This article deals with the blind detection and identification of error correcting codes. More precisely, we aim at estimating the code length from a noisy bits stream in a non-cooperative context (e.g. Electronic Warfare). In this context, an eavesdropper may intercept a communication. To retrieve the sent information, one can consider identifying the channel code parameters. The method proposed here relies on a statistical analysis of a Euclidean distance matrix. It allows to estimate the code length. We address a process based on soft bits information with no a priori on the encoder used. Finally, we compare our method with a well known algorithm based on Gauss-Jordan elimination.

In RF receivers nonlinearities are inherent to analog processing. This is the result of strong signals presence close to the bandwidth of the signal of interest, or a power excess of this signal. Both cases greatly deteriorate the receiver bit-error-rate. Most advanced nonlinearities equalization methods rely on subtraction mechanisms of the modeled intermodulation terms. In this article, we propose a proof of concept for a novel technique to limit the harmful effects of nonlinearities. It consists in making a measure of intermodulation terms power, thanks to a cyclostationary sensing mechanism. And then, to dynamically adapt receivers parameters to make it works in a linear regime. We detail principles of that method and develop the theoretical analysis of detection. Thanks to simulations, we show that this method is reliable and allows a nonlinearity detection 16dB below the compression point. This work was conducted in the scope of high end radio such as professional mobile radios (PMR) receiver.

This paper considers the problem of detecting a QPSK communication signal on carrier. We propose a method to perform the detection thanks to second order cyclostationarity theory. It is well known that for such a signal, there is no cyclic frequency multiple of the studied signal carrier frequency. Hence, the basic method of second order cyclic-moments energy measurement is unable to detect any energy directly linked to the signal carrier. In this article, we propose a novel criterion based on second order cyclic-moments that exploits the convergence speed of the cyclic autocorrelation function estimator. We show that for a modulated QPSK signal the cyclic-correlation converges to zero but not in the same way if the cyclic frequency is a multiple of the carrier frequency or not. We develop a statistical test and derive the asymptotic probability density function of the criterion to propose a detection threshold. System performance simulation results are then evaluated by Monte Carlo simulations and compared to the results of fourth order nonlinear transformation method.

This paper deals with a new challenge for cognitive opportunistic receivers : base station number of antennas estimation. This knowledge allows to get a better understanding of the Signal to Noise Ratio and of the achievable bit-rate with the BS. This task is achieved by taking benefits of the orthogonality between the pilots patterns used by the base station antennas and making use of a the Pilot Induced Cyclo-stationarity detector proposed in [1]. To the best of our knowledge our proposed algorithm is the first technique that can estimate any number of antennas using only one antenna at reception and without any knowledge of the pilot sequence.

In wireless communication, the discovery of the surrounding access points is crucial to provide seamless connectivity to mobile users. In IEEE 802.11, this discovery process is performed by passive and active scanning functions. For both, timers are usually constant (within the 802.11 driver) and their configuration affects the two main scanning performance metrics, i.e., scanning latency and scanning failure. In order to manage this trade-off, we propose a couple of adaptive scanning algorithms that are aware of the access point's signal power and congestion level using cross-layer information from the physical layer. As shown by experimentation in a real testbed, this allows a faster topology discovery while mostly reducing the failure rate.

The problem of frame synchronization of non-binary Low-Density Parity-Check (LDPC) codes is considered in this paper. We propose two techniques of blind frame synchronization that are based on syndrome calculation over the Galois Field GF(q). While the first technique computes hard values of the syndrome, the second one deals with probabilities. Furthermore, we present in this paper a theoretical analysis on the proposed synchronization criteria. This analysis is validated by comparison to simulated results. Although non-binary LDPC codes have short lengths and their decoding is very effective even at low Signal-to-Noise Ratio (SNR), simulation results have shown that the proposed Non-Binary Soft Syndrome (NBSS) based synchronization algorithm is well adapted to such codes. The Frame Error Rate (FER) curves obtained after synchronization and decoding are very close to the perfect synchronization case.

We present two new noise variance estimation methods for OFDMA signals transmitted through an unknown multipath fading channel. We focus on blind estimation as it does not require any pilot sequences and is therefore applicable to contexts, such as cognitive radio for instance, where little prior signal knowledge is available. The two estimators are respectively based on the time-frequency sparsity of OFDMA signals and on the redundancy induced by the cyclic prefix. Numerical simulations compare the performance of the two algorithms and highlight their complementarity.

We present in this paper a blind frame synchronization method based on the adaptation of the parity check matrix of the code. The blind synchronizer is initially based on the calculation of the log-likelihood ratios (LLR) of the syndrome elements, obtained using the parity check matrix of the code. Before applying our synchronization procedure, we propose in this paper to rearrange the parity check matrix of the code according to the reliability of the received symbols as previously introduced for decoding linear block codes with high density parity check matrix. Simulation results show that the frame error rate (FER) curves obtained after applying the proposed synchronization method to product codes are very close to the ones with perfect synchronization. In addition to its powerful synchronization properties, the main advantage of the proposed synchronization algorithm is its capability of being introduced as a part of the decoder so that no additional material is required for the synchronization step.

