!!Visa Koivunen - Selected Publications
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1. “Advanced methods for I/Q imbalance compensation in communication networks” (with M. Valkama and M. Renfors), IEEE Transactions on Signal Processing, vol. 49, 2001 (Google Scholar citations: 666).\\
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I/Q signal processing, even though widely utilized in today’s communication receivers, face a common problem in all processing receiver structures, such as the low-IF receiver, of matching the amplitudes and phases of the I and Q branches, causing the image signal to appear as interference on top of the desired signal. This advances a simple structure for compensation based on a tradi-tional adaptive interference canceller and improved image rejection which has been obtained by using more advanced blind source separation techniques.\\
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2.  “Device-to-device communication underlaying cellular communication systems: (with P. Janis, C-H Yu,  C. Ribeiro, C. Wijting, K. Hugl and O. Tirkkonen), International Journal of Communications, Network and System Sciences, 2009 (Google Scholar citations: 478).\\
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A scheme to facilitate local peer-to-peer communication by a Device-to-Device (D2D) radio that operates as an underlay network to an IMT-Advanced cellular network is advanced using a novel power control mechanism for D2D connections that share cellular uplink resources. The mecha-nism limits the maximum D2D transmit power utilizing cellular power control information of the devices in D2D communication. Thereby it enables underlaying D2D communication even in inter-ference-limited networks with full load and without degrading the performance of the cellular net-work. Also investigated is a single cell scenario consisting of a device communicating with the base station and two devices that communicate with each other demonstrating that the D2D radio, sharing the same resources as the cellular network, can provide higher capacity compared to pure cellular communication where all the data is transmitted through the base station. A related confer-ence paper (IEEE VTC 2009) with some additional results has been cited 549 times by Google Scholar.\\
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4. “Collaborative cyclo-stationary spectrum sensing for cognitive radio systems” (with J. Lundén, A. Huttunen and H.V. Poor), IEEE Transactions on Signal Processing, vol. 57, 2008 (Google Scholar citations: 430).\\
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An energy efficient collaborative cyclo-stationary spectrum sensing approach for cognitive radio systems has been advanced by extending an existing statistical hypothesis test for multisensor systems and the presence of cyclo-stationarity to multiple cyclic frequencies and establishing its asymptotic distributions. Collaborative test statistics have been proposed for the fusion of local test statistics of the secondary users, and a censoring technique in which only informative test statistics are transmitted to the fusion center (FC) during the collaborative detection is further proposed for improving energy efficiency in mobile applications. Moreover, a technique for numerical approxi-mation of the asymptotic distribution of the censored FC test statistic has also been proposed. The methods are used in the Nokia Bell-Labs cognitive radio demonstrator system. \\
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5. “Complex elliptically symmetric distributions: Survey, new results and applications” (with E. Ollila, D.E. Tyler and H.V. Poor), IEEE Transactions on Signal Processing, vol. 60, 2012 (Google Scholar citations: 418).\\
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This paper provides a survey of the widely used circular complex elliptically symmetric (CES)  distributions, derives some new results along with their applications, e.g., in radar and array signal processing, and illustrated with theoretical examples, simulations and analysis of real radar data. The maximum likelihood (ML) estimator of the scatter matrix parameter is derived and general conditions for its existence and uniqueness, and for convergence of the iterative fixed point algorithm are established. Specific ML-estimators for several CES distributions that are widely used in the signal processing literature are discussed in depth, including the complex t-distribution, K-distribution, the generalized Gaussian distribution and the closely related angular central Gaussian distribution.\\
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6. “Robust estimation in signal processing: A tutorial style treatment of fundamental concepts” (with A.M. Zoubir, Y. Chakhchoukh and M. Muma), IEEE Signal Processing Magazine, vol. 29 2012 (Google Scholar citations: 399).\\
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This work is concerned with statistical robustness, which deals with deviations from the distribu-tional assumptions. Many problems encountered in engineering practice rely on the Gaussian dis-tribution of the data, which in many situations is well justified. This enables a simple derivation of optimal estimators. Nominal optimality, however, is useless if the estimator was derived under dis-tributional assumptions on the noise and the signal that do not hold in practice. Even slight devia-tions from the assumed distribution may cause the estimator’s performance to drastically degrade or to completely break down. It is important to know ahead of time whether the performance of the derived estimator is acceptable in situations where the distributional assumptions do not hold. This paper received the IEEE Signal Processing Society best paper award in 2017. \\
