Blind Recognition of Linear Space Time Block Codes

©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.International audienceThe blind recognition of communication parameters is a key research issue for commercial and military communication systems. In this paper, we investigate the problem of the blind recognition of Linear Space-Time Block Codes (STBC). To characterize the space time coding, we propose to compute a time-lag correlation of the received samples. Provided the number of transmitters, the noise variance and the symbol timing are well estimated, we show that the theoretical values of the correlation norm only depend on the STBC and are affected by neither the channel nor the symbol modulation. The automatic recognition of the STBC is realized by selecting the STBC which minimizes the distance between the theoretical values and the experimental ones. Simulations show that our method performs well even for low signal to noise ratio (0dB)

Blind Detection of the Number of Communication Signals Under Spatially Correlated Noise by ICA and K-S Tests

©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.International audienceThe issue addressed in this paper is the determination of the number of communication signals in a sensor array. Most of the available algorithms rely on the spatial uncorrelation of the additive noise. In practice, this condition is rarely satisfied when the receivers are not sufficiently spaced (MIMO communications for example). In this paper, we propose a new method to detect the number of communication signals based on the fact that the signals are independent and non gaussian and that the background noise is gaussian. By using an Independent Component Analysis in conjunction with Kolomogorov-Smirnov (K-S) tests, the method can detect as many communication signals as the number of receiver antennas. Simulations results show that our method performs well in many environments like those with spatially correlated noise

Modulation Recognition for MIMO Communications

International audienceThe blind recognition of communication parameters is an important research topic in both commercial and civilian systems. In this paper, we investigate the blind recognition of the modulation. Currently most part of the existing algorithms assumes that the transmitter uses a single-antenna. This study extends the problem for multiple-antennas (MIMO) systems. We adopt a Maximum Likelihood approach for the blind recognition of the modulation and we consider two different situations. First, we assume the channel knowledge at the receiver side and we expose the optimal solution which is called Average Likelihood Ratio Test (ALRT). Then, we relax this assumption and we propose a second method based on a Hybrid Likelihood Ratio Test (HLRT)

Blind Recognition of Linear Space–Time Block Codes: A Likelihood-Based Approach

International audienceBlind recognition of communication parameters is a research topic of high importance for both military and civilian communication systems. Numerous studies about carrier frequency estimation, modulation recognition as well as channel identification are available in literature. This paper deals with the blind recognition of the space–time block coding (STBC) scheme used in multiple input–multiple-output (MIMO) communication systems. Assuming there is perfect synchronization at the receiver side, this paper proposes three maximum-likelihood (ML)-based approaches for STBC classification: the optimal classifier, the second-order statistic (SOS) classifier, and the code parameter (CP) classifier. While the optimal and the SOS approaches require ideal conditions, the CP classifier is well suited for the blind context where the communication parameters are unknown at the receiver side. Our simulations show that this blind classifier is more easily implemented and yields better performance than those available in literature

Blind Channel Estimation for STBC Systems Using Higher-Order Statistics

International audienceThis paper describes a new blind channel estimation algorithm for Space-Time Block Coded (STBC) systems. The proposed method exploits the statistical independence of sources before space-time encoding. The channel matrix is estimated by minimizing a kurtosis-based cost function after Zero-Forcing equalization. In contrast to subspace or Second-Order Statistics (SOS) approaches, the proposed method is more general since it can be employed for the general class of linear STBCs including Spatial Multiplexing, Orthogonal, quasi-Orthogonal and Non-Orthogonal STBCs. Furthermore, unlike other approaches, the method does not require any modification of the transmitter and, consequently, is well-suited for non-cooperative context. Numerical examples corroborate the performance of the proposed algorithm

Nouvelles interconnexions globales à haut débit pour la réalisation de microsystèmes communicants de type SIP.

4 pagesNational audienceLes microsystèmes intégrés sur puces (SoC) ou en boîtier (SiP) sont actuellement en plein essor et nécessitent le développement de nouvelles structures d'interconnexions reliant les différents blocs fonctionnels entre eux. Nous proposons dans ce papier l'étude du concept d'interconnexion RF par couplage capacitif qui est une solution intéressante pour remplacer les interconnexions classiques. Dans un premier temps nous décrivons le principe de cette technique et montrons à l'aide de simulations circuits de type ADS, la faisabilité de ce concept. Nous présentons ensuite la caractérisation d'un canal de type microruban, réalisée sous HFSS ainsi que son comportement dans le domaine temporel. I. Introductio

New Neural Network Pruning and its application to sonar imagery

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Simultaneous Transmitting–Receiving–Sensing for OFDM-based Full-Duplex Cognitive Radio

International audienceIn this paper, a Transmitting–Receiving–Sensing (TRS) mode of OFDM-based Full-Duplex Cognitive Radio (FD-CR) is proposed. The new mode aims at monitoring the Primary User (PU) activities on the operating channel while establishing an in-band full-duplex communication between two communicating Secondary Users (SUs), i.e. SUs transmit and receive simultaneously on the same frequency band. Assuming that the primary activity covers all the operating band when PU is active, Spectrum Sensing is performed on some Sub-Carriers (SCs) which are neutralized by the two communicating SUs. Letting some SCs null by both SUs helps to accurately performing the spectrum sensing on these SCs since no residual self-interference neither secondary transmission are present. When PU is detected on these SCs, then we consider that he becomes active again; Then SUs should vacate the channel. For the proposed mode, false alarm, detection and collision probabilities are derived in addition to the throughput rate. An optimal selection of the sensing SCs per OFDM symbol is derived with respect to a maximal tolerable rate of collision between PU and SU transmission. Numerical results corroborate the effectiveness of our proposed mode in terms of the PU awareness and the secondary throughput rate

Blind Detection of Cyclostationary Features in the Context of Cognitive Radio

International audienceThe methods of dynamic access to spectrumdeveloped in Cognitive Radio require efficient and robustspectrum detectors. Most of these detectors suffer fromfour main limits: the computational cost required forthe detection procedure; the need of prior knowledge ofPrimary User’s (PU) signal features; the poor performancesobtained in low SNR (Signal to Noise Ratio) environment;finding an optimal detection threshold is a crucial issue.In this paper, we propose a blind detection method basedon the cyclostationary features of communication signalsto overcome the four limits of spectrum sensors. In orderto reduce the computational cost, the FFT AccumulationMethod has been adjusted to estimate the cyclic spectrumof the intercepted signal. Then, the spectrum coherenceprinciple is used to catch the periodicity hidden in thecyclic autocorrelation function of this signal. The hiddenperiodicity is revealed by the crest factor of the cyclicdomain profile. The detection of PU’s signal is achieved bycomparing the embedded periodicity level with a predeterminedthreshold related to the crest factor. This thresholdvaries randomly dependent on the SNR. Then, we havemodelized the distribution law of the threshold in orderto select the optimal value. Using the crest factor of thecyclic domain profile as a detection criterion has permittedto develop a spectrum sensor which is able to work in ablind context. Simulation results corroborate the efficiencyand robustness of the proposed detector compared with theclassical Energy Detector

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

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