PAPR and ICI reduction techniques for OFDM based satellite communication systems

Multi-carrier systems such as orthogonal frequency division multiplexing (OFDM) are significantly affected by peak-to-average-power ratio (PAPR). Unfortunately, the high PAPR inherent to OFDM signals envelopes will occasionally drive high power amplifiers (HPAs) to operate in the nonlinear region of their characteristic curve. The nonlinearity of the HPA exhibits amplitude and phase distortions, which cause loss of orthogonality among the subcarriers (SCs), and hence, inter-carrier interference (ICI) is introduced in the transmitted signal. The ICI power is proportional to the amplitude of the signal at the amplifier input and it may cause a considerable bit error rate (BER) degradation. A plethora of research has been devoted to reduce the performance degradation due to the PAPR problem inherent to OFDM systems. Some of the reported techniques such as amplitude clipping have low-complexity; on the other hand, they suffer from various problems such as in-band distortion and out-of-band expansion. Signal companding methods have low-complexity, good distortion and spectral properties; however, they have limited PAPR reduction capabilities. Advanced techniques such as coding, partial transmit sequences (PTS) and selected mapping (SLM) have also been considered for PAPR reduction. Such techniques are efficient and distortionless, nevertheless, their computational complexity is high and requires the transmission of several side information (SI) bits. In this thesis, a new low-complexity scheme is proposed based on the PTS that employs two inverse fast Fourier transforms (IFFTs) and two circulant transform matrices, in order to reduce complexity and improve the system performance. Furthermore, the low-complexity scheme is simplified by omitting one of the circulant transform matrices in order to reduce both the computational complexity and the number of SI bits at the cost of a small reduction in PAPR and BER performance. It is well known that, accurate PAPR estimation requires oversampling of the transmitted signal, which in turn results in increased complexity. More importantly, minimising the PAPR does not necessarily minimise the distortion produced by the nonlinearity of the HPA. Therefore, minimising PAPR does not necessarily imply that the BER will be minimised too. Efficient and less complex schemes for BER reduction of OFDM systems in the presence of nonlinear HPA and/or carrier frequency offset (CFO) are proposed. These proposed techniques are based on predicting the distortion introduced by the nonlinearity of HPA and/or CFO. Subsequently, techniques such as the PTS and SLM are invoked to minimise the distortion and BER. Three distortion metrics are adopted in this thesis: inter-modulation distortion (IMD), peak interference-to-carrier ratio (PICR) and distortion-to-signal power ratio (DSR). Monte Carlo simulations will confirm that the DSR and PICR are more reliable than the PAPR and IMD for selecting the coefficients of the PTS and SLM to minimise the BER. Furthermore, complexity analyses demonstrate that the proposed schemes offer significant complexity reduction when compared to standard PAPR-based methods. A closed form solution for accurate BER for the OFDM signals perturbed by both the HPA nonlinearity and CFO was derived. Good agreement between the simulation results and the theoretical analysis can be obtained for different HPA parameters and CFOs. Finally, efficient approaches to reduce the impact of nonlinear power amplifiers with respect to the BER of OFDM systems are proposed. These are approaches based on: the well-established PAPR schemes, a power amplifier model and a simple single point cross correlator. The optimum phase sequence within the proposed approaches is selected by maximising the correlation between the input and output of the power amplifier model. Simulation results have confirmed that the BER using the proposed approaches is almost identical to the DSR, while the complexity is reduced significantly for particular system configurations.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Low-Complexity Schemes for Class-III and CORR SLM in OFDM Systems

