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This paper presents machine learning classification on simulated data of permeable conducting spheres in air and seawater irradiated by low frequency electromagnetic pulses. Classification accuracy greater than 90% was achieved. The simulated data were generated using an analytical model of a magnetic dipole in air and seawater placed 1.5–3.5 m above the center of the sphere in 50 cm increments. The spheres had radii of 40 cm and 50 cm and were of permeable materials, such as steel, and non-permeable materials, such as aluminum. A series RL circuit was analytically modeled as the transmitter coil, and an RLC circuit as the receiver coil. Additive white Gaussian noise was added to the simulated data to test the robustness of the machine learning algorithms to noise. Multiple machine learning algorithms were used for classification including a perceptron and multiclass logistic regression, which are linear models, and a neural network, 1D convolutional neural network (CNN), and 2D CNN, which are nonlinear models. Feature maps are plotted for the CNNs and provide explainability of the salient parts of the time signature and spectrogram data used for classification. The pulses investigated, which expand the literature, include a two-sided decaying exponential, Heaviside step-off, triangular, Gaussian, rectangular, modulated Gaussian, raised cosine, and rectangular down-chirp. Propagation effects, including dispersion and frequency dependent attenuation, are encapsulated by the analytical model, which was verified using finite element modeling. The results in this paper show that machine learning methods are a viable alternative to inversion of electromagnetic induction (EMI) data for metallic sphere classification, with the advantage of real-time classification without the use of a physics-based model. The nonlinear machine learning algorithms used in this work were able to accurately classify metallic spheres in seawater even with significant pulse distortion caused by dispersion and frequency dependent attenuation. This paper presents the first effort towards the use of machine learning to classify metallic objects in seawater based on EMI sensing. [ABSTRACT FROM AUTHOR]

The design of minimum phase finite impulse response (FIR) filters is considered. The study demonstrates that the residual errors achieved by current state‐of‐the‐art design methods are nowhere near the smallest error possible on a finite resolution digital computer. This is shown to be due to conceptual errors in the literature pertaining to what constitutes a factorable linear phase filter. This study shows that factorisation is possible with a zero residual error (in the absence of machine finite resolution error) if the linear operator or matrix representing the linear phase filter is positive definite. Methodology is proposed able to design a minimum phase filter that is optimal—in the sense that the residual error is limited only by the finite precision of the digital computer, with no systematic error. The study presents practical application of the proposed methodology by designing two minimum phase Chebyshev FIR filters. Results are compared to state‐of‐the‐art methods from the literature, and it is shown that the proposed methodology is able to reduce currently achievable residual errors by several orders of magnitude. [ABSTRACT FROM AUTHOR]

In this paper, a novel channel-estimation scheme for an 8-PSK enhanced data rates for GSM evolution (EDGE) system with fast time-varying and frequency-selective fading channels is presented. Via a mathematical derivation and simulation results, the channel impulse response (CIR) of the fast fading channel is modeled as a linear function of time during a radio burst in the EDGE system. Therefore, a least-squares-based method is proposed along with the modified burst structure for time-varying channel estimation. Given that the pilot-symbol blocks are located at the front and the end of the data block, the LS-based method is able to estimate the parameters of the time-varying CIR accurately using a linear interpolation. The proposed time-varying estimation algorithm does not cause an error floor that existed in the adaptive algorithms due to a nonideal channel tracking. Besides, the time-varying CIR in the EDGE system is not in its minimum-phase form, as is required for low-complexity reduced-state equalization methods. In order to maintain a good system performance, a Cholesky-decomposition method is introduced in front of the reduced-state equalizer to transform the time-varying CIR into its minimum-phase equivalent form. Via simulation results, it is shown that the proposed algorithm is very well suited for the time-varying channel estimation and equalization, and a good bit-error-rate performance is achieved even at high Doppler frequencies up to 300 Hz with a low complexity. Index Terms--Channel estimation, fast time-varying fading, frequency-selective fading.

