On PAPR Reduction of OFDM using Partial Transmit Sequence with Intelligent Optimization Algorithms

In recent time, the demand for multimedia data services over wireless links has grown up rapidly. Orthogonal Frequency Division Multiplexing (OFDM) forms the basis for all 3G and beyond wireless communication standards due to its efficient frequency utilization permitting near ideal data rate and ubiquitous coverage with high mobility. OFDM signals are prone to high peak-to-average-power ratio (PAPR). Unfortunately, the high PAPR inherent to OFDM signal envelopes occasionally drives high power amplifiers (HPAs) to operate in the nonlinear region of their characteristic leading out-of-band radiation, reduction in efficiency of communication system etc. A plethora of research has been devoted to reducing the performance degradation due to the PAPR problem inherent to OFDM systems. Advanced techniques such as partial transmit sequences (PTS) and selected mapping (SLM) have been considered most promising for PAPR reduction. Such techniques are seen to be efficient for distortion-less signal processing but suffer from computational complexity and often requires transmission of extra information in terms of several side information (SI) bits leading to loss in effective data rate. This thesis investigates the PAPR problem using Partial Transmit Sequence (PTS) scheme, where optimization is achieved with evolutionary bio-inspired metaheuristic stochastic algorithms. The phase factor optimization in PTS is used for PAPR reduction. At first, swarm intelligence based Firefly PTS (FF-PTS) algorithm is proposed which delivers improved PAPR performance with reduced searching complexity. Following this, Cuckoo Search based PTS (CS-PTS) technique is presented, which offers good PAPR performance in terms of solution quality and convergence speed. Lastly, Improved Harmony search based PTS (IHS-PTS) is introduced, which provides improved PAPR. The algorithm has simple structure with a very few parameters for larger PTS sub-blocks. The PAPR performance of the proposed technique with different parameters is also verified through extensive computer simulations. Furthermore, complexity analysis of algorithms demonstrates that the proposed schemes offer significant complexity reduction when compared to standard PAPR reduction techniques. Findings have been validated through extensive simulation tests

저복잡도 후보 OFDM 신호 생성을 이용한 새로운 PTS 방법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 노종선.This dissertation proposes several research results on the peak-to-average power ratio (PAPR) reduction schemes for the orthogonal frequency division multiplexing (OFDM) systems. The PAPR is the one of major drawback of OFDM system which causes signal distortion when OFDM signal passes through nonlinear high power amplifier (HPA). Various schemes have been proposed to reduce the PAPR of OFDM signals such as clipping, selected mapping (SLM), partial transmit sequence (PTS), active constellation extension (ACE), companding, and tone reservation (TR). Among them, PTS scheme can transmit an OFDM signal vector by generating many alternative OFDM signal vectors using the partitioned subblock signals and selecting the optimal OFDM signal vector with the minimum PAPR. However, the PTS scheme requires large computational complexity, because it needs many inverse fast Fourier transforms (IFFTs) of subblock signals and lots of alternative OFDM signal vectors are generated. In this dissertation, we concentrate on reducing the computational complexity of the PTS scheme. In the first part of this dissertation, we propose a new PTS scheme with low computational complexity using two search steps to find a subset of phase rotating vectors showing good PAPR reduction performance. In the first step, sequences with low correlation are used as phase rotating vectors for PTS scheme, which are called the initial phase vectors. Kasami sequence and quaternary sequence are used in this step as the initial phase vectors. In the second step, local search is performed based on the initial phase vectors to find additional phase rotating vectors which show good PAPR reduction performance. Numerical analysis shows that the proposed PTS scheme can achieve almost the same PAPR reduction performance as the conventional PTS scheme with much lower computational complexity than other low-complexity PTS schemes. In the second part of the dissertation, we propose another low-complexity PTS schemes using the dominant time-domain OFDM signal samples, which are only used to calculate PAPR of each alternative OFDM signal vector. In this PTS scheme, we propose efficient metrics to select the dominant time-domain samples. For further lowering the computational complexity, dominant time-domain samples are sorted in decreasing order by the proposed metric values and then the power of each sample is compared with the minimum PAPR of the previously examined alternative OFDM signal vectors. Numerical results confirm that the proposed PTS schemes using new metrics show large computational complexity reduction compared to other existing low-complexity PTS schemes without PAPR degradation. In the last part of the dissertation, for the reduced-complexity PTS scheme, a new selection method of the dominant time-domain samples is proposed by rotating the IFFTed signal samples to the area on which the IFFTed signal sample of the first subblock is located in the signal space. Moreover, the method of pre-exclusion of the phase rotating vectors using the time-domain sample rotation is proposed to reduce the number of alternative OFDM signal vectors. Further, three proposed PTS schemes are introduced to reduce the computational complexity by using simple OFDM signal rotation and pre-exclusion of the phase rotating vectors. Numerical analysis shows that the proposed PTS schemes achieve the same PAPR reduction performance as that of the conventional PTS scheme with the large computational complexity reduction.Docto

