Orthogonal Frequency Division Multiplexing Peak-to-average Power Ratio Reduction Research Articles

Channel estimation and PAPR reduction in OFDM based on dual layers-superimposed training

Superimposed Training (ST) is one of the most appealing channel estimation techniques for Orthogonal Frequency Division Multiplexing (OFDM), to be possibly exploited in 6G. The data and pilot symbols are sharing the same time and frequency resources, and hence, the overhead is significantly reduced. Moreover, the superimposed pilots can be also used for the reduction of the Peak-to-Average Power Ratio (PAPR). However, a joint channel estimation and PAPR reduction procedure has not been addressed yet. In this work, a novel scheme denoted as Dual Layers-Superimposed Training (DL-ST) is proposed for this joint purpose. The Training Sequence (TS) of the first layer is targeted to perform channel estimation, while the TS of a second layer is designed for PAPR reduction and it is made transparent to the first one. Both layers can be independently processed, which implies a reduced complexity. To verify the performance of the proposed technique, the analytical expression of the channel estimation Mean Squared Error (MSE) is derived. Finally, several numerical results further illustrate the performance of the proposal, showing how the MSE and achievable rate are improved while significant PAPR reductions are attained with negligible complexity.

A LOW-COMPLEXITY PTS TECHNIQUE–BASED IMPROVED PSO ALGORITHM FOR PAPR REDUCTION IN OFDM SYSTEMS

Partial transmit sequence (PTS) is a potent and distortionless scheme frequently used to lower the high peak-to-average power ratio (PAPR) levels in orthogonal frequency division multiplexing (OFDM) signaling. Although this method effectively reduces the PAPR, its main limitation is the exponential growth in the computational expense caused by the exhaustive search for the optimal complex of rotation factors. This work proposes a suboptimal PTS scheme based on an improved particle swarm optimization (PSO) algorithm. The latter exploits heuristics to find the best-matched weighting factors complex in fewer computations. A comparison against existing techniques ascertains the superior efficiency of the proposed scheme in terms of PAPR mitigation and computational burden.

PSO-DBNet for Peak-to-Average Power Ratio Reduction Using Deep Belief Network

Data transmission through a wireless network has faced various signal problems in the past decades. The orthogonal frequency division multiplexing (OFDM) technique is widely accepted in multiple data transfer patterns at various frequency bands. A recent wireless communication network uses OFDM in long-term evolution (LTE) and 5G, among others. The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network. This transmission loss is called peak-to-average power ratio (PAPR). This wireless signal distortion can be reduced using various techniques. This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication. Partial transmit sequence (PTS) helps in the fast transfer of data in wireless LTE. PTS is merged with deep belief neural network (DBNet) for the efficient processing of signals in wireless 5G networks. Result indicates that the proposed system outperforms other existing techniques. Therefore, PAPR reduction in OFDM by DBNet is optimized with the help of an evolutionary algorithm called particle swarm optimization. Hence, the specified design supports in improving the proposed PAPR reduction architecture.

LADMM-Based PAPR-Aware Precoding for Massive MIMO-OFDM Downlink Systems

We tackle the peak to average power ratio (PAPR) reduction of an orthogonal frequency division multiplexing (OFDM)-based massive multi-user (MU) multiple-input multiple-output (MIMO) downlink systems in this paper. Utilizing the redundant degree of freedom (DOF) provided by a large number of antennas equipped at the base station, we first formulate OFDM modulation, MU precoding, and PAPR reduction into a non-convex optimization problem. By using the linearized alternating direction method of multipliers (LADMM), we directly address the non-convex PAPR-aware precoding problem without any relaxation in terms of PAPR and multi-user interference (MUI), which is completely different from the existing convex optimization methods based on relaxations. At the same time, the paper is also the first work to directly solve the non-convex PAPR-aware precoding optimization. The experimental results demonstrate that the LADMM method gets the comparable PAPR reduction and symbol error rate (SER), faster convergence, and lower complexity than the existing relaxed methods.

OFDM and MIMO wireless communication performance measurement using enhanced selective mapping based partial transmit sequences

The great spectral efficiency to mitigate multipath fading of OFDM (orthogonal frequency division multiplexing) made more accepted for broadband communication systems with some drawbacks such as high PAPR (Peak-to-Average Power Ratio), ISI (Inter-Symbol Interference) and ICI (Interiv Carrier Interference). High PAPR forces the operations of the HPA amplifier to work beyond its linear region causing in-band distortion as well as out-band noise and are overcome by using an amplifier with a large dynamic range. In this method, OFDM symbols are partitioned into multiple disjoint sub-blocks which are independently rotated in phase by optimum phase weighting factors. The resultant OFDM signal has less PAPR when compared to that of original OFDM signal in wireless communication. To minimize computational complexity, a modified PTS technique is proposed to enhance PAPR reduction and power amplifier efficiency in OFDM and MIMO (multiple inputs, multiple outputs)-OFDM methods through Selective Mapping based PTS (SMPTS) method combined with PAPR reduction methods.

