Peak-to-average Power Ratio Reduction Algorithm Research Articles

Improved Hybrid Blind PAPR Reduction Algorithm for OFDM Systems

The ever growing demand for high data rate communication services resulted into the development of long-term evolution (LTE) technology. LTE uses orthogonal frequency division multiplexing (OFDM) as a transmission technology in its PHY layer for down-link (DL) communications. OFDM is spectrally efficient multicarrier modulation technique ideal for high data transmissions over highly time and frequency varying channels. However, the transmitted signal in OFDM can have high peak values in the time domain due to inverse fast Fourier transform (IFFT) operation. This creates high peak-to-average power ratio (PAPR) when compared to single carrier systems. PAPR drives the power amplifiers to saturation degrading its efficiency by consuming more power. In this paper a hybrid blind PAPR reduction algorithm for OFDM systems is proposed, which is a combination of distortion technique (Clipping) and distortionless technique (DFT spreading). The DFT spreading is done prior to clipping reducing significantly the probability of having higher peaks in the composite signal prior to transmission. Simulation results show that the proposed algorithm outperforms unprocessed conventional OFDM transmission by 9 dB. Comparison with existing blind algorithms shows 7 dB improvement at error rate 10 –3 and 3 dB improvement at error rate 10 –1 when operating in flat fading and doubly dispersive channels, respectively. Keywords: LTE Systems; OFDM; Peak to Average Power Ratio; DFT spreading; Signal to Noise Power Ratio;

PAPR Reduction of TDCS Based on Chirp Noise Sequence

This letter proposes a transform domain communication system (TDCS) based on chirp noise sequence to deal with its high peak to average power ratio (PAPR). The optimal chirp noise sequence is obtained by the selective mapping to improve PAPR reduction of the proposed TDCS waveform with low complexity. Compared with other PAPR reduction algorithms, such as magnitude weighting selection and complementary peak reducing signal, the proposed TDCS based on optimal chirp noise sequence has about 1.5 dB PAPR reduction gain without extra bit error rate loss.

A Novel Iterative-SLM Algorithm for PAPR Reduction in 5G Mobile Fronthaul Architecture

One of the main drawbacks of orthogonal frequency division multiplexing (OFDM) is the unpredictable significant increase in the peak-to-average power ratio (PAPR), due to the large dynamic range of the OFDM symbol waveforms. To overcome this problem, we propose a novel PAPR reduction technique in the transmitter DSP of a fiber mobile fronthaul network, named as iterative selective mapping (I-SLM). The proposed algorithm uses orthogonal phase vectors construction. Several alternative sets of the OFDM symbol are iteratively generated by deterministic sets of orthogonal phase vectors and the one which introduces the lowest peak power value is considered for transmission. Simulation results demonstrate a substantial PAPR reduction, comparing to the partial orthogonal selective mapping (POSLM), especially when the number of iterations increases in the presence of different variables, such as the number of OFDM subcarriers/frame and the modulation order.

Quasi-Optimal Tone Reservation PAPR Reduction Algorithm for Next Generation Broadcasting Systems: A Performance/Complexity/Latency Tradeoff With Testbed Implementation

High peak-to-average power ratio (PAPR) of the transmitted signal is a serious issue in multicarrier communication systems, such as second generation terrestrial digital video broadcasting (DVB-T2) systems. These large fluctuations prevent feeding the high power amplifier at an operating point near its non-linear saturation region thereby lowering its power efficiency. In recent years, tone reservation (TR) PAPR reduction techniques have been deeply studied and included in the DVB-T2 and the American digital video broadcasting (ATSC 3.0) specifications. It is based on a gradient iterative approach where, at each iteration, a predefined kernel is used to reduce one peak in time domain. In this paper, a novel TR PAPR reduction technique namely individual carrier allocation for multiple peaks (ICMPs) that is based on a new kernel signal is proposed. This algorithm, compatible with the DVB-T2 standard, offers better performance than the gradient-based DVB-T2 algorithm but suffers with increased complexity for higher modes of DVB-T2 and ATSC 3.0 as the number of required iterations is equal to the number of reserved tones. To overcome this issue, we propose an improved ICMP technique, called grouped ICMP defined with this new kernel. The main principle of this new algorithm consists in dividing the reserved tones into $G$ groups. This highly reduces the number of iterations, now equal to the number of groups, and thereby the latency. An in-depth performance analysis has been done by implementing our algorithm on a testbed platform with real power amplifiers. Both the simulation and experimental results demonstrated that the proposed PAPR reduction algorithm offers very good performance/complexity/latency tradeoff.

