| 1. |
- Khanzadi, M Reza, 1983, et al.
(författare)
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A model-based analysis of phase jitter in RF oscillators
- 2012
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Ingår i: 2012 IEEE International Frequency Control Symposium, IFCS 2012, Proceedings. - 9781457718199 ; , s. 508-511
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Konferensbidrag (refereegranskat)abstract
- The closed-form autocorrelation function of the phase jitter accumulation process in presence of 1/f 3 and 1/f 2 shape noises is derived from the single-sideband (SSB) phase noise (PN) measurements. Exploiting the calculated autocorrelation function, a lower bound for the minimum achievable mean square error (MSE) of the PN prediction in a typical single-input singleoutput communication system is computed. This bound links the performance of a communication system suffering from the PN directly to the SSB PN measurements.
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| 2. |
- Khanzadi, M Reza, 1983, et al.
(författare)
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A Novel Cognitive Modulation Method Considering the Performance of Primary User
- 2010
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Ingår i: Wireless Advanced (WiAD), 2010 6th Conference on. - 9781424470693 ; , s. 1 - 6
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a new modulation method foran uncoded cognitive transmission (secondary user transmission)in presence of a Primary User (PU) for the AWGN channel.Interference of the PU is assumed to be known at the transmitterof Cognitive User (CU) non-causally. Based on this knowledge,for the design of the modulator and demodulator of the CU,a symbol by symbol approach is studied which can fulfill thecoexistence conditions of the CU and the PU of the band. In thisscheme, the modulator and demodulator of CU are designedjointly by solving an optimization problem to mitigate theinterference of the PU and minimize the symbol error probability(Pe) in CU’s communication link without increasing the symbolerror probability (Pe) of the PU. The proposed method is amodulation approach in a single (complex-valued) dimensionrather than a high dimensional coding scheme. Although thisone-dimensional method is not capacity achieving, we show it stillhas a remarkable performance with low amount of complexity.An implementation algorithm for our modulation method is alsopresented and the performance of this method is evaluated byexperimental results.
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| 3. |
- Khanzadi, M Reza, 1983, et al.
(författare)
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Calculation of the Performance of Communication Systems from Measured Oscillator Phase Noise
- 2014
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Ingår i: IEEE Transactions on Circuits and Systems I: Regular Papers. - 1549-8328 .- 1558-0806. ; 61:5, s. 1553-1565
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Tidskriftsartikel (refereegranskat)abstract
- Oscillator phase noise (PN) is one of the major problems that affect the performance of communication systems. In this paper, a direct connection between oscillator measurements, in terms of measured single-side band PN spectrum, and the optimal communication system performance, in terms of the resulting error vector magnitude (EVM) due to PN, is mathematically derived and analyzed. First, a statistical model of the PN, considering the effect of white and colored noise sources, is derived. Then, we utilize this model to derive the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an EVM bound for the system performance. Based on our analysis, it is found that the influence from different noise regions strongly depends on the communication bandwidth, i.e., the symbol rate. For high symbol rate communication systems, cumulative PN that appears near carrier is of relatively low importance compared to the white PN far from carrier. Our results also show that 1/f^3 noise is more predictable compared to 1/f^2 noise and in a fair comparison it affects the performance less.
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| 4. |
- Mecklenbräuker, Christoph F., et al.
(författare)
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Sequential Bayesian Sparse Signal Reconstruction Using Array Data
- 2013
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Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1941-0476 .- 1053-587X. ; 61:24, s. 6344-6354
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, the sequential reconstruction of source waveforms under a sparsity constraint is considered from a Bayesian perspective. Let the wave field, which is observed by a sensor array, be caused by a spatially-sparse set of sources. A spatially weighted Laplace-like prior is assumed for the source field and the corresponding weighted Least Absolute Shrinkage and Selection Operator (LASSO) cost function is derived. After the weighted LASSO solution has been calculated as the maximum a posteriori estimate at time step, the posterior distribution of the source amplitudes is analytically approximated. The weighting of the Laplace-like prior for time step is then fitted to the approximated posterior distribution. This results in a sequential update for the LASSO weights. Thus, a sequence of weighted LASSO problems is solved for estimating the temporal evolution of a sparse source field. The method is evaluated numerically using a uniform linear array in simulations and applied to data which were acquired from a towed horizontal array during the long range acoustic communications experiment.
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| 5. |
- Movahed, A., et al.
(författare)
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A robust {RFPI}-based 1-bit compressive sensing reconstruction algorithm
- 2012
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Ingår i: IEEE Information Theory Workshop (ITW), Lausanne, 3-7 September 2012. - 9781467302234 ; , s. 567-571
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Konferensbidrag (refereegranskat)abstract
- n this paper, we introduce a 1-bit compressive sensing reconstruction algorithm that is not only robust against bit flips in the binary measurement vector, but also does not require a priori knowledge of the sparsity level of the signal to be reconstructed. Through numerical experiments, we show that our algorithm outperforms state-of-the-art reconstruction algorithms for the 1-bit compressive sensing problem in the presence of random bit flips and when the sparsity level of the signal deviates from its estimated value.
