Author
Visa Koivunen
Other affiliations: Princeton University, University of Oulu, University of Pennsylvania ...read more
Bio: Visa Koivunen is an academic researcher from Aalto University. The author has contributed to research in topics: MIMO & Radar. The author has an hindex of 53, co-authored 495 publications receiving 11901 citations. Previous affiliations of Visa Koivunen include Princeton University & University of Oulu.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors carried out general signal analysis of an imbalanced I/Q processing receiver and proposed novel methods for I and Q imbalance compensation using baseband digital signal processing.
Abstract: I/Q signal processing is widely utilized in today's communication receivers However, all I/Q processing receiver structures, such as the low-IF receiver, face a common problem of matching the amplitudes and phases of the I and Q branches In practice, imbalances are unavoidable in the analog front-end, which results in finite and usually insufficient rejection of the image frequency band This causes the image signal to appear as interference on top of the desired signal We carry out general signal analysis of an imbalanced I/Q processing receiver and propose novel methods for I/Q imbalance compensation using baseband digital signal processing A simple structure for compensation is derived, based on a traditional adaptive interference canceller Improved image rejection can also be obtained by using more advanced blind source separation techniques Theoretical analysis of the performance of the proposed imbalance compensation structures is presented In addition, some simulation results are provided in order to further evaluate the performance of the proposed methods The results indicate that the I/Q imbalance can be effectively compensated during the normal operation of the receiver even in the rapidly changing case, as long as a linear system model for the imbalance is valid
495 citations
26 Apr 2009
TL;DR: This work proposes a practical and efficient scheme for generating local awareness of the interference between the cellular and D2D terminals at the base station, which then exploits the multiuser diversity inherent in the cellular network to minimize the interference.
Abstract: Future cellular networks such as IMT-Advanced are expected to allow underlaying direct Device-to-Device (D2D) communication for spectrally efficient support of eg rich multimedia local services Enabling D2D links in a cellular network presents a challenge in radio resource management due to the potentially severe interference it may cause to the cellular network We propose a practical and efficient scheme for generating local awareness of the interference between the cellular and D2D terminals at the base station, which then exploits the multiuser diversity inherent in the cellular network to minimize the interference System simulations demonstrate that substantial gains in cellular and D2D performance can be obtained using the proposed scheme
463 citations
TL;DR: The results demonstrate 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.
Abstract: In this article we propose 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 It is expected that local services may utilize mobile peer-to-peer communication instead of central server based communication for rich multimedia services The main challenge of the underlay radio in a multi-cell environment is to limit the interference to the cellular network while achieving a reasonable link budget for the D2D radio We propose a novel power control mechanism for D2D connections that share cellular uplink resources The mechanism 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 interference-limited networks with full load and without degrading the performance of the cellular network Secondly, we study a single cell scenario consisting of a device communicating with the base station and two devices that communicate with each other The results demonstrate that the D2D radio, sharing the same resources as the cellular network, can provide higher capacity (sum rate) compared to pure cellular communication where all the data is transmitted through the base station
405 citations
TL;DR: Applications of CES distributions and the adaptive signal processors based on ML- and M-estimators of the scatter matrix are illustrated in radar detection problems and in array signal processing applications for Direction-of-Arrival estimation and beamforming.
Abstract: Complex elliptically symmetric (CES) distributions have been widely used in various engineering applications for which non-Gaussian models are needed. In this overview, circular CES distributions are surveyed, some new results are derived and their applications e.g., in radar and array signal processing are discussed 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. A generalization of ML-estimators, the M-estimators of the scatter matrix, are also discussed and asymptotic analysis is provided. Applications of CES distributions and the adaptive signal processors based on ML- and M-estimators of the scatter matrix are illustrated in radar detection problems and in array signal processing applications for Direction-of-Arrival (DOA) estimation and beamforming. Furthermore, experimental validation of the usefulness of CES distributions for modelling real radar data is given.
392 citations
TL;DR: Simulation experiments are provided that show the benefits of the proposed cyclostationary approach compared to energy detection, the importance of collaboration among spatially displaced secondary users for overcoming shadowing and fading effects, as well as the reliable performance of the suggested algorithms even in very low signal-to-noise ratio (SNR) regimes and under strict communication rate constraints for collaboration overhead.
Abstract: This paper proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. An existing statistical hypothesis test for the presence of cyclostationarity is extended to multiple cyclic frequencies and its asymptotic distributions are established. Collaborative test statistics are 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 approximation of the asymptotic distribution of the censored FC test statistic is proposed. The proposed tests are nonparametric in the sense that no assumptions on data or noise distributions are required. In addition, the tests allow dichotomizing between the desired signal and interference. Simulation experiments are provided that show the benefits of the proposed cyclostationary approach compared to energy detection, the importance of collaboration among spatially displaced secondary users for overcoming shadowing and fading effects, as well as the reliable performance of the proposed algorithms even in very low signal-to-noise ratio (SNR) regimes and under strict communication rate constraints for collaboration overhead.
359 citations
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Journal Article•
28,685 citations
6,278 citations
TL;DR: In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented and the cooperative sensing concept and its various forms are explained.
Abstract: The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.
4,812 citations
31 Aug 2012
TL;DR: A statistical generative model called independent component analysis is discussed, which shows how sparse coding can be interpreted as providing a Bayesian prior, and answers some questions which were not properly answered in the sparse coding framework.
Abstract: Independent component models have gained increasing interest in various fields of applications in recent years. The basic independent component model is a semiparametric model assuming that a p-variate observed random vector is a linear transformation of an unobserved vector of p independent latent variables. This linear transformation is given by an unknown mixing matrix, and one of the main objectives of independent component analysis (ICA) is to estimate an unmixing matrix by means of which the latent variables can be recovered. In this article, we discuss the basic independent component model in detail, define the concepts and analysis tools carefully, and consider two families of ICA estimates. The statistical properties (consistency, asymptotic normality, efficiency, robustness) of the estimates can be analyzed and compared via the so called gain matrices. Some extensions of the basic independent component model, such as models with additive noise or models with dependent observations, are briefly discussed. The article ends with a short example.
Keywords:
blind source separation;
fastICA;
independent component model;
independent subspace analysis;
mixing matrix;
overcomplete ICA;
undercomplete ICA;
unmixing matrix
2,976 citations