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

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

Advanced methods in automatic modulation classification for emerging technologies

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

Joint semiblind frequency offset and channel estimation for multiuser MIMO-OFDM uplink

A semiblind method is proposed for simultaneously estimating the carrier frequency offsets (CFOs) and channels of an uplink multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system. By incorporating the CFOs into the transmitted symbols and channels, the MIMO-OFDM with CFO is remodeled into an MIMO-OFDM without CFO. The known blind method for channel estimation (Zeng and Ng in 2004) (Y. H. Zeng and T. S. Ng, "A semi-blind channel estimation method for multi-user multi-antenna OFDM systems," IEEE Trans. Signal Process., vol. 52, no. 5, pp. 1419-1429, May 2004.) is then directly used for the remodeled system to obtain the shaped channels with an ambiguity matrix. A pilot OFDM block for each user is then exploited to resolve the CFOs and the ambiguity matrix. Two dedicated pilot designs, periodical and consecutive pilots, are discussed. Based on each pilot design and the estimated shaped channels, two methods are proposed to estimate the CFOs. As a result, based on the second-order statistics (SOS) of the received signal and one pilot OFDM block, the CFOs and channels are found simultaneously. Finally, a fast equalization method is given to recover the signals corrupted by the CFOs. © 2007 IEEE.published_or_final_versio

Novel Complex Adaptive Signal Processing Techniques Employing Optimally Derived Time-varying Convergence Factors With Applicatio

In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR)

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

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

Adaptive interference cancelation techniques for multicarrier modulated systems

Current wireline systems and wireless broadcasting systems employ multicarrier modulation (MCM). This includes the high-rate digital subscriber line (HDSL), digital audio broadcasting system (DAB) and the digital terrestrial television broadcasting system (dTTb). Multicarrier modulation is also envisioned for high-speed indoor wireless local area networks (WLAN). Additionally, multicarrier code division multiple access (MC-CDMA), a hybrid of orthogonal frequency division multiplexing (OFDM) and CDMA, is proposed for the downlink (base-to-mobile) of a 3rd generation wireless system as part of the IMT-2000 standardization process. The performance of an MC-CDMA system--similar to a direct sequence CDMA (DS-CDMA) system--is limited by the presence of multiple access interference (MAI) . Downlink communications also suffers from MAI as a result of the multipath channel effect, even if it implements orthogonal code multiplexing. Additionally, transmissions aimed at different mobile users may be assigned different powers in order to increase the system capacity, essentially creating a near-far problem for some users. Due to the MC-CDMA signal structure the conventional decorrelator (based on the inverse of the correlation matrix) is dependent on the channel coefficients, suggesting the use of an adaptive multiuser detector, which can track a time-variant channel. The performance of a blind adaptive multiuser detector for MC-CDMA, based on the bootstrap algorithm, is investigated and compared to the performance of the conventional decorrelator. Additionally, the performance is investigated for different channel conditions. First, for a non-faded flat additive white Gaussian noise (AWGN) channel. Second, for a frequency selective channel with and without correlation between the channel coefficients at the different subcarriers. In general, the mobile terminal suffers from limited available resources such as computing power or battery life and, therefore, cannot accommodate the same level of receiver complexity as the base station. For the downlink, however, the received signal structure is less complex due to the assumed synchronized transmission. Moreover, the mobile receiver is merely required to detect the desired user\u27s data stream. To reduce the complexity, detectors are proposed that do not require knowledge of the active users nor their respective codes, but rather use a combined code to represent all the interfering users at once. The performance of the reduced complexity conventional decorrelator is compared to the performance of an adaptive reduced complexity detector using the bootstrap algorithm. The performance of these detectors is also investigated for the aforementioned channel types. For spectral-efficiency, closely spaced subcarriers are used in a multicarrier modulated system. A resulting drawback is a high sensitivity of the performance to a frequency offset. This results from a Doppler shift, due to mobile movement, as well as from a mismatch between the carrier frequencies at the transmitter and receiver. To mitigate this problem an adaptive decorrelator based frequency offset correction scheme is developed for OFDM and its performance is investigated. Additionally, a blind frequency offset estimation and correction structure is proposed based on a stochastic gradient method. The convergence and statistical properties of this estimator are investigated. A blind adaptive joint multiuser detection and frequency offset correction structure for downlink MC-CDMA is developed. This detector is a combination of the structures for multiuser detection for MC-CDMA and frequency offset correction for OFDM. Moreover, the performance of this detector is investigated and compared to a joint detector based on a minimum mean square error (MMSE) criterion

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe