214 research outputs found

    Software Defined Radio Implementation of Carrier and Timing Synchronization for Distributed Arrays

    Full text link
    The communication range of wireless networks can be greatly improved by using distributed beamforming from a set of independent radio nodes. One of the key challenges in establishing a beamformed communication link from separate radios is achieving carrier frequency and sample timing synchronization. This paper describes an implementation that addresses both carrier frequency and sample timing synchronization simultaneously using RF signaling between designated master and slave nodes. By using a pilot signal transmitted by the master node, each slave estimates and tracks the frequency and timing offset and digitally compensates for them. A real-time implementation of the proposed system was developed in GNU Radio and tested with Ettus USRP N210 software defined radios. The measurements show that the distributed array can reach a residual frequency error of 5 Hz and a residual timing offset of 1/16 the sample duration for 70 percent of the time. This performance enables distributed beamforming for range extension applications.Comment: Submitted to 2019 IEEE Aerospace Conferenc

    Advanced classification of OFDM and MIMO signals with enhanced second order cyclostationarity detection

    Get PDF
    With the emergence of cognitive radio and the introduction of new modulation techniques such as OFDM and MIMO, the problem of Modulation Classification (MC) becomes more challenging and complicated. In the first part of the thesis, we explore the automatic modulation classification to blindly distinguish OFDM from single carrier signals. We use the fourth order cumulants; an approach which in the past has been also applied to classify single carrier signals. A blind OFDM parameter estimation scheme was then followed, which includes the estimation of number of subcarriers, CP length, timing and frequency offset and the oversampling factor for the OFDM signal. For the second part of the thesis, we improve the statistical signal processing techniques that were used in the first part. Particularly, the second order cyclostationarity based methods have been examined and improved. Based on the fact that most of the cyclostationary communication signals has a real cyclostationary part and a complex non-cyclostaionary part, we suggest an approach that enhance the second order cyclostationarity and hence increase its probability of detection. Using such improved second-order cyclostationarity, we present an improved synchronization method based on second order cyclostationarity. With the proposed approach, it is shown that the timing estimator, is independent of the frequency offset estimator, and therefore performs better than the previously proposed class of blind synchronization methods. To negate the dependence of the blind synchronization scheme on the prior knowledge of the raised cosine pulse shaping filters, we proposed a blind roll-off factor estimator based on the second order cyclostationarity. Last, we address the MIMO classification problem, wherein we estimate the number of transmitting antennas. Here the second order cyclostationarity test has been applied in distinguishing STC from BLAST modulation

    MIMO signal processing in offset-QAM based filter bank multicarrier systems

    Get PDF
    Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft

    A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems

    Get PDF
    This paper deals with training-assisted carrier frequency offset (CFO) estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The exact maximum likelihood (ML) solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load

    A Novel estimation and Correction of Channel errors in LTE SYSTEMS

    Get PDF
    The increase in the number of RF devices and the requirement for large data rates places major role in increasing demand on bandwidth. This necessitates the need for RF communication systems with increased throughput and capacity. MIMO-OFDM is one way to meet this basic requirement. OFDM is used in many (WCD) wireless communication devices and offers high spectral efficiency and resilience to multipath channel effects. Though OFDM is very sensitive to synchronization errors, it makes the task of channel equalization simple. MIMO utilize the multiple antennas to increase throughput without increasing transmitter power or bandwidth. This project presents an introduction to the (MPC) multipath fading channel and describes an appropriate channel model. Many modulation schemes are presented (i.e. BPSK, QPSK, QAM) that are often used in Conjunction with OFDM. Mathematical modeling and analysis of OFDM are given along with a discrete implementation common to modern RF communication systems. Synchronization errors are modeled mathematically and simulated, as well as techniques to estimate and correct those errors at the receiver accurately

    Fine Timing and Frequency Synchronization for MIMO-OFDM: An Extreme Learning Approach

    Full text link
    Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is a key technology component in the evolution towards cognitive radio (CR) in next-generation communication in which the accuracy of timing and frequency synchronization significantly impacts the overall system performance. In this paper, we propose a novel scheme leveraging extreme learning machine (ELM) to achieve high-precision synchronization. Specifically, exploiting the preamble signals with synchronization offsets, two ELMs are incorporated into a traditional MIMO-OFDM system to estimate both the residual symbol timing offset (RSTO) and the residual carrier frequency offset (RCFO). The simulation results show that the performance of the proposed ELM-based synchronization scheme is superior to the traditional method under both additive white Gaussian noise (AWGN) and frequency selective fading channels. Furthermore, comparing with the existing machine learning based techniques, the proposed method shows outstanding performance without the requirement of perfect channel state information (CSI) and prohibitive computational complexity. Finally, the proposed method is robust in terms of the choice of channel parameters (e.g., number of paths) and also in terms of "generalization ability" from a machine learning standpoint.Comment: 13 pages, 12 figures, has been accepted for publication in IEEE Transactions on Cognitive Communications and Networkin

    Low-Complexity Time Synchronization Algorithm for Optical OFDM PON System Using a Directly Modulated DFB Laser