On the PTS Optimization Using the Firefly Algorithm for PAPR Reduction in OFDM Systems

ABSTRACTOrthogonal frequency division multiplexing (OFDM) is currently the most used technique for the high-data-rate transmission. However, OFDM systems have an inherent drawback in that the transmitted signals suffer from a high peak-to-average power ratio (PAPR). Partial transmit sequence (PTS) is generally applied to reduce the PAPR of an OFDM signal in wireless communication systems. Here, the search complexity for optimal phase vector increases exponentially with the number of phase vectors, since it involves an extensive random search over all the combinations of the allowed phase vectors. In this paper, a swarm intelligence algorithm for phase optimization based on the Firefly algorithm (FF) is applied to search the optimal combination of phase vectors. The proposed algorithm provides a superior trade-off between the improved PAPR performance and computational complexity when compared to the PTS scheme for a large number of sub-blocks. Simulation results show that the Firefly-algorithm-based PTS (FF-PTS) algorithm is an efficient method to achieve superior PAPR characteristics for OFDM signals when compared to conventional algorithms with very few parameters to adjust.

A Novel Joint PAPR Reduction Algorithm With Low Complexity Using LT Codes

In this letter, a low complexity joint peak to average power ratio (PAPR) reduction scheme is proposed for orthogonal frequency division multiplexing systems based on Luby transform (LT) codes. In the encoding process of LT codes, a predetermined threshold is introduced to control PAPR and reduce complexity. Moreover, we use the number of IFFT operations to model and formulate the theoretical algorithm complexity. Simulation results show that the proposed scheme can effectively reduce PAPR with a huge complexity reduction. Compared with the existing scheme, a maximum complexity reduction of 81% can be obtained concerning the total number of IFFT operations. Regarding the IFFT operations per degree, experimental curves are also consistent with the mathematical analysis.

PTS based on DisABC algorithm for PAPR reduction in OFDM systems

A novel discrete artificial bee colony algorithm-based partial transmit sequences (DisABC-PTS) scheme is proposed to reduce peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing signals. Compared to ABC algorithm-based PTS scheme (ABC-PTS) proposed previously, the DisABC-PTS scheme works directly in discrete space, which has a high computational efficiency. Simulation results indicate that DisABC-PTS scheme can obtain lower PAPR than existing PTS schemes and has a low computational complexity.

Improved Tone Reservation PAPR Reduction Algorithm in NC-OFDM/OQAM System

Non-continuous orthogonal frequency division multiplexing with offset quadrature amplitude modulation (NC-OFDM/OQAM) is often referred to overcome the issues associated with spectrum distribution. The corresponding peak to average power ratio (PAPR) emerged as a difficult task for the hardware implementation which seriously restricts the practicability of NC-OFDM/OQAM. To solve this problem, an improved PAPR reduction algorithm based on the tone reservation technique is proposed. According to the results of spectrum sensing, the bands are divided into two categories based on whether or not there are primary users (PU). Secondary users (SU) choose different sub-carrier numbers and amplitudes of the reserved sub-carriers in those bands separately. There by, SU get a substantial PAPR reduction while avoiding the interference to the PU and increasing the spectrum utilization efficiency. Theoretical analysis and simulation results show that the proposed algorithm supports a good PAPR reduction performance and efficient use of spectrum as well.

