deteriorates the performance of SLM. To overcome this problem, we have developed an efficient SLM scheme named dual symbol optimization-SLM (DSO-SLM) for the WOLA-OFDM system. In this new scheme, instead of reducing the PAPR of adjacent symbols separately as in conventional SLM, each symbol is evaluated together with its overlapping predecessor symbol while searching for the optimal transmission signal with minimized PAPR. With the usage of DSO procedure, it becomes possible to enhance the performance of conventional SLM in the WOLA-OFDM system.

Improving Performance of MC-CDMA Systems Using UTTCM Channel Coding

Over the past decade, personal communications have witnessed exponential growth, fueled by the increasing number of connected users and the diversity of transmitted data types. This expansion necessitates a boost in the transmission systems' capacity to accommodate higher user numbers and data rates, simultaneously striving to optimize cost and complexity. Consequently, future communication systems are pivoting towards multi-carrier spread spectrum techniques (MC-CDMA), capitalizing on the robustness of OFDM multi-carrier transmissions against multipath propagation and leveraging the flexibility of the code division multiple access (CDMA) technique. This study addresses data transmission quality-related concerns within an MC-CDMA system by implementing UTTCM error correction codes. These codes aim to enhance channel spectrum efficiency and mitigate error probability. Simulation results demonstrate that the proposed transmission scheme offers significant improvements in terms of bit error rate and signal-to-noise ratio, while maximizing the bandwidth shared among users. Additionally, the incorporation of such equalization techniques as zero forcing (ZF) and minimum mean square error (MMSE), ensures extensive compensation for the channel selectivity effect.

Evaluation of User-Centric Cell-Free Massive Multiple-Input Multiple-Output Networks Considering Realistic Channels and Frontend Nonlinear Distortion

Future 6G networks are expected to utilize Massive Multiple-Input Multiple-Output (M-MIMO) and follow a user-centric cell-free (UCCF) architecture. In a UCCF M-MIMO network, the user can be potentially served by multiple surrounding Radio Units (RUs) and Distributed Units (DUs) controlled and coordinated by a single virtualized Centralized Unit (CU). Moreover, in an M-MIMO network, each transmit frontend is equipped with a Power Amplifier (PA), typically with nonlinear characteristics, that can have a significant impact on the throughput achieved by network users. This work evaluates a UCCF M-MIMO network within an advanced system-level simulator considering multicarrier transmission, using Orthogonal Frequency-Division Multiplexing (OFDM), realistic signal-processing steps, e.g., per resource block scheduling, and a nonlinear radio frontend. Moreover, both idealistic independent and identically distributed (i.i.d.) Rayleigh and 3D ray-tracing-based radio channels are evaluated. The results show that under the realistic radio channel, the novel user-centric network architecture can lead to an almost uniform distribution of user throughput and improve the rate of the users characterized by the worst radio conditions by over 3 times in comparison to a classical, network-centric design. At the same time, the nonlinear characteristics of the PA can cause significant degradation of the UCCF M-MIMO network’s performance when operating close to its saturation power.

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.

Nonlinear Multicarrier Transmitter System With Signal Clipping: Measurement, Analysis, and Optimization

Nonlinear Multicarrier Transmitter System With Signal Clipping: Measurement, Analysis, and Optimization

Massive MIMO-OFDM Transmission Without Cellular Networks Using Frequency - Selective Fading Channels

Abstract: For cell-free massive multi-input multi-output (CF-m-MIMO) across frequency-selective fading channels, this system introduces and determines the effectiveness of the orthogonal frequency-division multiplexing (OFDM)-based multi-carrier transmission. The CF-m-MIMO-OFDM system can accommodate a substantial user base and is flexible enough to offer a range of data rates for usage in a variety of contexts. With its scalability and flexibility, the CF-m-MIMO-OFDM transmission network can serve a large number of users at variable data rates. It is proposed to beamform in the frequency-domain conjugate, to choose a pilot, and to allocate resources differently for each user. User-specific resource allocation, pilot selection, and frequency-domain conjugate beamforming are all suggested. The CF-m-MIMO-OFDM system can support a large number of users and can offer varying data rates to accommodate a wide range of applications.

