10 research outputs found

    Clipping noise cancellation in OFDM systems using oversampled signal reconstruction

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    Clipping the OFDM signals in the digital part of the transmitter is one of the simplest methods to reduce the peak factor. However, it suffers from additional clipping distortion, peak regrowth after digital to analog conversion, and out-of-band radiation in the case of oversampled sequence clipping. We use oversampled sequence clipping to combat the effect of peak regrowth and propose a method to reconstruct the clipped samples and mitigate the clipping distortion in the presence of channel noise at the expense of bandwidth expansion. We show through extensive simulations that by slightly increasing the bandwidth of the system, we can significantly improve the performance while limiting the maximum amplitude of the analog signal

    Clipping noise cancellation in OFDM systems using oversampled signal reconstruction

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    Clippling Noise Mitigation in Optical OFDM System

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    This letter portrays another non-straight calculation for cut-out clamor relief in force regulation/coordinate discovery dc one-sided optical symmetrical recurrence division multiplexing (DCO-OFDM) frameworks. Cut-out commotion is frequently the significant constraint in DCO-OFDM. In this letter, we demonstrate that additional data about the cut flag can be extricated utilizing a non-direct process and afterward used to alleviate the cut-out clamor. The adequacy of the new calculation is shown by recreation and in an optical remote trial. Decision errors, resulting in decision noise, limit the performance of the blind estimator even when estimation is based on very long signals. However, the pilot system can achieve more accurate estimations, and thus a better performance. Results are first presented for typical SEM waveforms for the case where the fundamental frequency of the SEM is known. The algorithms are then extended to include a frequency estimation step and the mitigation algorithm is shown also to be effective in this case

    Improved Hybrid Blind PAPR Reduction Algorithm for OFDM Systems

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    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

    Multicarrier-signal design with low peaks and low out-of-band power

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    Projecte fet en col.laboraciĂł amb el Department of Electrical and Information Technology. Lund UniversityThe high peak-to-average power ratio (PAPR) and the high out-of-band power (OBP) are two major drawbacks of multicarrier communication systems. Many PAPR reduction and OBP supression techniques have been proposed in the literature whereas not much has been proposed regarding the jointly reduction performance. This thesis focuses on joint reducing time-domain peaks and out-of-band leakage of OFDM signals. The resulting algorithm combines the bene ts of both methods and yields better results than each method does separately

    Multicarrier-signal design with low peaks and low out-of-band power

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    Projecte fet en col.laboraciĂł amb el Department of Electrical and Information Technology. Lund UniversityThe high peak-to-average power ratio (PAPR) and the high out-of-band power (OBP) are two major drawbacks of multicarrier communication systems. Many PAPR reduction and OBP supression techniques have been proposed in the literature whereas not much has been proposed regarding the jointly reduction performance. This thesis focuses on joint reducing time-domain peaks and out-of-band leakage of OFDM signals. The resulting algorithm combines the bene ts of both methods and yields better results than each method does separately

