153 research outputs found

    Improved timing recovery in wireless mobile receivers

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    The problem of timing recovery in wireless mobile receiver systems is critical. This is partly because timing recovery functions must follow rapid parameter changes inherent in mobile systems and partly because both bandwidth and power must be conserved in low signal to noise ratio communication channels. The ultimate goal is therefore to achieve a low bit error rate on the recovered information for improving QoS provisioning to terminal mobile users. Traditional timing recovery methods have over-relied on phase-locked loops for timing information adjustment. However, associated schemes do not exploit code properties. This leads to synchronization difficulties in digital receivers separated from transmitters by lossy channels. In this paper we present a soft timing phase estimation algorithm for wireless mobile receivers in low signal to noise ratios. In order to develop a bandwidth and power efficient timing recovery method for wireless mobile receivers, a raised cosine filter and a multilevel phase shift keying modulation scheme are implemented and no clock signals are transmitted to the receiver. In the proposed method, the receiver exploits the soft decisions computed at each turbo decoding iteration to provide reliable estimates of a soft timing signal, which in turn, improves the decoding time. The derived method, based on sequential minimization techniques, approaches the theoretical Cramer-Rao bound with unbiased estimates within a few iterations.Key Words: discrete polyphase matched filters, maximum likelihood estimators, iterative turbo receivers, log-MAP b

    Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

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    Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

    Frequency estimation in multipath rayleigh-sparse-fading channels

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    Maximum-likelihood (ML) data-aided frequency estimation in multipath Rayleigh-fading channels with sparse impulse responses is investigated. We solve this problem under the assumption that the autocorrelation matrix of the pilot signal can be approximated by a diagonal matrix, the fading of different path amplitudes are independent from each other, and the additive noise is white and Gaussian. The ML frequency estimator is shown to be based on combining nonlinearly transformed path periodograms. We have derived the nonlinear function for the two cases: known and unknown fading variances. The new frequency estimators lead, in particular cases, to known ML frequency estimators for nonsparse multipath fading channels. The use of a priori information about the mean number of paths in the channel allows a significant improvement of the accuracy performance. Exploiting the sparseness of the channel impulse response is shown to significantly reduce the threshold signal-to-noise ratio at which the frequency error departs from the Cramer-Rao lower bound. However, precise knowledge of the channel sparseness is not required in order to realize this improvement

    Joint CFO Estimation and Data Detection in OFDM systems

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    Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that is widely used in wireless broadband communication systems. The spectral e ciency of OFDM is very high since the subcarriers are spaced as closely as possible while maintaining orthogonality. However, one of the major problems with OFDM that can cause performance degradation is carrier frequency o set (CFO) which impairs the orthogonality among OFDM subcarriers, as a consequence, results in inter-subcarrier interference. In this thesis, an iterative algorithm for joint CFO estimation and data detection in OFDM systems over frequency selective channels is proposed. The proposed algorithm is performing both CFO estimation and data detection in the frequency domain based on the Expectation-Maximization (EM) algorithm. The proposed algorithm can achieve the same bit-error-rate (BER) performance as that of its time-domain counterpart with much lower complexity. Simulation results show that the proposed algorithm can converge after three iterations and an estimate of CFO can be obtained with high accuracy

    Algorithms for channel impairment mitigation in broadband wireless communications

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    Ph.DDOCTOR OF PHILOSOPH

    Doppler Spread Estimation in MIMO Frequency-Selective Fading Channels

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    One of the main challenges in high-speed mobile communications is the presence of large Doppler spreads. Thus, accurate estimation of maximum Doppler spread (MDS) plays an important role in improving the performance of the communication link. In this paper, we derive the data-aided (DA) and non-data-aided (NDA) Cramér-Rao lower bounds (CRLBs) and maximum likelihood estimators (MLEs) for the MDS in multiple-input multiple-output (MIMO) frequency-selective fading channel. Moreover, a low-complexity NDA-moment-based estimator (MBE) is proposed. The proposed NDA-MBE relies on the second- and fourth-order moments of the received signal, which are employed to estimate the normalized squared autocorrelation function of the fading channel. Then, the problem of MDS estimation is formulated as a non-linear regression problem, and the least-squares curve-fitting optimization technique is applied to determine the estimate of the MDS. This is the first time in the literature, when DA- and NDA-MDS estimation is investigated for MIMO frequency-selective fading channel. Simulation results show that there is no significant performance gap between the derived NDA-MLE and NDA-CRLB, even when the observation window is relatively small. Furthermore, the significant reduced-complexity in the NDA-MBE leads to low root-mean-square error over a wide range of MDSs, when the observation window is selected large enough

    Advanced methods in automatic modulation classification for emerging technologies

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    Modulation classification (MC) is of large importance in both military and commercial communication applications. It is a challenging problem, especially in non-cooperative wireless environments, where channel fading and no prior knowledge on the incoming signal are major factors that deteriorate the reception performance. Although the average likelihood ratio test method can provide an optimal solution to the MC problem with unknown parameters, it suffers from high computational complexity and in some cases mathematical intractability. Instead, in this research, an array-based quasi-hybrid likelihood ratio test (qHLRT) algorithm is proposed, which depicts two major advantages. First, it is simple yet accurate enough parameter estimation with reduced complexity. Second the incorporation of antenna arrays offers an effective ability to combat fading. Furthermore, a practical array-based qHLRT classifier scheme is implemented, which applies maximal ratio combining (MRC) to increase the accuracy of both carrier frequency offset (CFO) estimation and likelihood function calculation in channel fading. In fact, double CFO estimations are executed in this classifier. With the first the unknown CFO, phase offsets and amplitudes are estimated as prerequisite for MRC operation. Then, MRC is performed using these estimates, followed by a second CFO estimator. Since the input of the second CFO estimator is the output of the MRC, fading effects on the incoming signals are removed significantly and signal-to-noise ratio (SNR) is augmented. As a result, a more accurate CFO estimate is obtained. Consequently, the overall classification performance is improved, especially in low SNR environment. Recently, many state-of-the-arts communication technologies, such as orthogonal frequency division multiplexing (OFDM) modulations, have been emerging. The need for distinguishing OFDM signal from single carrier has become obvious. Besides, some vital parameters of OFDM signals should be extracted for further processing. In comparison to the research on MC for single carrier single antenna transmission, much less attention has been paid to the MC for emerging modulation methods. A comprehensive classification system is proposed for recognizing the OFDM signal and extracting its parameters. An automatic OFDM modulation classifier is proposed, which is based on the goodness-of-fittest. Since OFDM signal is Gaussian, Cramer-von Mises technique, working on the empirical distribution function, has been applied to test the presence of the normality. Numerical results show that such approach can successfully identify OFDM signals from single carrier modulations over a wide SNR range. Moreover, the proposed scheme can provide the acceptable performance when frequency-selective fading is present. Correlation test is then applied to estimate OFDM cyclic prefix duration. A two-phase searching scheme, which is based on Fast Fourier Transform (FFT) as well as Gaussianity test, is devised to detect the number of subcarriers. In the first phase, a coarse search is carried out iteratively. The exact number of subcarriers is determined by the fine tune in the second phase. Both analytical work and numerical results are presented to verify the efficiency of the proposed scheme

    Channel parameter estimation for Quantize and Forward cooperative systems

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