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 노종선.In this dissertation, orthogonal frequency division multiplexing (OFDM) system is studied. Since OFDM signal sequence undergoes high peak-to-average power ratio (PAPR), several schemes are proposed to mitigate the PAPR problem. PAPR reduction schemes such as selected mapping (SLM) and partial transmit sequence (PTS) are introduced. Due to the high computational complexity of the SLM scheme, low-complexity SLM schemes have been proposed by many researchers. Class-III SLM scheme [55] requires only one inverse fast Fourier transform (IFFT) operation, whereas the conventional scheme needs U IFFT operations. By randomly selecting the cyclic shift and rotation values, this scheme can generate up to N3 alternative OFDM signal sequences. The PAPR reduction performance of Class-III SLM scheme is little degraded compared to the conventional SLM scheme. Recently, instead of PAPR reduction, the different performance criteria for SLM scheme are proposed such as inter modulation distortion [38] and correlation (CORR) [56]. The objective of these schemes are enhancing the bit error rate (BER) performance instead of PAPR reduction performance. In the first part of this dissertation, a deterministic selection method of phase sequences is proposed for Class-III SLM scheme [55]. First, the optimal condition of cyclic shift values in the Class-III SLM scheme is proposed. Then, the cyclic shift values satisfying the optimal condition is also derived. Compared to the random selection method, the proposed selection method guarantees the optimal PAPR reduction performance. Second, two generation methods for good alternative OFDM signal sequences are proposed, one by using rotation values which do not have linear relation and the other with no rotation values. The advantages of the proposed selection schemes are: (a) The second proposed selection scheme does not need the rotation values. (b) Both of the proposed selection schemes require less side information than random selection scheme. (c) The first proposed selection scheme guarantees the optimal PAPR reduction performance in terms of variance of correlation. In the second part of this dissertation, the proper oversampling rate for the CORR SLMscheme is proposed. It is known that four times oversampling is enough to estimate the PAPR of the continuous OFDM signal. By calculating the correlation coefficient between the continuous and two times oversampled OFDMsignal sequences, it is found that two times oversampling is enough to achieve the same BER performance as four times oversampling case in the CORR SLM scheme. In the simulation results, the same BER performance can be achieved by the proposed two times oversampling rate as four times oversampling case.Abstract i Contents iii List of Tables vii List of Figures ix 1. Introduction 1 1.1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2. Overview of Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . 4 2. OFDM System Model 7 2.1. OFDM System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2. Modulation and Demodulation of OFDM Signal . . . . . . . . . . . . 9 2.2.1. Orthogonality Principle . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2. OFDM Signal Modulation and Demodulation . . . . . . . . . . 10 2.3. Fast Fourier Transform . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4. Guard Interval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5. Peak-to-Average Power Ratio . . . . . . . . . . . . . . . . . . . . . . . 13 2.5.1. Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.5.2. The distribution of PAPR . . . . . . . . . . . . . . . . . . . . . 13 2.5.3. PAPR of Oversampled Signal . . . . . . . . . . . . . . . . . . 15 3. PAPR Reduction Schemes 17 3.1. Clipping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.2. Tone Reservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.3. Partial Transmit Sequence . . . . . . . . . . . . . . . . . . . . . . . . 19 3.4. Selected Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.5. Low-Complexity SLM Schemes . . . . . . . . . . . . . . . . . . . . . 24 3.5.1. SLM Scheme with Divided IFFT Stages . . . . . . . . . . . . . 24 3.5.2. Modified SLM Scheme . . . . . . . . . . . . . . . . . . . . . . 25 3.5.3. SLM Scheme with Conversion Matrices . . . . . . . . . . . . . 26 3.6. Considerations for PAPR Reduction Schemes . . . . . . . . . . . . . . 28 4. BER Reduction Schemes 30 4.1. PTS Scheme with PICR Metric . . . . . . . . . . . . . . . . . . . . . . 30 4.2. IMD Reduction Scheme . . . . . . . . . . . . . . . . . . . . . . . . . 32 4.3. PTS Scheme with MSE Metric . . . . . . . . . . . . . . . . . . . . . . 33 4.4. DSR Reduction Scheme with Distortion Prediction . . . . . . . . . . . 34 5. Low-Complexity Class-III SLM Scheme 37 5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 5.2. Overview of Class-III SLM Scheme . . . . . . . . . . . . . . . . . . . 39 5.3. Selection of Optimal Alternative OFDM Signal Sequences for Class-III SLM Scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 5.3.1. Correlation Analysis . . . . . . . . . . . . . . . . . . . . . . . 41 5.3.2. Selection of Optimal Cyclic Shift Values . . . . . . . . . . . . 44 5.3.3. Maximum Number of Optimal Alternative OFDM Signal Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3.4. Selection of Additional Alternative OFDM Signal Sequences . . 49 5.4. Side Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.5. Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.6. Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 6. Low-Complexity CORR SLM Scheme 61 6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 6.2. Overview of SLM Scheme Using CORR Metric . . . . . . . . . . . . . 62 6.2.1. Overview of CORR Metric . . . . . . . . . . . . . . . . . . . . 62 6.2.2. BER Performance of SLM Scheme under HPA . . . . . . . . . 65 6.3. Oversampling Effect on SLM Scheme Using CORR Metric . . . . . . . 67 6.3.1. Expression of Oversampled Signal and CORR Metric . . . . . . 67 6.3.2. Correlation Coefficients between Coefficient Sequences Derived from CORR Metric Computation . . . . . . . . . . . . . . . . 70 6.4. Computational Complexity . . . . . . . . . . . . . . . . . . . . . . . . 72 6.5. Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.6. Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.6.1. Effect of 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.6.2. Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.6.2.1. Comparative CORR . . . . . . . . . . . . . . . . . . 82 6.6.2.2. Low Sampled CORR . . . . . . . . . . . . . . . . . 83 6.7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 7. Conclusions 86 Bibliography 88 초록 96Docto

Analysis and Implementation of PAPR reduction algorithms for C-OFDM signals

Nowadays multicarrier modulation has become a key technology for communication systems; for example C-OFDM schemes are used in wireless LAN (802.11a/g/n), terrestrial digital television (DVB-T) and audio broadcaster (DAB) in Europe, and discrete multitone (DMT) in x.DSL systems. The principal difficulty with OFDM is the occurrence of the coherent alignment of the time domain parallel signals at the transmitted side which forces system designer to introduce either additional hard computationally device or a suitable power back-off at the high power amplifier in order to cope with the large magnitude signal fluctuation. This leads to a significant increment in computational cost in the former case whereas in a worse allowable power utilization in the latter case with respect to the original system. However since both allowable power and computational cost are subject to a design as well as regulatory limit others solution must be accomplished. Peak reduction techniques reduce maximum-to-mean amplitude fluctuations nominating as a feasible solution. Peak-to-average power ratio is the key metric to measure this amplitude fluctuations at transmitter and to give a clear figure of merit for comparison among different techniques