Timing‐deviation and frequency‐offset estimations for multicarrier transmission in high mobility environments using deep neural network

SummaryThe multicarrier technology used in fourth‐generation (4G) and fifth‐generation (5G) communications is quite susceptible to multipath fading and Doppler frequency shift, which is more prominent in high mobility environments. Therefore, the accuracy of timing and frequency synchronization impacts the overall system performance significantly. Existing synchronization methods rely on the correlation of the preamble sequences and are, hence, vulnerable to severe multipath effect and Doppler effect. In this article, we propose a novel scheme leveraging deep neural network (DNN) to achieve high‐precision synchronization in high mobility environments. Concretely, a convolutional neural network (CNN) architecture is proposed to extract the hidden features of received signals for timing deviation estimation. In the following, a fully connected (FC) model is demonstrated to classify the optimal carrier frequency offset (CFO) estimate from several CFO candidates. The proposed synchronization scheme is assessed under extended vehicular A (EVA) channel with various Doppler frequency shifts. Simulation results corroborate that the proposed DNN‐based scheme achieves a significant performance gain over the conventional correlation methods, and the proposed timing deviation estimation scheme exhibits an excellent complexity reduction; wherefore, it is extremely promising for multicarrier transmission systems in high mobility environments.

Analysis of Optimum Technique for PAPR Reduction in UFMC System

Abstract: The fifth Generation of communication has to support many applications like the Internet of Everything (IoE) and Machine Type Communication (MTC). The proposed universal filtered multi-carrier (UFMC) technique is one of the best techniques for fifth-generation (5G) communication. UFMC is expected to achieve low latency, robustness against synchronization errors and frequency offset, short-packet burst support, and reduce out-of-band (OoB) radiation that leads to higher spectral efficiency. Although the UFMC system offers many advantages as mentioned before, being a multicarrier transmission technology, it suffers from a high peak-to-average power ratio (PAPR), which degrades the efficiency of the HighPower Amplifier (HPA) and makes the UFMC transmitter inefficient. Therefore, an optimum PAPR reduction technique to reduce the high PAPR of the UFMC system has to be proposed. The proposed technique is a hybrid technique that consists of a combination of Generalized Chirp-Like (GCL) precoding and Selective-Mapping techniques (SLM). A comparative analysis of the performance of Generalized Chirp-Like precoding methods, SLM, and hybrid methods are by CCDF of the PAPR and the bit error rate (BER) and simulation results show that proposed SLM based GCL UFMC outperform the conventional techniques

Performance of PAPR for Different Modulation Technique Using Cluster Scrambling Codeword Shifting Technique in F-OFDM Systems

Filtered-OFDM (F-OFDM) is one of the proposed 5G system candidates. In order to achieve service diversification, it must be able to support a large number of asynchronous subband transmissions. However, the transmitted signal in a multi-carrier transmission system with different subcarriers has a high peak-to-average power ratio (PAPR). Therefore, the main problem of F-OFDM systems is the high PAPR in the system, which leads to poor performance and excessive power consumption due to numerous distortions. This study introduces a technique based on codeword structure manipulation known as Cluster Scrambling Codeword (CSC) to achieve better reduction of PAPR with the evaluation of the performance of QAM and APSK modulation. This is a new formulation of the bit data sequence shifting approach that can reduce PAPR more effectively than the conventional scheme. Simulation results show that CSC with 256 QAM modulation scheme provides a PAPR reduction better than the conventional F-OFDM system.

Deep Learning Aided 5G Channel Estimation

Abstract: Wireless communications involves the transfer of voiceand data without a cable or wires. It uses orthogonal frequencydivision multiplexing, also known as a multicarrier transmission technique. In multiple input multiple output (MIMO) wireless communication (4G and 5G technologies), channel estimation is crucial. Multiple antennas are used at both the transmit and receive sides ofa MIMO system to increase spectral efficiency and reliability. In 5G channel estimation is performed to improve the accuracy of the received signal. Least-squares estimation is a cheap method with relatively large channel estimationerrors, but it is supported in this work by using a new channel estimation method that leverages deep learning. LS (least squares) and MMSE (minimum mean squared error) are two popular traditional approaches to channel estimation, but deep learning provides much more accurate results than previous channel estimation methods.

Robust Transmission using Efficient Adaptive Modulation and Coding in Modern OFDM Systems

Abstract: OFDM (Orthogonal Frequency Division Multiplexing) as a special multi-carrier transmission technology has good resistance to narrow-band interference and frequency selective fading ability. Using adaptive modulation and coding in an OFDM systems in comparison with traditional fixed modulation techniques, it becomes possible to take full advantage of spectrum resources enhancing bandwidth efficiency and system capacity making it suitable for the high-speed and reliable mobile communication systems in the future. In AMC (Adaptive Modulation and Coding) technique, modulation method, coding rate, and/or other signal transmission parameters are dynamically adapted to the channel conditions to increase the system performance in terms of Bit Error Rate (BER) and throughput (bps) in various conditions such as channel mismatch, Doppler spreads, fading, etc. The purpose of this paper is to investigate the effect of adaptive modulation and coding in an OFDM system in terms of bit error rate and SNR over fading communication channels. In this paper, we have considered fixed and adaptive modulation technique in an OFDM system over AWGN and RICEAN channel with convolutional and BCH coding. An OFDM system model is simulated in MATLAB programming environment to obtain the simulation result. From the comparative simulation result analysis in terms of BER v/s SNR, it can be concluded that Adaptive modulation with Convolutional coding over RICEAN channel significantly reduces bit error rate giving better trade-off between SNR and BER than all other options considered here.