Hybrid STBC-PTS with enhanced artificial bee colony algorithm for PAPR reduction in MIMO-OFDM system

Peak-to-average power ratio (PAPR) is found to be a significant role in multiple input, multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Partial transmit sequence (PTS) is one of the effective methods to reduce the PAPR in OFDM signals. However, finding an optimum phase factor in PTS scheme is considered to be a significant issue. In order to overcome this problem, we use orthogonal initialization method to identify the initial population for enhanced Artificial Bee Colony (ABC) algorithm. In addition, PTS technique uses exhaustive search method to find the better combination of phase factors. This would also increase the computational complexity of the system. In order to overcome this issue, a newly suboptimal method is also used in the enhanced ABC algorithm. Finally, we have combined the space time block coding (STBC) and the PTS based enhanced ABC algorithm to reduce the PAPR and bit error rate (BER). The orthogonal initialization method and suboptimal method in ABC algorithm greatly reduces the PAPR and BER in the OFDM system. MATLAB software is used to run this simulation.

A Multi-Carrier $M$ -Ary Differential Chaos Shift Keying System With Low PAPR

An improved multi-carrier $M$ -ary differential chaos shift keying (MM-DCSK) system is presented, where differential modulation and demodulation are carried out across multiple carriers in the frequency domain, so channel estimation is not needed. For one data frame transmission, only one non-information-bearing reference sub-carrier signal is required, and the reference of each information-bearing sub-carrier is its previous sub-carrier signal, thus high energy efficiency is attained. If channel response changes during a frame period, the time diversity is achieved. In addition, the peak-to-average power ratio (PAPR) is considered, and it is found that adjacent symbols with a large Euclidean distance achieve a low PAPR. Accordingly, a low-complexity PAPR reduction algorithm is proposed based on symbol-interleaving with only one inverse fast Fourier transform processor. The simulation results demonstrate that the system with the proposed algorithm dramatically reduces the PAPR. Analytical bit-error-rate expressions are derived and verified by simulations over additive white Gaussian noise and multi-path fading channels.

Improved Response of Genetic Simulated Annealing Algorithm for PAPR Reduction in OFDM System using PTS Technique

Objectives: Orthogonal Frequency Division Multiplexing (OFDM) which is a wide band digital modulation technique has high peak to average power ratio. An advanced Genetic Simulated Annealing Algorithm (GSAA) is here proposed to reduce Peak to Average Power Ratio (PAPR). Statistical Analysis: A hybrid of Genetic and Simulated Annealing Algorithms (SAA) is implemented with two different channels Additive White Gaussian Noise (AWGN) and Rayleigh Fading which improved the performance of PAPR. Compensation of effects as well as reduction in PAPR is achieved. Findings: Though the known method GSAA reduces PAPR by avoiding the computational complexity, local maxima, yet the resultant PAPR is between 5dB and 6dB. The proposed method, proceeds further by incorporating AWGN and Rayleigh Fading channels in the hybrid of GSAA. Implementing the hybrid algorithm with the two proposed channels reduces PAPR between 3dB and 4dB. Hence this method proves to be effective in reduction of PAPR.

A Modified Shuffled Frog Leaping Algorithm for PAPR Reduction in OFDM Systems

Significant reduction of the peak-to-average power ratio (PAPR) is an implementation challenge in orthogonal frequency division multiplexing (OFDM) systems. One way to reduce PAPR is to apply a set of selected partial transmission sequence (PTS) to the transmit signals. However, PTS selection is a highly complex NP-hard problem and the computational complexity is very high when a large number of subcarriers are used in the OFDM system. In this paper, we propose a new heuristic PTS selection method, the modified chaos clonal shuffled frog leaping algorithm (MCCSFLA). MCCSFLA is inspired by natural clonal selection of a frog colony, it is based on the chaos theory. We also analyze MCCSFLA using the Markov chain theory and prove that the algorithm can converge to the global optimum. Simulation results show that the proposed algorithm achieves better PAPR reduction than using others genetic, quantum evolutionary and selective mapping algorithms. Furthermore, the proposed algorithm converges faster than the genetic and quantum evolutionary algorithms.