OFDM PAPR Reduction via Time-Domain Scattered Sampling and Hybrid Batch Training of Synchronous Neural Networks

Peak-to-average power ratio (PAPR) reduction in multiplexed signals in orthogonal frequency division multiplexing (OFDM) systems has been a long-standing critical issue. Clipping and filtering (CF) techniques offer good performance in terms of PAPR reduction at the expense of a relatively high computational cost that is inherent in the repeated application of fast Fourier transform (FFT) operations. The ever-increasing demand for low-latency operation calls for the development of low-complexity novel solutions to the PAPR problem. To address this issue while providing an enhanced PAPR reduction performance, we propose a synchronous neural network (NN)-based solution to achieve PAPR reduction performance exceeding the limits of conventional CF schemes with lower computational complexity. The proposed scheme trains a neural network module using hybrid collections of samples from multiple OFDM symbols to arrive at a signal mapping with desirable characteristics. The benchmark NN-based approach provides a comparable performance to conventional CF. However, it can underfit or overfit due to its asynchronous nature which leads to increased out-of-band (OoB) radiations, and deteriorating bit error rate (BER) performance for high-order modulations. Simulations’ results demonstrate the effectiveness of the proposed scheme in terms of the achieved cubic metric (CM), BER, and OoB emissions.

Utilization of Compressed Sampling for PAPR Reduction in OFDM IEEE-802.11a System

Being spectrally efficient, easily implemented, and highly immune to selective channel imperfections and multipath fading, the Orthogonal Frequency Division Multiplexing (OFDM) can provide a sufficiently robust and high data rate modulation technique for emerging wired and wireless telecommunication applications. However, a major drawback of OFDM that is represented by its high Peak-to-Average Power Ratio (PAPR) of the transmitted signal, which leads to degrade the system’s transmission accuracy. In this paper, a Compressed Sampling (CS) based approach is considered for reducing the PAPR without lowering its transmission capacity or affecting its Bit Error Rate (BER) performance. The proposed scheme adds a sampling stage after the IFFT block in the transmitter side, that is compressively represents the transmitted signal by fewer symbols that is transmitted instead of the original signal. At the receiver side, the received compressively sampled signal is then recovered before the FFT block by following the Basis Pursuit (𝓵1–norm) algorithm. The proposed scheme shows an enhanced PAPR and BER performances while preserving the rest of the system performance aspects.

An approach to PAPR Reduction in OFDM using Goppa codes

Orthogonal frequency division multiplexing (OFDM) is a widely used modulation and multiplexing technology applied in many telecommunications standards due to its spectral efficiency and robustness against multipath fading. The multicarrier aspect of OFDM signal is characterized by high peak-to-average power ratio (PAPR), which renders the power amplifier (PA) inefficient and causes distortion in the transmitted signal. Several techniques to overcome and reduce PAPR such as signal distortion, signal scrambling, coding etc. are proposed and implemented on multipath fading channels. Coding methods does not affect system complexity as forward error correction is an inherent block in any digital communication system. The frequency diversity benefits of OFDM is not utilized well unless channel coding is used. Several codes like Hamming, Golay, BCH, RS, Reed Muller etc. have been investigated so far. Goppa codes were needed to be explored in OFDM systems. In this paper, its ability to reduce the peak power is studied for conventional OFDM signal. These codes are used in computer and telecommunication based applications owing to its useful properties required for cryptography. The PAPR reduction of Goppa coded OFDM (GOFDM) is found to be satisfactory for higher order constellation mapping of binary information. A look up table can also be created to select Goppa code words on the basis of a desired threshold of PAPR in dB. A mathematical analysis of the relationship of input data and its PAPR is also executed and certain conclusions are drawn as shown in the lemmas. But coding methods solely cannot achieve substantial PAPR reduction and therefore most of the literature on PAPR reduction methods have combined coding with other techniques. In this paper, G-OFDM is extended to a hybrid method of constant amplitude modulated (CAM)-G-OFDM to completely mitigate the PAPR problem. But it is achieved at the cost of transmitter and receiver complexity and performance parameters like bit error rate (BER), dependency on modulation index etc. which can be taken care of by making some amendments in the system design.