Peak to average power ratio reduction in spectrally efficient FDM using repeated clipping and filtering

Multi-carrier transmission may be considered one of the important developments in wireless communications. Spectrally efficient frequency division multiplexing (SEFDM) is a promising multi-carrier modulation which can significantly improve utilization of spectral. The SEFDM has high peak to average power ratio (PAPR) like any multicarrier system. High PAPR reduces the random forest (RF) transmitter power amplifier efficiency, which minimize the use of this technique in limited power supply transmitters. In this work, a repeated clipping and filtering method is introduced to reduce the PAPR in SEFDM with minimum or no out of band radiation. The results of the simulated approach show that the PAPR of the SEFDM was reduced from 16.264 dB to 7.9146 dB with marginal degradation in system performance when the clipping ratio varied from 4 to 2.

Coordinate Interleaved High-Dimensional OFDM With Index Modulation

In this letter, we propose a novel multicarrier transmission scheme named as coordinate interleaved high-dimensional orthogonal frequency division multiplexing with index modulation (CI-HD-OFDM-IM). In each subblock of the proposed scheme, two HD symbols with the optimal rotation angles are combined by coordinate interleaving technique to obtain an additional diversity gain and improve bit error performance. The single HD symbol maximum likelihood (ML) detection is exploited in the receiver. The average bit error probability (ABEP) of the CI-HD-OFDM-IM in the frequency selective Rayleigh fading environment is derived. Simulation results show that the proposed scheme has significantly better error performance than the reference systems, and the derived ABEP is very accurate.

Passive Location for 5G OFDM Radiation Sources Based on Virtual Synthetic Aperture

Passive location technology has been greatly developed because of its low power consumption, long detection distance, good concealment, and strong anti-interference ability. Orthogonal frequency-division multiplexing (OFDM) is an efficient multi-carrier transmission technology, which is an important signal form of 5G communication. Researching passive locations for OFDM signals can realize the location of base stations, which is of great significance in the military. Space-borne passive location technology has a contradiction between wide coverage and high precision. Therefore, a single-satellite passive location algorithm for OFDM radiation sources based on the virtual synthetic aperture is proposed. The algorithm introduces virtual synthetic aperture technology, using antenna movement to accumulate data coherently over a long time period and synthesizing a long azimuth virtual aperture. In addition, it utilizes fast Fourier transform (FFT) to extract phase information at a specific frequency based on the multi-carrier modulation technology of the OFDM signal. Pilot technology of the communication system is used for phase compensation and noise reduction. Thus, the azimuth linear frequency modulation (LFM) signal containing the location information of the radiation source is obtained. The radiation source location can be obtained by range searching and azimuth focusing. Simulation results verify the effectiveness of the algorithm and show that the algorithm can realize high-precision and wide-coverage location for the OFDM radiation sources using a single antenna, turning the hardware structure into software to reduce the cost and complexity of the system.

Mitigating Clipping Distortion in Multicarrier Transmissions Using Tensor-Train Deep Neural Networks

Multicarrier transmissions, such as orthogonal frequency/chirp division multiplexing (OF/CDM), offer high spectral efficiency and low complexity equalization in multipath fading channels at the cost of high peak-to-average power ratio (PAPR). High peak powers can occur randomly and may drive the power amplifier (PA) into saturation, resulting in non-linear distortion. In this work, we propose a novel tensor-train (TT) deep neural network (DNN) architecture combined with soft clipping to reduce the PAPR to a deterministic level and minimize in-band distortion, while also satisfying spectral mask constraints. The proposed solution requires modifications only at the transmitter and there is no loss of spectral efficiency. Employing the TT decomposition allows for significant reduction in parameters. Results show that the proposed solution allows for significant reduction in PAPR with minimal performance loss. Furthermore, an upper bound for the PAPR is also derived which allows for the prediction of the required input power back off (IBO) without extensive simulations and trial-and-error.

Spectrum analysis of OFDM versus FBMC in 5G mobile communications

With the demand for mobile data traffic, multi-carrier transmission techniques are highly attractive for all-new wireless communication systems, which divides data into many components and sends each of these components via a different carrier signal. So far, orthogonal frequency division multiplexing (OFDM) and filter bank multi-carrier (FBMC) techniques are the dominant waveform contenders. A number of studies have been made and failed to give a complete comparison where they did not consider various conditions altogether. Therefore, this paper addresses a complete comparative analysis of OFDM and FBMC, performed based on spectral efficiency, modulation, demodulation, power spectral densities, and peak to average power ratio comparison, all simulated using Matlab and GNU’s not unix radio (GNU-radio) software.