A novel TS-EIA-PTS PAPR reduction algorithm for optical OFDM systems

Because the partial transmit sequence (PTS) peak-to-average power ratio (PAPR) reduction technology for optical orthogonal frequency division multiplexing (O-OFDM) systems has higher computational complexity, a novel two-stage enhanced-iterative-algorithm PTS (TS-EIA-PTS) PAPR reduction algorithm with lower computational complexity is proposed in this paper. The simulation results show that the proposed TS-EIA-PTS PAPR reduction algorithm can reduce the computational complexity by 18.47% in the condition of the original signal sequence partitioned into 4 sub-blocks at the remaining stage of n-d=5. Furthermore, it has almost the same PAPR reduction performance and the same bit error rate (BER) performance as the EIA-PTS algorithm, and with the increase of the subcarrier number, the computational complexity can be further reduced. As a result, the proposed TS-EIA-PTS PAPR reduction algorithm is more suitable for the practical O-OFDM systems.

Jointly RVM Based Channel Estimation and PAPR Reduction Using Modified Tabu Search Algorithm in Power Line Communication Systems

Power line communication (PLC) channel as a transmitting medium for high speed data communication based on orthogonal frequency division multiplexing (OFDM) is demonstrated. High peak to average power ratio (PAPR) in OFDM, frequency selectivity and impulsive noise in PLC channel are the most important challenges that should be taken into consideration. In this paper, a new SFTS algorithm with low searching complexity is applied to popular PTS method to reduce the PAPR parameter in which there is no need to send any side information. Also, the robust relevance vector machine based channel estimation is jointly used with the PAPR reduction. Our proposed channel estimation algorithm is based on sparse Bayesian learning with a sigmoid function as a new multi-kernel with proper initial hyper-parameters. It improves BER and MSE performances in PLC channels contaminated by impulsive noises. Proposed jointly PAPR reduction and channel estimation without any side information achieves good results comparing to parallel Tabu search PAPR reduction and Huang channel estimation algorithms. It is shown that in our proposed PAPR reduction algorithm about 1.5 and 4.5 dB improvements are obtained with considerable searching complexity reduction comparing to the parallel Tabu search method and conventional OFDM, respectively. Also, about 2 dB improvement achieved in SNIR for BER = 10?3 of proposed channel estimation algorithm comparing to LS method and 5 dB enhancement in MSE comparing to Huang method.

SLM and Clipping Joint Algorithm for PAPR Reduction in OFDM System

As one of the most appealing techniques, selective mapping (SLM) provides an efiective solution for Peakto-average Power Ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing (OFDM) systems, however, results in large computational complexity simultaneously. As compared to SLM, clipping provides a more simple way towards a better PAPR performance, whereas results in degradation of the Bit Error Rate (BER) performance. In this paper, we proposed a joint algorithm called SLM and Quantization Clipping (SLM-QC) scheme, which combined the conventional SLM technology with a modifled quantization clipping scheme. The proposed scheme achieves a better exploitation of advantages brought about by each technique alone, with the tradeofi between the PAPR performance and the BER performance being well balanced.

PTS Method with Combined Partitioning Schemes for Improved PAPR Reduction in OFDM System

Although orthogonal frequency division multiplexing (OFDM) is an efficient wireless transmission system, it suffers from a crucial drawback namely high peak-to-average power ratio (PAPR) that limits transmitter power efficiency. Thus, different PAPR reduction algorithms have been introduced. Partial transmit sequence (PTS) is the most attractive solution which can provide good PAPR reduction performance without distortion. In any PTS system, partitioning of the OFDM frame into disjoint sub-blocks is a significant step. Out of the existing partitioning techniques, adjacent partitioning (AP) is a fairly simple partitioning scheme achieving efficient PAPR reduction performance. This paper presents an enhanced PTS approach that combines two PTS partitioning schemes, adjacent and interleaved partitioning, in order to effectively reduce the PAPR of OFDM systems. With an aim of determining the effects of length variability of adjacent partitions, we performed an investigation into the performances of a variable length adjacent partitioning (VL-AP) and fixed length adjacent partitioning in comparison with the enhanced PTS scheme.