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| 6. |
- Movahed, A., et al.
(författare)
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Recovering signals with variable sparsity levels from the noisy 1-bit compressive measurements
- 2014
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Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781479928927 ; , s. 6454-6458
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Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the 1-bit compressive sensing reconstruction problem in a scenario that the sparsity level of the signal is unknown and time variant, and the binary measurements are contaminated with the noise. We introduce a new reconstruction algorithm which we refer to as Noise-Adaptive Restricted Step Shrinkage (NARSS). NARSS is superior in terms of performance, complexity and speed of convergence to the algorithms already introduced in the literature for 1-bit compressive sensing reconstruction from the noisy binary measurements.
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| 7. |
- Panahi, Ashkan, 1986, et al.
(författare)
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A novel method of DOA tracking by penalized least squares
- 2013
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Ingår i: 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013. - 9781467331463 ; , s. 61-64
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Konferensbidrag (refereegranskat)abstract
- This work develops a new DOA tracking technique by proposing a novel semi-parametric method of sequential sparse recovery for a dynamic sparsity model. The proposed method iteratively provides a sequence of spatial spectrum estimates. The final process of estimating direction paths from the spectrum sequence is not considered. However, the simulation results show concentration of the spectrum around the true directions, which simplifies DOA tracking, for example, using a pattern recognition approach. We have also proved analytical results indicating consistency in terms of spectral concentration, which we omit in the interest of space and postpone to a more extensive work. The semi-parametric nature of the proposed method avoids highly complex data association and makes the method robust against crossing. The computational complexity per time sample is proportional to grid size, which can be contrasted to a single-snapshot LASSO solution that has a polynomial complexity order.
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| 8. |
- Panahi, Ashkan, 1986, et al.
(författare)
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A robust ℓ1 penalized DOA estimator
- 2012
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Ingår i: Conference Record - Asilomar Conference on Signals, Systems and Computers. - 1058-6393. - 9781467350518 ; , s. 2013-2017
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Konferensbidrag (refereegranskat)abstract
- The SPS-LASSO has recently been introduced as a solution to the problem of regularization parameter selection in the complex-valued LASSO problem. Still, the dependence on the grid size and the polynomial time of performing convex optimization technique in each iteration, in addition to the deficiencies in the low noise regime, confines its performance for Direction of Arrival (DOA) estimation. This work presents methods to apply LASSO without grid size limitation and with less complexity. As we show by simulations, the proposed methods loose a negligible performance compared to the Maximum Likelihood (ML) estimator, which needs a combinatorial search We also show by simulations that compared to practical implementations of ML, the proposed techniques are less sensitive to the source power difference.
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| 9. |
- Panahi, Ashkan, 1986, et al.
(författare)
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Basis pursuit over continuum applied to range-Doppler estimation problem
- 2014
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Ingår i: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. - 2151-870X. - 9781479914814 ; , s. 381-384
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Konferensbidrag (refereegranskat)abstract
- Sparse estimation and compressive sensing techniques have been recently considered for radar estimation problems. It is frequently observed that these methods are robust to model uncertainties and substantially improve performance in scenarios with a low signal-to-noise. However, since current sparsity-based techniques are computationally costly and require a suitable discretization (grid), which strongly restricts resolution, they practically receive less attention. In this work, we present an application of a new sparsity-based technique to the specific problem of range-Doppler estimation. The method, generalizing basis pursuit, is less computationally complex and its performance is independent of the grid selection. We demonstrate that the proposed technique can improve estimation performance in difficult cases, as compared to the SAGE technique.
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| 10. |
- Panahi, Ashkan, 1986, et al.
(författare)
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Fast Candidate Points Selection in the LASSO Path
- 2012
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Ingår i: IEEE Signal Processing Letters. - 1070-9908 .- 1558-2361. ; 19:2, s. 79-82
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Tidskriftsartikel (refereegranskat)abstract
- The LASSO sparse regression method has recently received attention in a variety of applications from image compression techniques to parameter estimation problems. This paper addresses the problem of regularization parameter selection in this method in a general case of complex-valued regressors and bases. Generally, this parameter controls the degree of sparsity or equivalently, the estimated model order. However, with the same sparsity/model order, the smallest regularization parameter is desired. We relate such points to the nonsmooth points in the path of LASSO solutions and give an analytical expression for them. Then, we introduce a numerically fast method of approximating the desired points by a recursive algorithm. The procedure decreases the necessary number of solutions of the LASSO problem dramatically, which is an important issue due to the polynomial computational cost of the convex optimization techniques. We illustrate our method in the context of DOA estimation.
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