Roland Gautier

Blind recovery of k/n rate convolutional encoders in a noisy environment

In order to enhance the reliability of digital transmissions, error correcting codes are used in every digital communication system. To meet the new constraints of data rate or reliability, new coding schemes are currently being developed. Therefore, digital communication systems are in perpetual evolution and it is becoming very difficult to remain compatible with all standards used. A cognitive radio system seems to provide an interesting solution to this problem: the conception of an intelligent receiver able to adapt itself to a specific transmission context. This article presents a new algorithm dedicated to the blind recognition of convolutional encoders in the general k/n rate case. After a brief recall of convolutional code and dual code properties, a new iterative method dedicated to the blind estimation of convolutional encoders in a noisy context is developed. Finally, case studies are presented to illustrate the performances of our blind identification method.

Dual Code Method for Blind Identification of Convolutional Encoder for Cognitive Radio Receiver Design

Digital communication systems are in perpetual evolution in order to respond to the new user expectations and to new applications transmissions constraints, in term of data rate or reliability. With this fast development of new communication standards, it becomes very difficult for users and also for communications devices producers, to stay compatible with all standards used and with the oncoming ones. For that reason, cognitive radio systems seem to provide an interesting solution to this problem. The conception of intelligent receiver able to adapt itself to a specific transmission context and to blindly estimate the transmitter parameters is a promising solution for the future. In such context, new coding schemes like turbocodes, Low-Density Parity-Check (LDPC) or concatenated codes are developed to increase transmission robustness without significant degradation of the data rate. It is why we have developed a method, described in this paper, dedicated to the blind identification of convolutional encoders usually used in many standards. Moreover, an analysis of the method performances is detailed.

Blind synchronization and sequences identification in CDMA transmissions

Blind sequences estimation methods, which work without prior knowledge about the transmitter, have been proposed in M.K. Tsatsanis and G.B. Giannakis (1997), G. Burel and C. Boulder (2001), and G. Burel and C. Boulder (2001); but they are restricted to a single-user context. Here, we extend the approach originally proposed in G. Burel and C. Boulder (2001) to the multi-user context. We have developed a fast and efficient blind synchronization criterion based on the behavior of the FROBENIUS square norm of a submatrix that scans the intercepted signal correlation matrix. By using eigenanalysis techniques and theoretical linear algebra results, we prove that the maxima of this criterion correspond to the synchronization times with transmitters. Then, eigenanalysis techniques allow to estimate the spreading sequences. Eigenanalysis was associated with additional processing modules aimed at solving dephasing problems due to the transmission channel.

Algebraic method for blind recovery of punctured convolutional encoders from an erroneous bitstream

To enhance the quality of transmissions, all digital communication systems use error-correcting codes. By introducing some redundancy in the informative binary data stream, they allow one to better withstand channel impairments. The design of new coding schemes leads to a perpetual evolution of the digital communication systems and, thus, cognitive radio receivers have to be designed. Such receivers will be able to blind estimate the transmitter parameters. In this study, an algebraic method dedicated to the blind identification of punctured convolutional encoders is presented. The blind identification of such encoders is of great interest, because convolutional encoders are embedded in most digital transmission systems where the puncturing principle is used to increase the code rate to reduce the loss of the information data rate because of the redundancy introduced by the encoder. After a brief recall of the principle of puncturing codes and the construction of the equivalent punctured code, a new method dedicated to the blind identification of both the mother code and the puncturing pattern is developed when the received bits are erroneous. Finally, case studies are presented to illustrate the performances of our blind identification method.