    Full text link
    © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper a low-complexity time synchronization algorithm for optical orthogonal frequency division multiplexing (OFDM) is proposed. The algorithm is based on a repetitive preamble that allows the use of a short cross correlator with an exponential average filter for postprocessing before a threshold detection. The signals in the correlation have been quantized with 1 bit, and the correlations have been implemented as a hard-wired tree adder to reduce the hardware cost. This solution has been verified in a passive optical network (PON) system using a directly modulated distributed feedback (DFB) laser achieving excellent performance with low computing processing complexity even in low signal-to-noise ratio scenarios. Finally, a parallel hardware architecture has been proposed for this time synchronization algorithm, and it has been implemented in a field programmable gate array device reaching a sample rate throughput up to 7.4 Gs/s.This work was supported by the Spanish Ministerio de Economia y Competitividad under projects TEC2012-38558-C02-02 and TEC2012-38558-C02-01 and with FEDER funds.Bruno, JS.; Almenar Terre, V.; Valls Coquillat, J.; Corral, JL. (2015). Low-Complexity Time Synchronization Algorithm for Optical OFDM PON System Using a Directly Modulated DFB Laser. IEEE/OSA Journal of Optical Communications and Networking. 7(11):1025-1033. doi:10.1364/JOCN.7.001025S1025103371

    Timing and Frequency Synchronization and Channel Estimation in OFDM-based Systems

    Get PDF
    Orthogonal frequency division multiplexing (OFDM) due to its appealing features, such as robustness against frequency selective fading and simple channel equalization, is adopted in communications systems such as WLAN, WiMAX and DVB. However, OFDM systems are sensitive to synchronization errors caused by timing and frequency offsets. Besides, the OFDM receiver has to perform channel estimation for coherent detection. The goal of this thesis is to investigate new methods for timing and frequency synchronization and channel estimation in OFDM-based systems. First, we investigate new methods for preamble-aided coarse timing estimation in OFDM systems. Two novel timing metrics using high order statistics-based correlation and differential normalization functions are proposed. The performance of the new timing metrics is evaluated using different criteria including class-separability, robustness to the carrier frequency offset, and computational complexity. It is shown that the new timing metrics can considerably increase the class-separability due to their more distinct values at correct and wrong timing instants, and thus give a significantly better detection performance than the existing timing metrics do. Furthermore, a new method for coarse estimation of the start of the frame is proposed, which remarkably reduces the probability of inter-symbol interference (ISI). The improved performances of the new schemes in multipath fading channels are shown by the probabilities of false alarm, missed-detection and ISI obtained through computer simulations. Second, a novel pilot-aided algorithm is proposed for the detection of integer frequency offset (IFO) in OFDM systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic pilot sequence and an aperiodic pilot sequence. It is shown that the new scheme can significantly reduce the computational complexity while achieving almost the same performance as the previous methods do. Third, we propose a method for joint timing and frequency synchronization and channel estimation for OFDM systems that operate in doubly selective channels. Basis expansion modeling (BEM) that captures the time variations of the channel is used to reduce the number of unknown channel parameters. The BEM coefficients along with the timing and frequency offsets are estimated by using a maximum likelihood (ML) approach. An efficient algorithm is then proposed for reducing the computational complexity of the joint estimation. The complexity of the new method is assessed in terms of the number of multiplications. The mean square estimation error of the proposed method is evaluated in comparison with previous methods, indicating a remarkable performance improvement by the new method. Fourth, we present a new scheme for joint estimation of CFO and doubly selective channel in orthogonal frequency division multiplexing systems. In the proposed preamble-aided method, the time-varying channel is represented using BEM. CFO and BEM coefficients are estimated using the principles of particle and Kalman filtering. The performance of the new method in multipath time-varying channels is investigated in comparison with previous schemes. The simulation results indicate a remarkable performance improvement in terms of the mean square errors of CFO and channel estimates. Fifth, a novel algorithm is proposed for timing and frequency synchronization and channel estimation in the uplink of orthogonal frequency division multiple access (OFDMA) systems by considering high-mobility situations and the generalized subcarrier assignment. By using BEM to represent a doubly selective channel, a maximum likelihood (ML) approach is proposed to jointly estimate the timing and frequency offsets of different users as well as the BEM coefficients of the time-varying channels. A space-alternating generalized expectation-maximization algorithm is then employed to transform the maximization problem for all users into several simpler maximization problems for each user. The computational complexity of the new timing and frequency offset estimator is analyzed and its performance in comparison with that of existing methods using the mean square error is evaluated . Finally, two novel approaches for joint CFO and doubly selective channel estimation in the uplink of multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) systems are presented. Considering high-mobility situations, where channels change within an OFDMA symbol interval, and the time varying nature of CFOs, BEM is employed to represent the time variations of the channel. Two new approaches are then proposed based on Schmidt Kalman filtering (SKF). The first approach utilizes Schmidt extended Kalman filtering for each user to estimate the CFO and BEM coefficients. The second approach uses Gaussian particle filter along with SKF to estimate the CFO and BEM coefficients of each user. The Bayesian Cramer Rao bound is derived, and performance of the new schemes are evaluated using mean square error. It is demonstrated that the new schemes can significantly improve the mean square error performance in comparison with that of the existing methods
    • …
    corecore