A low-complexity modified SLM with new phase sequences for PAPR reduction in OFDM system

Orthogonal frequency division multiplexing (OFDM) system has high spectral efficiency and immunity to frequency selective fading channel. So, it has been widely used in modern wireless communication systems. However, the major drawback of OFDM system is the high peak-to-average power ratio (PAPR) of the transmitted signal for large number of subcarriers. Selected mapping (SLM) is one of the most well-known technique to reduce the PAPR in OFDM system, since it can achieve a good PAPR reduction without signal distortion. Moreover, SLM technique can be used with wavelet-OFDM (WOFDM) system to enhance the PAPR performance, while maintaining most of the advantages of the conventional OFDM system. In this paper, an effective PAPR reduction technique using SLM-WOFDM based on particle swarm optimization (PSO) algorithm is proposed. PSO is applied to SLM-OFDM and SLM-WOFDM systems for searching the optimum phase rotation factors. The systems evaluation shows that the proposed PSO based SLM-WOFDM system provides better PAPR reduction compared to PSO based SLM-OFDM, SLM-WOFDM, and conventional SLM-OFDM systems.

Reduction of high Peak-to-Average Power Ratio (PAPR) is a very important issue in Orthogonal Frequency Division Multiplexing (OFDM) system. In this contribution, we propose a new phase sequence that can be used in Selective Mapping (SLM) technique; a well known PAPR reduction method. Generated from Greatest Common Divisor (GCD) Matrix, we show that our proposed phase sequence possesses better PAPR reduction capability compared to the Bauml sequence often used in SLM technique. From simulation results, we demonstrate that the proposed sequence achieves 3.2 dB higher PAPR reduction compared to SLM method with Bauml sequence and also reduces the computational overhead about 65 percent.

A three-dimensional (3D) orthogonal frequency division multiplexing (OFDM) system with peak-to-average power ratio (PAPR) reduction method for the wireless sensor networks (WSNs) is presented. The transmit power of wireless nodes in an ad hoc network is strictly limited. Thus, high PAPR of the 3D OFDM system is a possible drawback when it is considered as a physical layer transmission scheme for the WSNs. Here, we propose an improved partial transmit sequence (PTS) technique to reduce PAPR of the OFDM system with 3D modulation formats. In the proposed algorithm, the components of 3D signals are assigned to different subblocks using a diagonal rule (DR), increasing randomness of the signals in the disjoint subblocks forcibly. As a result, the proposed method reduces PAPR of the 3D OFDM system significantly without increase in computational complexity. Hence, the proposed algorithm makes the 3D OFDM system be a possible candidate for a physical layer transmission scheme in future WSNs.

Orthogonal Frequency Division Multiplexing (OFDM) is one of the attractive data transmission technologies in recent years because of its high data processing rate and its capable to combat inter-symbol interference (ISI) that come from multiple paths fading. Also, OFDM is the standard of new generation wireless communication systems. However, the high Peak-to-Average Power Ratio(PAPR) can influence the system performance through significantly degrading its signal quality in the nonlinear channel. Researchers propose several PAPR reduction algorithms, such as Clipping, Partial Transmit Sequences (PTS), selective mapping (SLM). In this paper we propose a novel turbo scheme combining PTS with adaptive tone reservation (TR) to reduce PAPR in OFDM systems. Conducted simulations show that the performance of PAPR with TR-enhanced Turbo PTS are superior to pervious works.

High Peak to Average Power Ratio (PAPR) in the transmitted signal is still a very important challenge in Orthogonal Frequency Division Multiplexing (OFDM) systems. In this paper, we present a new Zadoff-Chu matrix Transform (ZCT) precoded Selected Mapping (SLM) based OFDM (SLM-OFDM) system for PAPR reduction. The proposed system is based on precoding the constellation symbols with ZCT precoder after the multiplication of phase rotation factor and before the Inverse Fast Fourier Transform (IFFT) in SLM-OFDM Systems. At the clipping probability of 10−3, simulation results show that our proposed system can reduce the PAPR up to 5.0 dB with N=64 (System subcarriers) and V=16 (Dissimilar phase sequences) for QPSK modulation. Additionally, ZCT based SLM-OFDM systems also take advantage of frequency variations of the communication channel and can also offer substantial performance gain in fading multipath channels.