Index and mode modulated orthogonal frequency division multiplexing with enhanced spectral efficiency

AbstractIndex modulation aided orthogonal frequency division multiplexing (OFDM‐IM) is a potential multicarrier transmission technique for wireless data transmission systems due to its attractive error performance and energy efficiency. However, it fails to cope with increasing demand of high data rate in upcoming mobile data services, mainly, due to the lower spectral efficiency. In this communication, an efficient transmission technique, called index and mode modulation OFDM, is proposed that delivers additional information through permutations of multiple modes and indexed bits patterns resulting in higher spectral efficiency. For the proposed technique, a low complexity log‐likelihood ratio detector with suitable algorithm is designed and its computational complexity has been analysed. The simulation results indicate improved performance of this newly proposed scheme in terms of spectral efficiency, bit error rate, as well as energy efficiency over other existing index modulated and multiple mode based OFDM schemes, while maintaining considerably low computational complexity in detection. That proclaims the scheme as a potential transmission technique to meet the data transmission challenges in 5G and beyond.

Study of Radio over Fiber Transmission with a Single Line in Ring Topology for Deployment of MIMO Antenna Access Points in a Cell-less Network

The massive growth of wireless traffic goes hand in hand with the deployment of advanced radio interfaces as well as network densification. This growth has a direct impact on the radio access architecture, which today is moving from centralized to distributed deployments through the use of a large number of access points (APs). This paper verifies the feasibility of deploying multiple APs in series on a single line in a ring topology in a cell-less network. On the one hand, this technique will further improve the communication capacity and flexibility of a Radio-over-Fiber (RoF) based mobile communication system and will reduce its construction cost. And on the other hand, this deployment topology is a solution to achieve a massive cell-free Multiple-Input Multiple-Output (MIMO) architecture and a cost-effective fronthaul solution. First, a passive optical add/drop multiplexer (OADM) is used to extract and add downlink and uplink signals from the remote access points of one kilometer. Then, a deployment model is developed with version 17 Optisystem software. The results obtained showed that the quadrature amplitude modulation (QAM) does not adapt to this multi-carrier transmission to deploy several AP in series on a single line. Thus, the performance degradation increases when the number of APs integrated on the line increases.

Highly focussed beampattern synthesis in FDA‐MIMO radar with multicarrier transmission

AbstractMulticarrier technology is widely used for improving the performance of beampattern synthesis in frequency diverse array multiple‐input and multiple‐output (FDA‐MIMO) Radar. However, how to use multicarrier technology to achieve highly focussed beampattern synthesis is still an open problem. To this end, the authors first establish the system model of FDA‐MIMO radar with multicarrier transmission and analyse the parameters influencing beampattern synthesis by Cramér–Rao lower bound derivation. It can be recognised that frequency increments and multicarrier distribution are key parameters hindering highly focussed beampattern synthesis. On top of the investigation, a simple yet effective Multidimensional Non‐linear Frequency Component, named multidimensional frequency components (MNFC), is proposed for forming a highly focussed beam. Specifically, MNFC is a two‐dimension frequency component for FDA‐MIMO radar. The first dimension is the frequency increment weighted by the Dynamic Taylor Window Function that effectively decouples the joint‐range‐angle beampattern. The second dimension is a non‐linear multicarrier weighted by Log with a Linear Coefficient for further optimising dot‐shaped beampatterns for target indication with high precision. Finally, numerical simulations and comparative experiments are performed to validate the superiority of the MNFC in beampattern synthesis.

Deep Learning for Channel Sensing and Hybrid Precoding in TDD Massive MIMO OFDM Systems

This paper proposes a deep learning approach to channel sensing and downlink hybrid beamforming for massive multiple-input multiple-output systems operating in the time division duplex mode and employing either single-carrier or multicarrier transmission. The conventional precoding design involves a two-step process of first estimating the high-dimensional channel, then designing the precoders based on such estimate. This two-step process is, however, not necessarily optimal. This paper shows that by using a learning approach to design the analog sensing and the hybrid downlink precoders directly from the received pilots without the intermediate high-dimensional channel estimation, the overall system performance can be significantly improved. Training a neural network to design the analog and digital precoders simultaneously is, however, difficult. Further, such an approach is not generalizable to systems with different number of users. In this paper, we develop a simplified and generalizable approach that learns the uplink sensing matrix and downlink analog precoder using a deep neural network that decomposes on a per-user basis, then designs the digital precoder based on the estimated low-dimensional equivalent channel. Numerical comparisons show that the proposed methodology results in significantly less training overhead and leads to an architecture that generalizes to various system settings.