SPC11-2: Blind Multiuser Detection in Multirate CDMA Transmissions Using Fluctuations of Correlation Estimators

This paper deals with the problem of blind multiuser detection in multirate direct-sequence code division multiple access (DS-CDMA). Direct-sequence spread spectrum (DSSS) signals are well-known for their low probability of interception: their statistics are similar to those of a noise; furthermore, they are usually transmitted below the noise level. Here, the method based on the fluctuations of autocorrelation estimators, previously described in a single user context, is extended to multiusers. From the variable spreading length technique, we will evidence an increase of these periodical fluctuations and, on average, a relationship between their peak amplitudes and sequence lengths. A theoretical analysis will show that detection is possible, even with a very low signal-to-noise ratio (SNR) at the detector input. This approach will be illustrated with experimental results. The assessment of symbol periods allows one to start the synchronization process proposed recently, which also permits the determination of the number of interfering users in each group of users transmitting at the same symbol period, thus, conversely at the same data rate.

Multiple-Antenna-Based Blind Spectrum Sensing in the Presence of Impulsive Noise

Cognitive radio (CR) was proposed as a solution to the spectrum scarcity problem. One of the basic functions of any CR is spectrum sensing. Most existing works on spectrum sensing consider the Gaussian noise assumption. In practice, this assumption is not always valid since several existing noise types exhibit non-Gaussian and impulsive behavior. Hence, it is very beneficial to study spectrum sensing in the presence of impulsive noise. In this paper, we propose two new multiple-antenna-based spectrum sensing methods, assuming that the underlying noise follows a symmetric α-stable distribution. This assumption is justified by a distribution fitting of some measurements of the noise acting on the GSM-R antennas onboard trains. The first proposed sensing method is based on the covariation properties of α-stable processes, whereas the second proposed method has the strategy of filtering the corrupted signals before applying a traditional spectrum sensing method. These two methods do not require a priori knowledge about the primary-user signal. Simulation results show that the proposed algorithms provide good spectrum sensing performance in the presence of α-stable distributed impulsive noise.

Blind Identification of Convolutional Encoder Parameters over GF(2m) in the Noiseless Case

In most digital communication systems, error correcting codes are essential to achieve good immunity to channel impairment. Due to the complexity of the encoding process, but especially of the decoding process, most research on error correcting codes is restricted to binary data which are elements of the Galois field GF(2). Reed Solomon codes have been the most commonly used so far as non-binary (GF(q)) error correcting codes. Recently, low complexity decoding algorithms for non-binary LDPC and non-binary turbo-codes have been developed. In this paper, the design of convolutional codes over the non-binary Galois field, with cardinal 2^m (GF(2^m)), is presented in order to blind identify their parameters. An extension of our blind identification method dedicated to convolutional codes over GF(2) is developed for convolutional encoders over GF(2^m). Finally, the impact of Galois field parameters on the blind estimation of convolutional encoder parameters over GF(2^m) is investigated.

Some interesting dual-code properties of convolutional encoder for standards self-recognition

For enhancement of the quality of digital transmissions, standards are in continual evolution, which generates compatibility problems. Cognitive radio systems permit one to solve this problem through the design of intelligent receivers. However, such receivers must be able to adapt themselves to a specific transmission context. This requires the development of new methods in order to blindly estimate error-correcting codes. Coding schemes such as turbocode, composed of convolutional codes, belong to a family of error-correcting codes in use in many standards. In most of the methods designed to identify convolutional encoders the algebraic properties are used implicitly. However usually, these dedicated properties are neither explicated, nor detailed, nor demonstrated. The study reported here investigates the algebraic properties of convolutional encoders, useful for blind recognition methods in the cognitive radio context and more specially the algebraic relationships between different forms of a convolutional code and its corresponding dual code. Moreover, some simulation results are presented to show the relevance of these properties for the blind identification of the convolutional encoder.

Predicted Eigenvalue Threshold Based Spectrum Sensing with Correlated Multiple-Antennas

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple-antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Also, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. A performance comparison between the proposed method and other existing methods is provided. Spatial antenna correlation at the secondary user is a crucial factor for practical systems. The effect of the spatial correlation presence on the different sensing methods is investigated.

Non-parametric multiple-antenna blind spectrum sensing by predicted eigenvalue threshold

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Then, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. Compared with the original PET sensing algorithm, the simplified algorithm significantly reduces the computational complexity without any loss in performance. A performance comparison between the proposed method and other existing methods is provided.