In this paper, we propose a new PAPR reduction by using a partial transmit sequences (PTS) method with coded side information (SI) technique. These methods are used in an orthogonal frequency division multiplexing (OFDM) system. The OFDM employs orthogonal sub-carriers for data modulation. These sub-carriers unexpectedly present a large peak to average power ratio (PAPR) in some cases. In order to reduce PAPR, the sequence of input data is partitioned into disjoint sub-block of PTS. If number of sub-block increases, high efficiency of PAPR reduction can be obtained. However, a quite large calculation cost must be demanded and thus it is impossible to obtain the optimum PTS. In the proposed method, we introduce a coded side information technique assuming the pseudo-optimum condition into the PTS. The total calculation cost becomes drastically reduced and side information bits for recovering original data in demodulation. In simulation results, the proposed method demonstrated the improvement of PAPR and bit error rate (BER) performance.

This paper proposes a partial transmit sequence (PTS) scheme with applying a stochastic optimization technique for peak-to-average power ratio (PAPR) reduction in the orthogonal frequency division multiplexing (OFDM) system. PTS technique combining can improve the PAPR statistics of an OFDM signals, but the considerable computational complexity for the required search through a high-dimensional vector space is a potential problem for implementation in the practical systems. Differential evolution (DE) is an efficient and powerful population-based stochastic search technique for solving optimization problems over continuous space, which has been widely applied in many scientific and engineering fields. Thus, to reduce the complexity for searching phase weight vector and to improve the PAPR statistics, we introduce the DE, an effective algorithm that solves various combinatorial optimization problems, to search the optimal phase weight factors. The simulation results show that the proposed DE-based PTS obtains the excellent PAPR performance with a low computational complexity.

Partial transmit sequence (PTS) scheme is one of the efficacious tool for lessening peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) system. However, computational cost for the optimum phase factors searches of PTS scheme entails huge computational requirements and limits its applicability to practical applications especially for high-speed data transmissions. This study proposes a PAPR reduction method with a low computational complexity based on a combination of cuckoo search optimization algorithm with PTS scheme in OFDM system. In terms of PAPR and computational cost reductions, the performance of the cuckoo-PTS scheme is comparatively investigated by performing a set of simulations with different PTS schemes.

Based on superposition of signals in the time domain, we propose a new low-complexity scheme for the reduction of the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. The proposed scheme first generates signal candidates by combining an OFDM signal and its cyclically delayed versions with different delays and phases, and then selects the candidate signal with minimum PAPR. It is shown that the complexity of the proposed scheme is significantly lower than that of the selective mapping (SLM) at the cost of some degradation in the bit error rate (BER) performance and, at similar PAPR and coded BER performance, is lower than that of the low-complexity SLM proposed recently.

Given that the conventional Selected Mapping (SLM) scheme needs to multiply pseudo-random phase sequences to the transmitted data meanwhile transmitting the whole side information, an exhaustive entropy and chaotic phase sequence based SLM method was proposed for reduction the peak-to-average power ratio (PAPR) of Orthogonal frequency division multiplexing (OFDM) in the paper. In the novel algorithm, exhaustive entropy was used to evaluate the randomness of phase sequence, chaotic sequences to reduce the large side information and improved Lorenz sequence digitalization method to enlarge sequence entropy, expanding the number of the candidate phase sequences vector space with the lower transmitted parameters of phase sequence. Simulation results show that different quantization methods of chaotic sequence have different exhaustive entropy and PAPR values. Furthermore, compared with the traditional SLM method, the new scheme proposed in the paper has better performance in reducing PAPR of OFDM system by about 0.1-0.5dB.