Application Framework Development for Algorithm Design of PAPR Reduction in OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is a well-built candidate for Physical Layer of 5G Communications as like it was there in 3G and 4G. With many advantages OFDM has some limitations like synchronization, Peak to Average Power Ratio (PAPR) etc. PAPR in OFDM remained the hot topic in PHY design of modern wireless communication systems since decades. Researchers are working to solve this problem with various approaches. Being one of the problem solvers team we realized that for a new researcher major effort goes into development of framework rather than actual PAPR algorithm. With this paper we tried to solve this issue by designing a simplified framework for developing, testing and measurement of PAPR of OFDM in Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) Platform. LabVIEW is a cutting edge, state of the art graphical programming environment which makes programming more simplified by adapting icons and connectors instead of text instructions, which makes computer programming language least complex, so that one can focus more on algorithm design rather than solving syntactical issues of the programming language. There are numerous applications of LabVIEW platform such as Instrumentation, image processing, digital signal processing, digital communication and many more. We have used core programming, signal processing and digital communication modules of LabVIEW for this research work. This paper has three sections, in section one, we explained need of framework, in second section we have explained detailed explanation of framework and its deployment and in the third section result and conclusion has been described..

PAPR reduction in OFDM using scaled particle swarm optimisation based partial transmit sequence technique

Partial transmit sequence (PTS) is one of the effective techniques for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. PTS technique has some issues such as higher computational complexity due to its exhaustive searching of optimal phase factors. In order to overcome this drawback, a scaled particle swarm optimisation algorithm is applied to PTS technique to find the optimal phase factors for reducing the PAPR at a faster convergence rate and lower computational complexity. A scaling factor has been introduced in the velocity updating equation of conventional particle swarm optimisation (PSO) to increase the inertia weight and velocity of the particle, thereby providing faster convergence to the optimum value as well as reducing PAPR effectively. From the simulation results obtained, it can be observed that the proposed scaled PSO-PTS algorithm reduces PAPR effectively and is most suitable for applications with the 64-QAM modulation scheme.

Spectrum Efficient DSI-Based OFDM PAPR Reduction by Subcarrier Group Modulation

High peak-to-average power ratio (PAPR) is a long-standing problem of orthogonal frequency division multiplexing (OFDM) system. Although there have been a plethora of proposals presented to date, most of the proposals sacrifice spectral efficiency to attain low PAPR. In this paper, a concept of subcarrier group modulation (SGM) is proposed to transform those spectrum inefficient schemes into spectrum efficient ones. The SGM scheme groups available subcarriers, and assigns one extra bit to each group depending on one of two different sets of constellation, thereby freeing some subcarriers for PAPR reduction. At the receiver, the constellation set used in a particular group is determined by the maximum-likelihood detection. The SGM scheme can be integrated to different PAPR reduction schemes. In this paper, it is integrated with the dummy sequence insertion (DSI) scheme. The DSI with SGM can attain the same spectral efficiency as the conventional OFDM does. Through simulations, it is found that it can achieve PAPR almost similar to that the conventional DSI scheme does without degrading BER performance significantly over both additive white Gaussian noise and Rayleigh fading channels. In addition to the PAPR reduction application, the proposed scheme can be used to improve throughput of any conventional OFDM systems.

Chaotic reconfigurable ZCMT precoder for OFDM data encryption and PAPR reduction

A secure orthogonal frequency division multiplexing (OFDM) transmission scheme precoded by chaotic Zadoff–Chu matrix transform (ZCMT) is proposed and demonstrated. It is proved that the reconfigurable ZCMT matrices after row/column permutations can be applied as an alternative precoder for peak-to-average power ratio (PAPR) reduction. The permutations and the reconfigurable parameters in ZCMT matrix are generated by a hyper digital chaos, in which a huge key space of ∼10800 is created for physical-layer OFDM data encryption. An encrypted data transmission of 8.9 Gb/s optical OFDM signals is successfully demonstrated over 20 km standard single-mode fiber (SSMF) for 16-QAM. The BER performance of the encrypted signals is improved by ∼2 dB (BER@10−3), which is mainly attributed to the effective reduction of PAPR via chaotic ZCMT precoding. Moreover, the chaotic ZCMT precoding scheme requires no sideband information, thus the spectrum efficiency is enhanced during transmission.

Low-Complexity Null Subcarrier-Assisted OFDM PAPR Reduction With Improved BER

In this letter, we propose a low complex data-null subcarrier switching-based peak-to-average power ratio (PAPR) reduction scheme for the orthogonal frequency division multiplexing (OFDM) systems, which provides improved bit error rate. We perform the switching between the data and null subcarriers in such a way that distance between any two switched-null subcarriers remains constant. This method can achieve up to 3 dB signal-to-noise ratio gain and shed the system complexity by more than 98% of the conventional systems, with a slight compromise of the PAPR reduction capability.