OFDM 시스템에서의 PAPR 감소를 위한 시간 영역의 큰 샘플을 이용한 저복잡도 PTS 기법

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2018. 2. 노종선.In orthogonal frequency division multiplexing (OFDM) systems, high peak-to-average power ratio (PAPR) of OFDM signals is one of the most important problems. The high PAPR of OFDM signals causes serious nonlinear distortions in process of passing through high power amplifier (HPA). These distortions have a effect on in-band distortion and out-of-band radiation, which result in bit error rate degradation of received OFDM signals and interference in adjacent channel, respectively. In order to solve the PAPR problem of OFDM signals, various PAPR reduction schemes have been proposed. This dissertation includes research results on a kind of the PAPR reduction schemes, called the partial transmit sequence (PTS) for the OFDM systems. As a solution to the PAPR problem in OFDM systems, the PTS scheme is a fairly suitable scheme due to its PAPR reduction performance and distortionless characteristics. The PTS scheme generates several candidate OFDM signals to represent an original OFDM signal and selects one with the lowest PAPR among them for transmission. However, a serious problem in the PTS scheme is high computational complexity, which is mainly required to generate and process the candidate OFDM signals. In this dissertation, in an effort to reduce its computational complexity, new PTS schemes are proposed using dominant time-domain samples of OFDM signals. Dominant time-domain samples is a small number of samples of OFDM signals used to estimate PAPRs of candidate OFDM signals efficiently. In the first part of this dissertation, low-complexity PTS schemes are proposed using new selection methods of dominant time-domain samples. The proposed selection methods of dominant time-domain samples are based on selection methods of candidate samples in candidate OFDM signals. These methods select dominant time-domain samples with reduced computational complexity. The dominant time-domain samples selected by the proposed methods are used to estimate PAPRs of candidate OFDM signals with high accuracy. Therefore, the proposed low-complexity PTS schemes can achieve the optimal PAPR reduction performance with considerably reduced computational complexity. In the second part of this dissertation, improved PTS schemes are proposed to lower the computational complexity of previous PTS schemes further while maintaining high performance of PAPR reduction. Similar with the PTS schemes proposed in the previous part of this dissertation, the improved PTS schemes utilize dominant time-domain samples and candidate samples. However, they use more efficient methods, which select the candidate samples by adaptive method or multi-stage method to select dominant time-domain samples. Therefore, the improved PTS schemes reduce computational complexity further while maintaining the optimal PAPR reduction performance. The proposed PTS schemes in this dissertation use efficient methods to select dominant time-domain samples and thus they reduce the computational complexity considerably compared to previous PTS schemes. In addition, they achieve the optimal PAPR reduction performance, which is equivalent to that of the conventional PTS scheme with the low complexity. Due to the high performance and low complexity, they are fully expected to be used in the practical implementation of OFDM systems.1 INTRODUCTION 1 1.1 Introduction 1 1.2 Overview of Dissertation 4 2 PRELIMINARIES 6 2.1 OFDM and PAPR 6 2.2 High Power Amplifier Models 8 2.3 Analysis of PAPR 11 2.3.1 PAPR of OFDM Signal 11 2.3.2 PAPR and BER 17 2.4 Iterative PAPR Reduction Schemes 18 2.4.1 Clipping and Filtering 19 2.4.2 Tone Reservation 20 2.4.3 Active Constellation Extension 24 2.5 Probabilistic PAPR Reduction Scheme: Selective Mapping 26 2.6 Conventional PTS Scheme 32 2.7 Low-Complexity PTS Schemes Using Dominant Time-Domain Samples 34 2.7.1 Dominant Time-Domain Samples 34 2.7.2 Low-Complexity PTS Schemes Using Dominant Time-Domain Samples 37 3 LOW-COMPLEXITY PTS SCHEMES WITHNEWSELECTION METHODS OF DOMINANT TIME-DOMAIN SAMPLES 40 3.1 Notations 40 3.2 Selection Methods of Candidate Samples for Dominant Time-Domain Samples 41 3.3 Proposed Low-Complexity PTS Schemes 50 4 IMPROVED PTS SCHEMES WITH ADAPTIVE SELECTION METHODS OF DOMINANT TIME-DOMAIN SAMPLES 52 4.1 Adaptive Selection Methods of Candidate Samples for Dominant Time-Domain Samples 52 4.1.1 A1-SM with W = 2 53 4.1.2 A1-SM with W = 4 54 4.1.3 A2-SM with W = 2 55 4.2 Mathematical Representations for Probability Distribution of Cn 66 4.2.1 A1-SM with W = 2 69 4.2.2 A1-SM with W = 4 69 4.2.3 A2-SM with W = 2 69 4.3 Multi-Stage Selection Method of Dominant Time-Domain Samples 70 4.4 Proposed PTS Schemes with Adaptive Selection Methods for Dominant Time-Domain Samples 71 5 PERFORMANCE ANALYSIS 74 5.1 Computational Complexity 74 5.2 Simulation Results 76 6 CONCLUSIONS 85 Abstract (In Korean) 92Docto