Orthogonal Frequency Division Multiplexing (OFDM) is an encoding method that are hugely utilized in wireless communication due to its high number of advantages such as tolerance for multipath delay spread, frequency selective fading channels immune and also power efficiency. The bad side of this method is it has high Peak Average Power Ratio (PAPR) that will generate nonlinear distortions and severe power penalty. In this research, Selective Mapping (SLM) method is proposed to solve the problem of high PAPR but from previous researches, it could be seen that in SLM, the search complexity increases as the number of phase sequence increase. To solve this issue, Firefly Algorithm (FA) is applied to optimize the function of SLM. The modulation method used is Quadrature Phase Shift Keying (QPSK). By the end of the process, CCDF and BER plots are computed. The performance of PAPR reduction in OFDM system are analyzed by different number of subcarriers, phase sequences, randomization parameters and iterations using CCDF graphs. The performance of OFDM channel through AWGN channel is studied with different number of subcarriers. By using SLM method only, the PAPR values manage to be reduced by 0.4–3 dB but with FA-SLM algorithm, the PAPR values can be reduced by 5–9.5 dB. With these results, it is concluded that the combination of SLM with FA can help to improve computational complexity in SLM and eventually reduce PAPR value in OFDM system.

Peak-to-average power ratio (PAPR) one of the most important issues in orthogonal frequency division multiplexing (OFDM). Iterative clipping and filtering (CF) is a high efficiency technique to reduce PAPR in OFDM systems, but it needs numerous iterations to minimize the peak regrowth problem. This paper presents a new CF method which requires one iteration. The previous method needs 2K+1 IFFT/FFT blocks where K is iterations number. By using this algorithm, the number of FFT and IFFT operations have been decreased to three. The simulated results show that the QPSK modulated OFDM signal with 528 sub-carriers achieves a P APR reduction of 6.1 dB by passing the OFDM signal from white Gaussian noise channel with a good bit error rate performance at the receiver.

In this paper, we propose a genetic-simulated annealing algorithm (GSAA) with partial transmit sequence (PTS) technique (GSAA-PTS) to reduce the peak-to-average power ratio (PAPR) for orthogonal frequency division multiplexing (OFDM) system. Genetic algorithm based PTS method (GA-PTS) is a novel and suboptimal PAPR reduction approach, which has lower computational load than original PTS method. However, researchers still focus on how to improve the PAPR performance. The proposed method GSAA-PTS takes the advantages of genetic algorithm and simulated annealing algorithm to search the best phase factors of PTS. In this method, we initialize the population firstly, and then selection, crossover and mutation are used to generate the new population, finally using the simulated annealing algorithm to update each chromosome in the population. The simulation results show that the better performance of PAPR have been achieved by adopting GSAA-PTS scheme.

The artificial bee colony-based SLM (ABC-SLM) scheme, which is a novel PAPR reduction scheme, has been proposed to reduce the peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. High PAPR can degrade the efficiency of high-power amplifier and is one of the major disadvantages of OFDM systems. This paper proposes a modified ABC-SLM scheme to further improve the PAPR reduction performance of ABC-SLM scheme. The proposed method, called GA-ABC-SLM, is combined the gene algorithm (GA) with the artificial bee colony-based SLM scheme. The simulation results show that the GA-ABC-SLM scheme has better PAPR reduction performance than the ABC-SLM scheme.

High peak-to-average-power ratio (PAPR) is a particular disadvantage of orthogonal frequency-division multiplexing (OFDM) systems and can significantly degrade the power efficiency at the transmitter. The aim of this paper is to propose a post-inverse fast Fourier transform (IFFT) PAPR reduction method based on intelligent linear symbol combining with the objective to minimize the PAPR at the transmitter. Unlike the methods so far reported in the literature, the proposed method has a relatively low complexity and does not require external randomization sequences. This paper will also investigate the impact of the proposed method on the system's bit error rate (BER) performance and provide a closed-form analytical expression that takes into account the BER dependency on the side information bits and multiblock combination. It will be shown that the proposed technique can provide significant PAPR reductions at manageable levels of signal processing requirements while the BER degradation is relatively small.