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM.

A Hybrid SLM Technique for PAPR Reduction in OFDM

With the advancement in age and its growing demands, there has been rapid growth in the field of communications. Multicarrier modulation is an attractive technique for fourth generation wireless communication. Orthogonal Frequency Division Multiplexing (OFDM) is one of the efficient multicarrier transmission schemes. OFDM consist of large number of independent sub carriers, as a result of which the amplitude of such a signal can have high peak values. The main drawback of OFDM system is that it suffers from high Peak to Average Power Ratio (PAPR). Due to high PAPR there is inefficient use of high power amplifier and this could limit transmission efficiency. Different technique can be used to reduce this PAPR; from that SLM is one of the efficient techniques. But the computational complexity and the transmission of side information are the concern problem in SLM. There for this paper, proposes a new SLM technique to reduce these drawbacks. As compared to the Conventional SLM method, the proposed Hybrid method provides less computational complexity and reduces the PAPR without any side information.

Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

Orthogonal frequency division multiplexing (OFDM) has been adopted as a standard for many modern wireless applications requiring high data rate due to bandwidth efficiency, resistance to frequency selective fading and simple digital realization using IFFT/FFT operations. However, physical implementation of the OFDM system suffers from several difficulties. One of the major limitations of OFDM is that it suffers from high peak-to-average power ratio (PAPR), which results in inter-carrier interference (ICI), high out-ofband radiation, and degradation of bit error rate performance. In this paper, different OFDM PAPR reduction techniques are reviewed and analyzed based on their computational complexity, bandwidth requirement and error performance.

Improved Clipping Technique for PAPR Reduction in OFDM

Multicarrier modulation technique also known as Orthogonal Frequency Division Multiplexing (OFDM) is considered to be the most rapidly growing technique for 4th Generation wireless communication system. Due to its high speed data rate and its ability of multipath fading channel robustness. OFDM becomes an attractive technique and it is widely adopted in many wireless communications system. OFDM signal carries its major drawback of high Peak to Average Power Ratio (PAPR) problem. Out of band radiation and in band distortion produced due to its high PAPR. Mobile phone communication suffer severe drawback during its amplification. When OFDM employed a non linear Power Amplifier (PA), it produces the fluctuation in amplitude of OFDM signal. This paper discusses the method to overcome PAPR in terms of its performance by using improved clipping technique for PAPR reduction. This method is easy to implement and reduces the amount of PAPR by clipping the peak of the maximum power signal. We present an improved method for PARR reduction for reducing peak magnitude of OFDM signal. This scheme simultaneously minimizes the peak magnitude of PAPR in OFDM signal.

PTS and Companding Transform for PAPR Reduction in OFDM

A combined model of Partial Transmit Sequence (PTS) and a Companding Transform is proposed to reduce Peak-toAverage Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM). Simulation results demonstrate that the proposed scheme can substantially offer better PAPR reduction and BER performance.

A Selected Peak Based TR Approach for OFDM PAPR Reduction

A high Peak-to-Average Power Ratio (PAPR) can lead to nonlinear distortion and low efficiency in Orthogonal Frequency-Division Multiplexing(OFDM) system. The approach of tone reservation (TR) designs peak-cancelling signal on reserved sub-carriers for peak cancellation and PAPR reduction. Aiming at reducing the computation of TR, this paper presents a new TR approach basing on selected peak. To narrow the search space of peak-cancelling signal, we calculate the maximum peak range of peak-canceling signal according to the relationship between peak value and threshold of power amplifier. Further, we propose the strategy to search the optimal peak-canceling signal which can eliminate the most of ultra-limit peaks. Simulation results show that the selected peak based TR approach can reduce computation effectively with preferable PAPR reduction.

A New Peak Clipping Algorithm for PAPR Reduction in OFDM

The peak-to-average-power ratio (PAPR) is one of the major problems of Orthogonal Frequency Division Multiplexing (OFDM) systems. Various PAPR reduction techniques have been given in the past. Among these techniques, the clipping technique has been widely adopted as a practical scheme because of its low computational complexity and simplicity in implementation, while the pre-coding technique is known to provide good PAPR reduction with improved bit error rate (BER) performance. In this paper, a combination of clipping and pre-coding is proposed to reduce PAPR with almost same BER performance as given by individual pre-coding technique. The proposed technique gives good result because the clipping noise of combined scheme would be less than that of single clipping. Also the clipping used in this paper is not hard as used in conventional clipping. A new clipping algorithm is proposed which is based on averaging of high amplitude samples. In addition, an another pulse shape called modified Bartlett Hanning (MBH) is proposed to generate pre-coding matrix and its performance is compared with square root raised cosine (SQRC) pulse shape.dB.