New method for PAPR reduction based on union strategy in OFDM system

Because of the high Peak to Average Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) system, a union algorithm for PAPR reduction, combined with modified Active Constellation Extension Smart Gradient-Project(ACE-SGP) algorithm and adaptive clipping algorithm, is proposed in this paper. First of all, an adaptive strategy is used to control the size of clipping level A. Secondly, a novel step factor µ is adopted to complete iterative computations in order to increase the convergence speed greatly. Simulation results show that the modified algorithm has reduced the PAPR and improved the convergence speed significantly without side information and any processing at the receiver end.

Optimal phase searching of PTS using modified genetic algorithm for PAPR reduction in OFDM systems

In this paper, a novel genetic algorithm assisted partial transmit sequence (NGA-PTS) is proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM). However, the search complexity of the optimum PTS (OPTS) scheme is too large for the typical number of sub-blocks. Therefore, some artificial intelligence methods, such as genetic algorithm technique, and particle swarm optimization, are introduced to reduce the complexity. As traditional GA-PTS (TGA-PTS) technique risks finding a suboptimal solution, how to avoid this disadvantage of TGA-PTS is an interest topic. In order to obtain a better suboptimal solution, a phase factor optimal pair technique and an abandon/introduction new chromosome technique are proposed in GA here. Simulation results show that the proposed scheme achieves a significant improvement over the TGA-PTS scheme in PAPR. Furthermore, by use of the inherent diversity of constellation for each OFDM candidate, in the receiver part, the proposed scheme enables data recovery without any side information. Simulation results show the efficiency of the proposed scheme.

PAPR Analysis and Mitigation Algorithms for Beamforming MIMO OFDM Systems

Beamforming (or precoding) techniques have been widely adopted in modern MIMO OFDM systems. Using beamforming can significantly improve the receive SNR of OFDM systems. However, the combination of transmit signals after beamforming deteriorates the peak-to-average power ratio (PAPR), which has long been considered a major issue of OFDM systems. High PAPR not only complicates the design of the power amplifier, but also increases power consumption. In this paper, we theoretically analyze the PAPR performance of MIMO OFDM systems that adopt either one of the two popular beamforming schemes, i.e. MRT (maximum ratio transmission) and EGT (equal gain transmission). The analysis considers different numbers of channel taps after sampling. The results may provide important reference for practical designs when evaluating the required power amplifiers and power consumption. Moreover, the theoretical results show that MRT OFDM systems generally perform much worse than EGT OFDM systems in terms of PAPR. Furthermore, motivated from the derived results, PAPR reduction algorithms are proposed for both MRT OFDM and EGT OFDM systems. It is worth to mention that for MRT OFDM systems, the proposed algorithm can improve both PAPR and bit error rate; for EGT OFDM systems, the proposed algorithm improves PAPR while it only slightly degrades bit error rate.

A Low-Complexity Compressive Sensing Algorithm for PAPR Reduction

One of the major challenges in orthogonal frequency division multiplexing system is its high peak-to-average-power ratio (PAPR). Among the existing PAPR reduction technologies, clipping is the most often used one due to its simplicity of implementation. But it induces signal distortion. In this paper, we propose a new PAPR reduction method which introduces compressive sensing theory to help the clipping and signal recovery processes. Our method has superior symbol-error-rate (SER) performance compared with traditional clipping, and at the same time has better PAPR reduction performance compared with traditional tone reservation based algorithms. What is more, different from the existing high-complexity compressive sensing based scheme which tries to solve an optimization problem, the proposed algorithm uses orthogonal matching pursuit scheme to recover the distorted signals, thereby it significantly reduces the computational complexity with the same PAPR reduction efficiency. Simulation results show that our proposed scheme can achieve dramatic PAPR reduction with only about $$10\,\%$$ 10 % of the existing method, while still keeps good SER performance.