A hybrid-structure offset-QAM filter-bank multi-carrier MIMO system

Offset quadrature amplitude modulation (OQAM) filter-bank multi-carrier (FBMC), has great potential for boosting the spectral efficiency (SE) and energy efficiency (EE) of future communication systems. This is due to its superior spectral localization, CP-less transmission and relaxed synchronization requirements. Our research focuses on three main OQAM/FBMC research problems: the computational complexity reduction taking equalization into consideration, its integration with multiple-input multiple-output (MIMO) and its high peak-to-average power ratio (PAPR). OQAM/FBMC systems are mainly implemented either using frequency spreading (FS) or polyphase network (PPN) techniques. The PPN technique is generally less complex, but when using frequency domain equalization (FDE) to equalize multipath channel effects at the receiver, there is a computational complexity overhead when using PPN. A novel hybrid-structure OQAM/FBMC MIMO space-frequency block coding (SFBC) system is proposed, to achieve the lowest possible overall complexity in conjunction with FDE at the receiver in frequency selective Rayleigh fading channel. The Alamouti SFBC block coding is performed on the complex-orthogonal signal before OQAM processing, which resolves the problems of intrinsic interference when integrating OQAM/FBMC with MIMO. In better multipath channel conditions with a line-of-sight (LOS) path, a zero-forcing (ZF) time domain equalization (TDE) is exploited to further reduce the computational complexity with comparable performance bit-error-rate (BER). On the other hand, to tackle the high PAPR problem of the OQAM/FBMC system in the uplink, a novel single carrier (SC)-OQAM/FBMC MIMO system is proposed. The system uses DFT-spreading applied to the OQAM modulated signal, along with interleaved subcarrier mapping to significantly reduce the PAPR and enhance the BER performance over Rayleigh fading channels, with relatively low additional computational complexity compared to the original complexity of the FBMC system and compared to other FBMC PAPR reduction techniques.The proposed hybrid-structure system has shown significant BER performance in frequency-selective Rayleigh fading channels compared to OFDM, with significantly lower OOB emissions in addition to the enhanced SE due to the absence of CP. In mild multipath fading channels with a LOS component, the PPN OQAM/FBMC MIMO using TDE has a comparable BER performance with significantly less computational complexity. As for the uplink, the SC-OQAM/FBMC MIMO system significantly reduces the PAPR and enhances the BER performance, with relatively low additional computational complexity

On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA–OFDM Wireless Communication System

Space Division Multiple Access(SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of SDMA and OFDM has emerged as a most competitive technology for future wireless communication system. In the SDMA uplink, multiple users communicate simultaneously with a multiple antenna Base Station (BS) sharing the same frequency band by exploring their unique user specific-special spatial signature. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. On the other hand, due to exhaustive search mechanism, the optimal Maximum Likelihood (ML) detector is limited by high computational complexity, which increases exponentially with increasing number of simultaneous users. Hence, cost function minimization based Minimum Error Rate (MER) detectors are preferred, which basically minimize the probability of error by iteratively updating receiver’s weights using adaptive algorithms such as Steepest Descent (SD), Conjugate Gradient (CG) etc. The first part of research proposes Optimization Techniques (OTs) aided MER detectors to overcome the shortfalls of the CG based MER detectors. Popular metaheuristic search algorithms like Adaptive Genetic Algorithm (AGA), Adaptive Differential Evolution Algorithm (ADEA) and Invasive Weed Optimization (IWO), which rely on an intelligent search of a large but finite solution space using statistical methods, have been applied for finding the optimal weight vectors for MER MUD. Further, it is observed in an overload SDMA–OFDM system that the channel output phasor constellation often becomes linearly non-separable. With increasing the number of users, the receiver weight optimization task turns out to be more difficult due to the exponentially increased number of dimensions of the weight matrix. As a result, MUD becomes a challenging multidimensional optimization problem. Therefore, signal classification requires a nonlinear solution. Considering this, the second part of research work suggests Artificial Neural Network (ANN) based MUDs on thestandard Multilayer Perceptron (MLP) and Radial Basis Function (RBF) frameworks fo