An OFDM Signal Identification Method for Wireless Communications Systems

Distinction of OFDM signals from single carrier signals is highly important for adaptive receiver algorithms and signal identification applications. OFDM signals exhibit Gaussian characteristics in time domain and fourth order cumulants of Gaussian distributed signals vanish in contrary to the cumulants of other signals. Thus fourth order cumulants can be utilized for OFDM signal identification. In this paper, first, formulations of the estimates of the fourth order cumulants for OFDM signals are provided. Then it is shown these estimates are affected significantly from the wireless channel impairments, frequency offset, phase offset and sampling mismatch. To overcome these problems, a general chi-square constant false alarm rate Gaussianity test which employs estimates of cumulants and their covariances is adapted to the specific case of wireless OFDM signals. Estimation of the covariance matrix of the fourth order cumulants are greatly simplified peculiar to the OFDM signals. A measurement setup is developed to analyze the performance of the identification method and for comparison purposes. A parametric measurement analysis is provided depending on modulation order, signal to noise ratio, number of symbols, and degree of freedom of the underlying test. The proposed method outperforms statistical tests which are based on fixed thresholds or empirical values, while a priori information requirement and complexity of the proposed method are lower than the coherent identification techniques

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

Reliability of Trigonometric Transform-based Multi-Carrier Scheme

This work is looking for a new physical layer of a multi-carrier wireless communication system to be implemented in low complexity way, resorting to suitable fast transform. The work presents and assesses a scheme based on Discrete Trigonometric Transform with appending symmetric redundancy either in each or multiple consecutive transformed blocks. A receiver front-end filter is proposed to enforce whole symmetry in the channel impulse response, and bank of one tap filter per sub-carrier is applied as an equalizer in the transform domain. The behaviour of the transceiver is studied in the context of practical impairments like fading channel, carrier frequency offset and narrow band interference. Moreover, the performance is evaluated in contrast with the state of art methods by means of computer simulations, and it has been found that the new scheme improves robustness and reliability of communication signal, and record lower peak to average power ratio. The study demonstrates that front-end matched filter effectively performs frequency synchronization to compensate the carrier frequency offset in the received signal

Efficient channel equalization algorithms for multicarrier communication systems

Blind adaptive algorithm that updates time-domain equalizer (TEQ) coefficients by Adjacent Lag Auto-correlation Minimization (ALAM) is proposed to shorten the channel for multicarrier modulation (MCM) systems. ALAM is an addition to the family of several existing correlation based algorithms that can achieve similar or better performance to existing algorithms with lower complexity. This is achieved by designing a cost function without the sum-square and utilizing symmetrical-TEQ property to reduce the complexity of adaptation of TEQ to half of the existing one. Furthermore, to avoid the limitations of lower unstable bit rate and high complexity, an adaptive TEQ using equal-taps constraints (ETC) is introduced to maximize the bit rate with the lowest complexity. An IP core is developed for the low-complexity ALAM (LALAM) algorithm to be implemented on an FPGA. This implementation is extended to include the implementation of the moving average (MA) estimate for the ALAM algorithm referred as ALAM-MA. Unit-tap constraint (UTC) is used instead of unit-norm constraint (UNC) while updating the adaptive algorithm to avoid all zero solution for the TEQ taps. The IP core is implemented on Xilinx Vertix II Pro XC2VP7-FF672-5 for ADSL receivers and the gate level simulation guaranteed successful operation at a maximum frequency of 27 MHz and 38 MHz for ALAM-MA and LALAM algorithm, respectively. FEQ equalizer is used, after channel shortening using TEQ, to recover distorted QAM signals due to channel effects. A new analytical learning based framework is proposed to jointly solve equalization and symbol detection problems in orthogonal frequency division multiplexing (OFDM) systems with QAM signals. The framework utilizes extreme learning machine (ELM) to achieve fast training, high performance, and low error rates. The proposed framework performs in real-domain by transforming a complex signal into a single 2–tuple real-valued vector. Such transformation offers equalization in real domain with minimum computational load and high accuracy. Simulation results show that the proposed framework outperforms other learning based equalizers in terms of symbol error rates and training speeds

Blind Demodulation of Pass Band OFDMA Signals and Jamming Battle Damage Assessment Utilizing Link Adaptation