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7. “Autocorrelation based decentralized sequential detection of OFDM signals in cognitive radio” (with S. Chaudhari and H. V. Poor), IEEE Transactions on Signal Processing, vol. 57, 2008 (Google Scholar citations: 352).\\
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This paper introduces a simple and computationally efficient spectrum sensing scheme for Or-thogonal Frequency Division Multiplexing (OFDM) based primary user signal using its autocorre-lation coefficient. Further, it is shown that the log likelihood ratio test statistic is the maximum like-lihood estimate of the autocorrelation coefficient in the low signal-to-noise ratio regime. Perfor-mance of the local detector has been investigated for the additive white Gaussian noise and multi-path channels using theoretical analysis. Obtained results were verified in simulation. The perfor-mance of the local detector in the face of shadowing has been studied by simulations. A sequential detection scheme where many secondary users cooperate to detect the same primary user has been proposed. User cooperation has provided diversity gains as well as facilitated using simpler local detectors. \\
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8. “DoA estimation via manifold separation for arbitrary array structures” (with F. Belloni and A. Richter), IEEE Transactions on Signal Processing, vol. 55, 2007 (Google Scholar citations: 249).\\
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The paper introduces a manifold separation technique (MST), which stems from the wavefield modeling formalism developed for array processing. MST is a method for modeling the steering vector of antenna arrays of practical interest with arbitrary 2-D or 3-D geometry. It is the product of a sampling matrix (dependent on the antenna array only) and a Vandermonde structured coefficients vector depending on the wavefield only. This allows fast direction-of-arrival (DoA) algorithms designed for linear arrays to be used on arrays with arbitrary configuration. The methods are later extended to polarimetric arrays and azimuth-elevation processing. In real-world applications, the calibration measurements used to determine the sampling matrix are corrupted by noise. This impairs the performance of MST-based algorithms. The effect of noisy calibration measurements on subspace-based DoA algorithms using MST is derived using analytical tools. A method for finding the optimal number of selected modes in the face of calibration noise is developed. The method is employed in a widely used commercial real-world indoor localization system.\\
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9. “Steepest descent algorithms for optimization under unitary matrix constraint” (with T. Abrudan and J. Eriksson) IEEE Transactions on Signal Processing, vol. 56, 2008 (Google Scholar citations: 208).\\
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In many engineering applications and quantum computation we deal with constrained optimiza-tion problems with respect to complex-valued matrices. This paper proposes a Riemannian geometry approach for optimization of a real-valued cost function J of complex-valued matrix argument W, under the constraint that W is an n×n unitary matrix. A steepest descent (SD) algorithms is de-rived on the Lie group of unitary matrices U(n). The proposed algorithms move towards the optimum along the geodesics, i.e. the locally shortest path but other alternatives are also considered. The computational complexity is addressed and the numerical stability issues considering both the geodesic and the non-geodesic SD algorithms are established. Armijo step size adaptation rule is used similarly to reduce complexity. The theoretical results are validated by computer simulations. The proposed algorithms are applied to blind signal separation in multi-sensor (MIMO) systems by using the joint diagonalization approach, and for precoder/decoder design for wireless communications. The proposed algorithms outperform other widely used algorithms. The program code is publicly available and the method is used widely in wireless communications, sensor array pro-cessing and quantum computation applications. The method is later extended to faster conjugate gradient computation (cited 122 times Google Scholar). \\
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10. “Toward millimeter-wave joint radar communications: A signal processing perspective” (with K.V. Mishra, M.R.B. Shankar, B. Ottersten and S.A. Vorobyov), IEEE Signal Processing Maga-zine, vol. 36, 2019 (Google Scholar citations: 308).\\
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Synergistic design of communications and radar systems with common spectral and hardware resources has heralded a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Convergence of radio frequency sensing and wireless communications into Integrated Sensing and Communications (ISAC) will be one of the genuinely new technologies in 6G wireless systems. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several giga-hertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems.\\ \\[{ALLOW view All}][{ALLOW edit vkoivunen}][{ALLOW upload vkoivunen}][{ALLOW comment All}]
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