| 1. |
- Larsson, Erik G, et al.
(författare)
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Adaptive equalization for frequency-selective channels of unknown length
- 2005
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Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 54:2, s. 568-579
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Tidskriftsartikel (refereegranskat)abstract
- This paper studies adaptive equalization for time-dispersive communication channels whose impulse responses have unknown lengths. This problem is important, because an adaptive equalizer designed for an incorrect channel length is suboptimal: it often estimates an unnecessarily large number of parameters. Some solutions to this problem exist (e.g., attempting to estimate the ``channel length'', and then switching between different equalizers); however, these are suboptimal owing to the difficulty of correctly identifying the channel length, and the risk associated with an incorrect estimation of this length. Indeed, to determine the channel length is effectively a model order selection problem, for which no optimal solution is known.We propose a novel, systematic approach to the problem under study, which circumvents the estimation of the channel length. The key idea is to model the channel impulse response via a mixture Gaussian model, which has one component for each possible channel length. The parameters of the mixture model are estimated from a received pilot sequence. We derive the optimal receiver associated with this mixture model, along with some computationally efficient approximations of it. We also devise a receiver, consisting of a bank of soft-output Viterbi algorithms (SOVAs), that can deliver soft decisions. Via numerical simulations, we show that our new method can significantly outperform conventional adaptive Viterbi equalizers that use a fixed or an estimated channel length.
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| 2. |
- Mattsson, Per, et al.
(författare)
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Identification of cascade water tanks using a PWARX model.
- 2018
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Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 106, s. 40-48
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we consider the identification of a discrete-time nonlinear dynamical model for a cascade water tank process. The proposed method starts with a nominal linear dynamical model of the system, and proceeds to model its prediction errors using a model that is piecewise affine in the data. As data is observed, the nominal model is refined into a piecewise ARX model which can capture a wide range of nonlinearities, such as the saturation in the cascade tanks. The proposed method uses a likelihood-based methodology which adaptively penalizes model complexity and directly leads to a computationally efficient implementation.
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| 3. |
- Soltanalian, Mojtaba, et al.
(författare)
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Training Signal Design for Correlated Massive MIMO Channel Estimation
- 2017
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Ingår i: IEEE Transactions on Wireless Communications. - : IEEE Press. - 1536-1276 .- 1558-2248. ; 16:2, s. 1135-1143
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a new approach to the design of training sequences that can be used for an accurate estimation of multi-input multi-output channels. The proposed method is particularly instrumental in training sequence designs that deal with three key challenges: 1) arbitrary channel and noise statistics that do not follow specific models, 2) limitations on the properties of the transmit signals, including total power, per-antenna power, having a constant-modulus, discrete-phase, or low peak-to-average-power ratio, and 3) signal design for large-scale or massive antenna arrays. Several numerical examples are provided to examine the proposed method.
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| 4. |
- Jansson, Daniel, 1986-
(författare)
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Identification Techniques for Mathematical Modeling of the Human Smooth Pursuit System
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis proposes nonlinear system identification techniques for the mathematical modeling of the human smooth pursuit system (SPS) with application to motor symptom quantification in Parkinson's disease (PD). The SPS refers to the complex neuromuscular system in humans that governs the smooth pursuit eye movements (SPEM). Insight into the SPS and its operation is of importance in a wide and steadily expanding array of application areas and research fields. The ultimate purpose of the work in this thesis is to attain a deeper understanding and quantification of the SPS dynamics and thus facilitate the continued development of novel commercial products and medical devices. The main contribution of this thesis is in the derivation and evaluation of several techniques for SPS characterization. While attempts to mathematically model the SPS have been made in the literature before, several key aspects of the problem have been previously overlooked.This work is the first one to devise dynamical models intended for extended-time experiments and also to consider systematic visual stimuli design in the context of SPS modeling. The result is a handful of parametric mathematical models outperforming current State-of-the-Art models in terms of prediction accuracy for rich input signals. As a complement to the parametric dynamical models, a non-parametric technique involving the construction of individual statistical models pertaining to specific gaze trajectories is suggested. Both the parametric and non-parametric models are demonstrated to successfully distinguish between individuals or groups of individuals based on eye movements.Furthermore, a novel approach to Wiener system identification using Volterra series is proposed and analyzed. It is exploited to confirm that the SPS in healthy individuals is indeed nonlinear, but that the nonlinearity of the system is significantly stronger in PD subjects. The nonlinearity in healthy individuals appears to be well-modeled by a static output function, whereas the nonlinear behavior introduced to the SPS by PD is dynamical.
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| 5. |
- Jyothi, R., et al.
(författare)
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Design of High-Dimensional Grassmannian Frames via Block Minorization Maximization
- 2021
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Ingår i: IEEE Communications Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1089-7798 .- 1558-2558. ; 25:11, s. 3624-3628
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Tidskriftsartikel (refereegranskat)abstract
- In this letter, we present an iterative algorithm for constructing high-dimensional incoherent Grassmannian Frames (GFs) which are sets of unit-norm vectors that are minimax optimal: the maximum absolute value of their inner products is a minimum. We formulate the GF design as a nonconvex optimization problem and solve it via an efficient iterative algorithm. The bulk of each iteration of the proposed algorithm is a Linear Program (LP) for which there are a host of efficient solvers. The proposed algorithm is based on the theoretically sound Minorization Maximization technique which, unlike some of the state-of-the-art design approaches, monotonically minimizes the design criterion and can construct GFs with low coherence values.