A new way to teach advanced undergraduate and graduate students the theory of estimation and detection is described. The paper shows that the global system mobile (GSM) radio interface is well suited to the teaching of estimation and detection theory because it entails the understanding and application of several concepts within estimation and detection, as well as information theory, signal processing, and radio-wave propagation. With GSM now a mature system with specifications available in the public domain, the students created an open-source (OS) GSM simulator, including all four modulation and coding schemes (MCS 1,2,3,4) with puncturing, a channel estimator, a minimum phase prefilter, a Max log maximum a posteriori probability (MAP) equalizer, and a convolutional decoder. Studying and understanding the theory of estimation and detection is now possible by creating algorithms for the simulator and evaluating the impact of the algorithm on the GSM block error rate (BLER). Several experiments that are possible with the simulator are described. Index Terms--Communications, signal processing, teaching detection and estimation.

In this paper, a new method is presented for channel equalization and symbol detection of an enhanced data rate for global system for mobile (GSM) communication and IS-136 evolution (EDGE) cellular system in which eight phase-shift keying (8-PSK) modulation is employed. The new method iteratively minimizes the Euclidean distance between the detected and received signal sequences, with neighbor symbol perturbation to reduce the computational complexity. The new algorithm is computationaily efficient and can also be easily implemented into commercial signal processors. Simulation results comparing our method with the reduced-state sequence-estimation (RSSE) method, both with and without set partitioning, are presented. Index Terms--Channel equalization, coherent symbol detection, enhanced data rate for global system for mobile (GSM) communication and IS-136 evolution (EDGE) cellular system.

We provide simple analytical results for the coefficients of a finite-impulse response (FIR) prefilter and the effective channel impulse response (IR) for use in cellular communication systems. We show that using a FIR filter with both causal and anticausal filter taps, it is possible to find the jointly optimized impulse response, such that the signal-to-noise ratio is maximized in the least-squares sense. We show via computer simulation for 8-ary phase-shift keying in enhanced data rates for global evolution (EDGE) that the joint optimization of the prefilter and IR produces results similar to the minimum mean-square error decision-feedback equalizer prefilter in thermal noise, but yields gain in colored noise. Index Terms--Channel estimation, maximum-likelihood detection, prefilter design, sequence estimation.

A pulsed finite-difference time-domain (FDTD) approach for computing the scattering parameters of multiport waveguide discontinuities and junctions is presented. Wideband absorbing boundary conditions (ABC's) necessary for implementation of the technique are derived. Applications of the technique are presented, and computed results are compared to measurements for several examples.

The finite-difference time-domain (FDTD) method is applied to predict reflection coefficients for edge slots penetrating the adjacent broadsides of thick walled rectangular X-band waveguides. Measured and calculated values [S.sub.11] are compared to experiment for waveguides terminated by shorted loads.

In this paper, a new algorithm is presented for estimating mobile speed for handoff in hierarchical cellular systems. The proposed algorithm is based on normalized autocorrelation values of received signals to estimate mobile speed; it contains six steps. First, the instantaneous power of the received baseband signal is calculated to remove the frequency offset and data/speech information-bearing signals, while keeping the Doppler frequency information. Second, the calculated power signal is filtered using a low-pass linear phase finite impulse response filter to suppress interference and noise. Third, the filtered power signal is decimated to ease the computational burden, while the decimation factor is properly chosen to avoid frequency aliasing. Fourth, autocorrelation values of the decimated filtered power signals are calculated on shifting slot by slot to suppress the 'slot burst frequency' interference. Fifth, the calculated autocorrelation values are normalized to suppress the power fluctuation of the received signals. Finally, the normalized autocorrelation values are compared with thresholds to estimate mobile speed. The simulation results indicate that the new algorithm works very well for both nondispersive channels and dispersive channels to distinguish fast and slow moving mobiles. The method has very low latency, with results being available typically within 1 s after communication is established, and it can report estimation result every second or less. The algorithm has been implemented by software code into Nortel's base-station radios and tested in Nortel's wireless communications labs. The lab test results are very close to the computer simulation results, which have very good estimation accuracy. Index Terms--Digital cellular systems, hierarchical cellular architecture, macrocell and microcell overlaying system, mobile speed estimation.