This research focuses on blind demodulation of a pass band OFDMA signal so that jamming effectiveness can be assessed; referred to in this research as BDA. The research extends, modifies and collates work within literature to perform a new method of blindly demodulating of a passband OFDMA signal, which exhibits properties of the 802.16 Wireless MAN OFDMA standard, and presents a novel method for performing BDA via observation of SC LA. Blind demodulation is achieved by estimating the carrier frequency, sampling rate, pulse shaping filter roll off factor, synchronization parameters and CFO. The blind demodulator\u27s performance in AWGN and a perfect channel is evaluated where it improves using a greater number OFDMA DL symbols and increased CP length. Performance in a channel with a single multi-path interferer is also evaluated where the blind demodulator\u27s performance is degraded. BDA is achieved via observing SC LA modulation behavior of the blindly demodulated signal between successive OFDMA DL sub frames in two scenarios. The first is where modulation signaling can be used to observe change of SC modulation. The second assumes modulation signaling is not available and the SC\u27s modulation must be classified. Classification of SC modulation is performed using sixth-order cumulants where performance increases with the number of OFDMA symbols. The SC modulation classi er is susceptible to the CFO caused by blind demodulation. In a perfect channel it is shown that SC modulation can be classified using a variety of OFDMA DL sub frame lengths in symbols. The SC modulation classifier experienced degraded performance in a multi-path channel and it is recommended that it is extended to perform channel equalization in future work

Waveform design and processing techniques in OFDM radar

Includes bibliographical referencesWith the advent of powerful digital hardware, software defined radio and radar have become an active area of research and development. This in turn has given rise to many new research directions in the radar community, which were previously not comprehensible. One such direction is the recently investigated OFDM radar, which uses OFDM waveforms instead of the classic linear frequency mod- ulated waveforms. Being a wideband signal, the OFDM symbol offers spectral efficiency along with improved range resolution, two enticing characteristics for radar. Historically a communication signal, OFDM is a special form of multi- carrier modulation, where a single data stream is transmitted over a number of lower rate carriers. The information is conveyed via sets of complex phase codes modulating the phase of the carriers. At the receiver, a demodulation stage estimates the transmitted phase codes and the information in the form of binary words is finally retrieved. In radar, the primary goal is to detect the presence of targets and possibly estimate some of their features through measurable quantities, e.g. range, Doppler, etc. Yet, being a young waveform in radar, more understanding is required to turn it into a standard radar waveform. Our goal, with this thesis, is to mature our comprehension of OFDM for radar and contribute to the realm of OFDM radar. First, we develop two processing alternatives for the case of a train of wideband OFDM pulses. In this, our first so-called time domain solution consists in applying a matched filter to compress the received echoes in the fast time before applying a fast Fourier transform in the slow time to form the range Doppler image. We motivate this approach after demonstrating that short OFDM pulses are Doppler tolerant. The merit of this approach is to conserve existing radar architectures while operating OFDM waveforms. The second so-called frequency domain solution that we propose is inspired from communication engineering research since the received echoes are tumbled in the frequency domain. After several manipulations, the range Doppler image is formed. We explain how this approach allows to retrieve an estimate of the unambiguous radial velocity, and propose two methods for that. The first method requires the use of identical sequence (IS) for the phase codes and is, as such, binding, while the other method works irrespective of the phase codes. Like the previous technique, this processing solution accommodates high Doppler frequencies and the degradation in the range Doppler image is negligible provided that the spacing between consecutive subcarriers is sufficient. Unfortunately, it suffers from the issue of intersymbol interference (ISI). After observing that both solutions provide the same processing gain, we clarify the constraints that shall apply to the OFDM signals in either of these solutions. In the first solution, special care has been employed to design OFDM pulses with low peak-to-mean power ratio (PMEPR) and low sidelobe level in the autocorrelation function. In the second solution, on the other hand, only the constraint of low PMEPR applies since the sidelobes of the scatterer characteristic function in the range Doppler image are Fourier based. Then, we develop a waveform-processing concept for OFDM based stepped frequency waveforms. This approach is intended for high resolution radar with improved low probability of detection (LPD) characteristics, as we propose to employ a frequency hopping scheme from pulse to pulse other than the conventional linear one. In the same way we treated our second alternative earlier, we derive our high range resolution processing in matrix terms and assess the degradation caused by high Doppler on the range profile. We propose using a bank of range migration filters to retrieve the radial velocity of the scatterer and realise that the issue of classical ambiguity in Doppler can be alleviated provided that the relative bandwidth, i.e. the total bandwidth covered by the train of pulses divided by the carrier frequency, is chosen carefully. After discussing a deterministic artefact caused by frequency hopping and the means to reduce it at the waveform design or processing level, we discuss the benefit offered by our concept in comparison to other standard wideband methods and emphasize on its LPD characteristics at the waveform and pulse level. In our subsequent analysis, we investigate genetic algorithm (GA) based techniques to finetune OFDM pulses in terms of radar requirements viz., low PMEPR only or low PMEPR and low sidelobe level together, as evoked earlier. To motivate the use of genetic algorithms, we establish that existing techniques are not exible in terms of the OFDM structure (the assumption that all carriers are present is always made). Besides, the use of advanced objective functions suited to particular configurations (e.g. low sidelobe level in proximity of the main autocorrelation peak) as well as the combination of multiple objective functions can be done elegantly with GA based techniques. To justify that solely phase codes are used for our optimisation(s), we stress that the weights applied to the carriers composing the OFDM signal can be spared to cope with other radar related challenges and we give an example with a case of enhanced detection. Next, we develop a technique where we exploit the instantaneous wideband trans- mission to characterise the type of the canonical scatterers that compose a target. Our idea is based on the well-established results from the geometrical theory of diffraction (GTD), where the scattered energy varies with frequency. We present the problem related to ISI, stress the need to design the transmitted pulse so as to reduce this risk and suggest having prior knowledge over the scatterers relative positions. Subsequently, we develop a performance analysis to assess the behaviour of our technique in the presence of additive white Gaussian noise (AWGN). Then, we demonstrate the merit of integrating over several pulses to improve the characterisation rate of the scatterers. Because the scattering centres of a target resonate variably at different frequencies, frequency diversity is another enticing property which can be used to enhance the sensing performance. Here, we exploit this element of diversity to improve the classification function. We develop a technique where the classification takes place at the waveform design when few targets are present. In our case study, we have three simple targets. Each is composed of perfectly electrically conducting spheres for which we have exact models of the scattered field. We develop a GA based search to find optimal OFDM symbols that best discriminate one target against any other. Thereafter, the OFDM pulse used for probing the target in the scene is constructed by stacking the resulting symbols in time. After discussing the problem of finding the best frequency window to sense the target, we develop a performance analysis where our figure of merit is the overall probability of correct classification. Again, we prove the merit of integrating over several pulses to reach classification rates above 95%. In turn, this study opens onto new challenges in the realm of OFDM radar. We leave for future research the demonstration of the practical applicability of our novel concepts and mention manifold research axes, viz., a signal processing axis that would include methods to cope with inter symbol interference, range migration issues, methods to raise the ambiguity in Doppler when several echoes from distinct scatterers overlap in the case of our frequency domain processing solutions; an algorithmic axis that would concern the heuristic techniques employed in the design of our OFDM pulses. We foresee that further tuning might help speeding up our GA based algorithms and we expect that constrained multi- objective optimisation GA (MOO-GA) based techniques shall benefit the OFDM pulse design problem in radar. A system design axis that would account for the hardware components' behaviours, when possible, directly at the waveform design stage and would include implementation of the OFDM radar system