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| 6. |
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| 7. |
- Shang, Xiaolei, et al.
(författare)
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Weighted SPICE Algorithms for Range-Doppler Imaging Using One-Bit Automotive Radar
- 2021
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Ingår i: IEEE Journal on Selected Topics in Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4553 .- 1941-0484. ; 15:4, s. 1041-1054
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Tidskriftsartikel (refereegranskat)abstract
- We consider the problem of range-Doppler imaging using one-bit automotive LFMCW1 or PMCW radar that utilizes one-bit ADC sampling with time-varying thresholds at the receiver. The one-bit sampling technique can significantly reduce the cost as well as the power consumption of automotive radar systems. We formulate the one-bit LFMCW/PMCW radar range-Doppler imaging problem as one-bit sparse parameter estimation. The recently proposed hyperparameter-free (and hence user friendly) weighted SPICE algorithms, including SPICE, LIKES, SLIM and IAA, achieve excellent parameter estimation performance for data sampled with high precision. However, these algorithms cannot be used directly for one-bit data. In this paper we first present a regularized minimization algorithm, referred to as 1bSLIM, for accurate range-Doppler imaging using one-bit radar systems. Then, we describe how to extend the SPICE, LIKES and IAA algorithms to the one-bit data case, and refer to these extensions as 1bSPICE, 1bLIKES and 1bIAA. These one-bit hyperparameter-free algorithms are unified within the one-bit weighted SPICE framework. Moreover, efficient implementations of the aforementioned algorithms are investigated that rely heavily on the use of FFTs. Finally, both simulated and experimental examples are provided to demonstrate the effectiveness of the proposed algorithms for range-Doppler imaging using one-bit automotive radar systems.
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| 8. |
- Tang, Bo, et al.
(författare)
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MIMO Multifunction RF Systems : Detection Performance and Waveform Design
- 2022
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Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 70, s. 4381-4394
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Tidskriftsartikel (refereegranskat)abstract
- This paper studies the detection performance of a multiple-input-multiple-output (MIMO) multifunction radio frequency (MFRF) system, which simultaneously supports radar, communication, and jamming. We show that the detection performance of the MIMO MFRF system improves as the transmit signal-to-interference-plus-noise-ratio (SINR) increases. To analyze the achievable SINR of the system, we formulate an SINR maximization problem under the communication and jamming functionality constraint as well as a transmit energy constraint. We derive a closed-form solution of this optimization problem for energy-constrained waveforms and present a detailed analysis of the achievable SINR. Moreover, we analyze the SINR for systems transmitting constant-modulus waveforms, which are often used in practice. We propose an efficient constant-modulus waveform design algorithm to maximize the SINR. Numerical results demonstrate the capability of a MIMO array to provide multiple functions, and also show the tradeoff between radar detection and the communication/jamming functionality.
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| 9. |
- Wirfält, Petter, 1979-, et al.
(författare)
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Subspace-based frequency estimation utilizing prior information
- 2011
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Ingår i: 2011 IEEE Statistical Signal Processing Workshop (SSP). - Piscataway, NJ : IEEE. - 9781457705694 ; , s. 533-536
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Konferensbidrag (refereegranskat)abstract
- In certain frequency estimation applications one or more of the underlyingfrequencies are known. For example, in rotary machines the known frequencymay be a strong network frequency masking important closely spacedfrequencies. Being able to include this information in the design of the estimator can be expected to improve the performance when estimating such closely spaced frequencies. We present a framework to include such priorinformation in a class of subspace-based estimators. Through Monte Carlo simulations and real-data applications we show the usefulness of our approach.
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| 10. |
- Zachariah, Dave, et al.
(författare)
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Scalable and Passive Wireless Network Clock Synchronization in LOS Environments
- 2017
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Ingår i: IEEE Transactions on Wireless Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 1536-1276 .- 1558-2248. ; 16:6, s. 3536-3546
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Tidskriftsartikel (refereegranskat)abstract
- Clock synchronization is ubiquitous in wireless systems for communication, sensing, and control. In this paper, we design a scalable system in which an indefinite number of passively receiving wireless units can synchronize to a single master clock at the level of discrete clock ticks. Accurate synchronization requires an estimate of the node positions to compensate the time-of-flight transmission delay in line-of-sight environments. If such information is available, the framework developed here takes position uncertainties into account. In the absence of such information, as in indoor scenarios, we propose an auxiliary localization mechanism. Furthermore, we derive the Cramer-Rao bounds for the system, which show that it enables synchronization accuracy at sub-nanosecond levels. Finally, we develop and evaluate an online estimation method, which is statistically efficient.
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