    OFDM 시슀템을 위한 ìƒˆëĄœìšŽ 저 ëł”ìžĄë„ SLM 방식 및 큮멬핑 ìžĄìŒ 제거 êž°ëȕ ì—°ê”Ź

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    í•™ìœ„ë…ŒëŹž (ë°•ì‚Ź)-- 서욞대학ꔐ 대학원 : ì „êž°Â·ì»Ží“ší„°êł”í•™ë¶€, 2015. 2. ë…žìą…ì„ .In this dissertation, several research results for the peak-to-average power ratio (PAPR) reduction schemes for orthogonal frequency division multiplexing (OFDM) systems are discussed. First, the basic principle and implementation of the OFDM systems are introduced, where high PAPR of OFDM signal is one of main drawbacks of OFDM systems. Thus, many PAPR reduction schemes to solve this problem have been studied such as clipping, selected mapping (SLM), partial transmit sequence (PTS), and tone reservation. In the first part of this dissertation, a low-complexity SLM scheme is proposed, where the proposed SLM scheme generates alternative OFDM signal sequences by cyclically shifting the connections in each subblock at an intermediate stage of inverse fast Fourier transform (IFFT). Compared with the conventional SLM scheme, the proposed SLM scheme achieves similar PAPR reduction performance with much lower computational complexity and no bit error rate (BER) degradation. The performance of the proposed SLM scheme is analyzed mathematically and verified through numerical analysis. Also, it is shown that the proposed SLM scheme has the lowest computational complexity among the existing low-complexity SLM schemes exploiting the signals at an intermediate stage of IFFT. In the second part of this dissertation, an efficient selection (ES) method of the OFDM signal sequence with the minimum PAPR among many alternative OFDM signal sequences is proposed, which can be used for various SLM schemes. The proposed ES method efficiently generates each component of alternative OFDM signal by utilizing the structure of IFFT and calculates its power, and such generation procedure is interrupted if the calculated power is larger than the given threshold. By using the proposed ES method, the average computational complexity of considered SLM schemes is substantially reduced without degradation of PAPR reduction performance, which is confirmed by analytical and numerical results. In the third part of this dissertation, a clipping noise cancellation scheme using compressed sensing (CS) technique is proposed for OFDM systems. The proposed scheme does not need reserved tones or pilot tones, which is different from the previous works using CS technique. Instead, observations of the clipping noise in data tones are exploited, which leads to no loss of data rate. Also, in contrast with the previous works, the proposed scheme selectively exploits the reliable observations of the clipping noise instead of using whole observations, which results in minimizing the bad influence of channel noise. From the selected reliable observations, the clipping noise in time domain is reconstructed and cancelled by using CS technique. Simulation results show that the proposed scheme performs well compared to other conventional clipping noise cancellation schemes and shows the best performance in the severely clipped cases.1. Introduction 1 1.1. Background 1 1.2. Overview of Dissertation 4 2. OFDM Systems 6 2.1. OFDM System Model 7 2.2. Peak-to-Average Power Ratio 8 2.2.1. Definition of PAPR 9 2.2.2. Distribution of PAPR 9 3. PAPR Reduction Schemes 11 3.1. Clipping 11 3.1.1. Clipping at Transmitter 11 3.1.2. A Statistical Model of Clipped Signals 13 3.1.3. Conventional Receiver without Clipping Noise Cancellation Scheme 15 3.2. Selected Mapping 16 3.3. Low-Complexity SLM Schemes 18 3.3.1. Lims SLM Scheme [25] 18 3.3.2. Wangs SLM Scheme [22] 19 3.3.3. Baxleys SLM Scheme [27] 19 3.4. Tone Reservation 20 4. A New Low-Complexity SLM Scheme for OFDM Systems 22 4.1. A New SLM Scheme with Low-Complexity 23 4.1.1. A New SLM Scheme 23 4.1.2. Relation Between the Proposed SLM Scheme and the Conventional SLM Scheme 26 4.1.3. Good Shift Values for the Proposed SLM Scheme 28 4.1.4. Methods to Generate Good Shift Values 31 4.1.5. Computational Complexity 33 4.2. Simulation Results 36 4.3. Conclusions 37 5. An Efficient Selection Method of a Transmitted OFDM Signal Sequence for Various SLM Schemes 42 5.1. ES Method and Its Application to the Conventional SLM Scheme 43 5.1.1. Sequential Generation of OFDM Signal Components in the Conventional SLM Scheme 43 5.1.2. Application of the ES Method to the Conventional SLM Scheme 45 5.1.3. Complexity Analysis for Nyquist Sampling Case 47 5.1.3.1. Characteristics of a Nyquist-Sampled OFDM Signal Sequence 48 5.1.3.2. Derivation of KN(b) 49 5.1.3.3. Distribution of pBu(bu) 51 5.1.4. Complexity Analysis for Oversampling Case 52 5.1.4.1. Characteristics of a Four-Times Oversampled OFDM Signal Sequence 52 5.1.4.2. Derivation of K4N(b) 53 5.1.4.3. Distribution of pBu(bu) 54 5.1.5. Comparison between Analytical and Simulation Results 55 5.2. Application of the ES Method to Various Low-Complexity SLM Schemes 57 5.2.1. Lims SLM Scheme Aided by the ES Method 57 5.2.2. Wangs SLM Scheme Aided by the ES Method 58 5.2.3. Baxelys SLM Scheme Aided by the ES Method 58 5.3. Simulation Results 59 5.3.1. Simulation Results for the Conventional SLM Scheme Aided by the ES Method 59 5.3.2. Simulation Results for Low-Complexity SLM Schemes Aided by the ES Method 60 5.4. Conclusions 62 6. Clipping Noise Cancellation for OFDM Systems Using Reliable Observations Based on Compressed Sensing 68 6.1. Preliminaries 71 6.1.1. Notation 71 6.1.2. Compressed Sensing 71 6.2. Clipping Noise Cancellation for OFDM Systems Based on CS 73 6.2.1. Sparsity of c 73 6.2.1.1. Sparsity of c for Clipping at the Nyquist Sampling Rate 73 6.2.1.2. Sparsity of c for Clipping and Filtering at an Oversampling Rate 74 6.2.2. Reconstruction of the Clipping Noise c by CS 75 6.2.3. Construction of the Compressed Observation Vector Y 77 6.2.3.1. Which Observations Should Be Selected 78 6.2.3.2. Estimation of Ξ(k) Based on H1(k)Y (k) 78 6.2.3.3. Selection Criterion of Observations 81 6.2.4. Computational Complexity 81 6.3. Simulation Results 82 6.3.1. AWGN Channel 82 6.3.2. Rayleigh Fading Channel 83 6.4. Conclusion 86 7. Conclusions 93 Bibliography 96 ìŽˆëĄ 104Docto