Energy-detection based spectrum sensing for cognitive radio on a real-time SDR platform

There has been an increase in wireless applications due to the technology boom; consequently raising the level of radio spectrum demand. However, spectrum is a limited resource and cannot be infinitely subdivided to accommodate every application. At the same time, emerging wireless applications require a lot of bandwidth for operation, and have seen exponential growth in their bandwidth usage in recent years. The current spectrum allocation technique, proposed by the Federal Communications Commission (FCC) is a fixed allocation technique. This is inefficient as the spectrum is vacant during times when the primary user is not using the spectrum. This strain on the current available bandwidth has revealed signs of an upcoming spectrum crunch; hence the need to find a solution that satisfies the increasing spectrum demand, without compromising the performance of the applications. This work leverages on cognitive radio technology as a potential solution to the spectrum usage challenge. Cognitive radios have the ability to sense the spectrum and determine the presence or absence of the primary user in a particular subcarrier band. When the spectrum is vacant, a cognitive radio (secondary user) can opportunistically occupy the radio spectrum, optimizing the radio frequency band. The effectiveness of the cognitive radio is determined by the performance of the sensing techniques. Known spectrum-sensing techniques are reviewed, which include energy detection, entropy detection, matched-filter detection, and cyclostationary detection. In this dissertation, the energy sensing technique is examined. A real-time energy detector is developed on the Software-Defined Radio (SDR) testbed that is built with Universal Software Radio Peripheral (USRP) devices, and on the GNU Radio software platform. The noise floor of the system is first analysed to determine the detection threshold, which is obtained using the empirical cumulative distribution method. Simulations are carried out using MATrix LABoratory (MATLAB) to set a benchmark. In both simulations and the SDR development platform, an Orthogonal Frequency Division Multiplexing (OFDM) signal with Quadrature Phase Shift Keying (QPSK) modulation is generated and used as the test signal