    EpÀlineaarinen vÀÀristymÀ laajakaistaisissa analogia-digitaalimuuntimissa

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    This thesis discusses nonlinearities of analog-to-digital converters (ADCs) and their mitigation using digital signal processing (DSP). Particularly wideband radio receivers are considered here including, e.g., the emerging cognitive radio applications. In this kind of receivers, a single ADC converts a mixture of signals at different frequency bands to digital domain simultaneously. Different signals may have considerably different power levels and hence the overall dynamic range can be very large (even 50–60 dB). Therefore, even the smallest ADC nonlinearities can produce considerable amount of nonlinear distortion, which may cause a strong signal to block significantly weaker signal bands. One concrete source of nonlinear distortion is waveform clipping due to improper signal conditioning in the input of an ADC. In the thesis, a mathematical model for this phenomenon is derived through Fourier analysis and is then used as a basis for an adaptive interference cancellation (AIC) method. This is a general method for reducing nonlinear distortion and besides clipping it can be used, e.g., to compensate integral nonlinearity (INL) originating from unintentional deviations of the quantization levels. Additionally, an interpolation method is proposed in this thesis to restore clipped waveforms and hence reduce nonlinear distortion. Through several computer simulations and corresponding laboratory radio signal measurements, the performance of the proposed post-processing methods is illustrated. It can be seen from the results that the methods are able to reduce nonlinear distortion from a weak signal band in a considerable manner when there are strong blocking signals in the neighboring channels. According to the results, the AIC method would be a highly recommendable post-processing technique for modern radio receivers due to its general ability to reduce nonlinear distortion regardless of its source. /Kir10TĂ€ssĂ€ työssĂ€ kĂ€sitellÀÀn analogia-digitaalimuuntimien (AD-muuntimien) epĂ€lineaarisuuksia ja niiden lieventĂ€mistĂ€ digitaalisen signaalinkĂ€sittelyn (DSP) avulla. TĂ€tĂ€ on tarkasteltu erityisesti laajakaistaisten radiovastaanottimien nĂ€kökulmasta, joka kĂ€sittÀÀ mm. tulevat kognitiiviseen radioon liittyvĂ€t sovellukset. TĂ€llaisissa vastaanottimissa yksittĂ€inen AD-muunnin muuntaa samanaikaisesti useita eri taajuuskaistoilla olevia signaaleita digitaaliseen muotoon, jolloin yhteenlaskettu dynaaminen alue voi olla hyvin suuri (jopa 50–60 dB). TĂ€mĂ€n takia AD-muuntimen pienimmĂ€tkin epĂ€lineaarisuudet voivat aiheuttaa huomattavasti epĂ€lineaarista vÀÀristymÀÀ, minkĂ€ vuoksi voimakas signaali saattaa hĂ€iriöllÀÀn peittÀÀ muilla taajuuskaistoilla olevia selkeĂ€sti heikompia signaaleja. ErĂ€s konkreettinen epĂ€lineaarisen vÀÀristymĂ€n aiheuttaja on aaltomuodon leikkaantuminen AD-muuntimen sisÀÀnmenossa jĂ€nnitealueen ylittymisen vuoksi. TĂ€ssĂ€ työssĂ€ johdetaan matemaattinen malli kyseiselle ilmiölle Fourier-analyysin avulla ja kĂ€ytetÀÀn sitĂ€ lĂ€htökohtana adaptiiviselle hĂ€iriönpoistomenetelmĂ€lle (AIC-menetelmĂ€). Se on yleisluonteinen menetelmĂ€ epĂ€lineaarisen vÀÀristymĂ€n vĂ€hentĂ€miseksi, ja leikkaantumisen lisĂ€ksi sitĂ€ voidaan kĂ€yttÀÀ esimerkiksi kompensoimaan integraalista epĂ€lineaarisuutta (INL), joka on perĂ€isin kvantisointitasojen tahattomista poikkeamista. LisĂ€ksi tĂ€ssĂ€ työssĂ€ esitellÀÀn interpolointimenetelmĂ€ leikkaantuneen aaltomuodon ehostamiseen siten, ettĂ€ epĂ€lineaarinen hĂ€iriö vĂ€henee. Esiteltyjen jĂ€lkikĂ€sittelymenetelmien suorituskykyĂ€ analysoidaan ja havainnollistetaan useilla tietokonesimulaatiolla sekĂ€ niitĂ€ vastaavilla radiosignaalien laboratoriomittauksilla. Tuloksista voidaan nĂ€hdĂ€, ettĂ€ nĂ€mĂ€ menetelmĂ€t kykenevĂ€t poistamaan huomattavasti epĂ€lineaarista vÀÀristymÀÀ heikolta signaalikaistalta silloin, kun naapurikaistoilla on voimakkaita hĂ€iriösignaaleja. Tulosten perusteella AIC-menetelmĂ€ olisi erittĂ€in suositeltava jĂ€lkikĂ€sittelytekniikka moderneihin radiovastaanottimiin, koska se pystyy yleisesti vĂ€hentĂ€mÀÀn epĂ€lineaarista vÀÀristymÀÀ riippumatta hĂ€iriön alkuperĂ€stĂ€

    Applications of Lattice Codes in Communication Systems

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    In the last decade, there has been an explosive growth in different applications of wireless technology, due to users' increasing expectations for multi-media services. With the current trend, the present systems will not be able to handle the required data traffic. Lattice codes have attracted considerable attention in recent years, because they provide high data rate constellations. In this thesis, the applications of implementing lattice codes in different communication systems are investigated. The thesis is divided into two major parts. Focus of the first part is on constellation shaping and the problem of lattice labeling. The second part is devoted to the lattice decoding problem. In constellation shaping technique, conventional constellations are replaced by lattice codes that satisfy some geometrical properties. However, a simple algorithm, called lattice labeling, is required to map the input data to the lattice code points. In the first part of this thesis, the application of lattice codes for constellation shaping in Orthogonal Frequency Division Multiplexing (OFDM) and Multi-Input Multi-Output (MIMO) broadcast systems are considered. In an OFDM system a lattice code with low Peak to Average Power Ratio (PAPR) is desired. Here, a new lattice code with considerable PAPR reduction for OFDM systems is proposed. Due to the recursive structure of this lattice code, a simple lattice labeling method based on Smith normal decomposition of an integer matrix is obtained. A selective mapping method in conjunction with the proposed lattice code is also presented to further reduce the PAPR. MIMO broadcast systems are also considered in the thesis. In a multiple antenna broadcast system, the lattice labeling algorithm should be such that different users can decode their data independently. Moreover, the implemented lattice code should result in a low average transmit energy. Here, a selective mapping technique provides such a lattice code. Lattice decoding is the focus of the second part of the thesis, which concerns the operation of finding the closest point of the lattice code to any point in N-dimensional real space. In digital communication applications, this problem is known as the integer least-square problem, which can be seen in many areas, e.g. the detection of symbols transmitted over the multiple antenna wireless channel, the multiuser detection problem in Code Division Multiple Access (CDMA) systems, and the simultaneous detection of multiple users in a Digital Subscriber Line (DSL) system affected by crosstalk. Here, an efficient lattice decoding algorithm based on using Semi-Definite Programming (SDP) is introduced. The proposed algorithm is capable of handling any form of lattice constellation for an arbitrary labeling of points. In the proposed methods, the distance minimization problem is expressed in terms of a binary quadratic minimization problem, which is solved by introducing several matrix and vector lifting SDP relaxation models. The new SDP models provide a wealth of trade-off between the complexity and the performance of the decoding problem
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