In the context of cognitive radio, this paper addresses the challenge of OFDM system identification. We show that it is possible to take advantage of pilot tone structures to perform identification. Pilot subcarrier usage is of great interest since it enables to discriminate OFDM systems that have the same modulation parameters (subcarrier spacing, cyclic prefix duration, etc.). The proposed method relies on the periodic redundancy often induced between pilot symbols. We demonstrate that most OFDM systems (Wifi, WiMAX, DVB-T, etc.) can be identified thanks to this redundancy by conducting a hypothesis test based on second order statistics. Detailed numerical examples demonstrate the efficiency of the proposed identification criterion in various kinds of environments.

We present in this letter a blind frame synchronization method based on a maximum a posteriori probability (MAP) approach. Applied to coded communication systems, this method is based on the calculation of the log-likelihood ratios (LLR) of the syndrome obtained according to the parity check matrix of the code. After presenting the proposed method, we compare it to an existing blind synchronization method previously introduced. Simulation results show that the proposed method outperforms the existing one and presents good performance when applied to codes having a sparse parity check matrix such as low density parity check (LDPC) codes and convolutional codes.

We have recently proposed in a blind frame synchronization method based on a maximum a posteriori (MAP) approach. In this letter, we study the properties of this method and show that this synchronization technique is well suitable for codes having a sparse parity check matrix, such as low-density parity-check (LDPC) codes. We also find the probability distributions involved in our synchronization criterion and expand the analytical expression of the probability of false synchronization. Through computer simulations we validate our theoretical results and show that this synchronization technique has excellent performance when applied to LDPC codes. We also show that this method outperforms another approach of blind frame synchronization that computes hard values of the syndrome instead of its log-likelihood ratios (LLR).

In the context of cognitive radio, system identification is a crucial step towards radio environment awareness. In this paper, we present a new OFDM system identification method based on m-sequence (MS) specific characteristics. Thanks to their good random properties, m-sequences are commonly used in existing standards (such as Wifi or WiMAX) to modulate pilot tones for channel estimation and/or for synchronization purposes. We demonstrate that such sequences show extra-properties relevant to distinguish systems from each other and therefore advocate to generalize their use in a cognitive context. MS signatures are indeed of interest since they are able to discriminate OFDM based systems that have the same modulation parameters (intercarrier spacing, cyclic prefix duration, etc.). In order to detect these signatures, we conduct a hypothesis test based on the MS high order statistics. Detailed numerical examples demonstrate the efficiency of the proposed identification criterion and especially show its benefits compared to classical correlation based methods.

In this paper, we propose a cross layer design which combines the PHYsical and the MAC layers for a distributed wireless underwater acoustic networks. The PHYsical layer is based on a CDMA transmission as used in UMTS systems, reception is done using a RAKE receiver. The MAC layer is a based on the CSMA/CA protocol. As we work in the case of underwater acoustic networks, the propagation delay is much more significant compared to radio channel. Therefore, the use of RTS/CTS used in the CSMA/CA protocol induces an increase in delay. The use of CSMA techniques allows to several nodes to transmit simultaneously through the common channel and without using control sequences RTS/CTS to reserve the medium. We show in this paper that our proposition solves the problem of collision present in the case of CSMA/CA. The comparison between our cross layer approach and the CSMA/CA is done in term of available throughput of nodes and average delay of transmission.

In decentralized communication schemes such as ad-hoc networks, a major challenge concerns the synchronization and detection of users sending information simultaneously. Classical synchronisation techniques based on training sequences decrease dramatically the spectral efficiency and are rarely applicable in non-cooperative settings. In this contribution, we propose an efficient technique for blind detection in the context of block coded interleaved division multiple access (IDMA). Interestingly, without any additional dimension (space, time or frequency), the users can be fully separated when using low rate LDPC codes with the same interleavers (which is a new feature compared to classical IDMA schemes). Results, in the context of additive white Gaussian noise (AWGN) and Rayleigh flat fading channels, demonstrate the potential of the method in the multi-user setting.

In this paper, we consider MAC (media access control) protocols appropriate to the underwater acoustic networks. First, we consider a media access method based on the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol used in the wireless local area networks IEEE 802.11 (WiFi). In the underwater acoustic channel, the acoustic wave propagates very slowly with regard to the electromagnetic wave (about 1500 m s ). Therefore the propagation delay is significant and thus collisions present a high cost considering the delay of transmission and the available throughput. To avoid this problem, we consider a second protocol in which we integrate a WAIT command [1]. Finally we integrate to our proposition a power control mechanism in order to increase network performance (delay, throughput). The performance evaluation of the three propositions has been done in terms of available throughput of the underwater sensors, delay of transmission and collision probability. The proposed simulation system model is detailed.

Interleaving is a key component of many digital communication systems involving error correction schemes. It provides a form of time diversity to guard against bursts of errors. Recently, interleavers have become an even more integral part of the code design itself, if we consider for example turbo and turbo-like codes. In a non-cooperative context, such as passive listening, it is a challenging problem to estimate the interleaver parameters. In this paper we propose an algorithm that allows us to estimate the parameters of the interleaver at the output of a binary symmetric channel and to locate the codewords in the interleaved block. This gives us some clues about the interleaving function used.

A blind source separation problem in a cyclostationary context is addressed. The mixture stems from several telecommunication signals, the baud-rates of which are possible different. Cost functions are introduced, the optimization of which achieves the equalization for a user (i.e. estimation of the baud-rate and the sequence of symbols). The method is iterated by implementing a deflation. The theoretical results are validated by simulations

The blind estimation of the symbol period of an unknown linearly modulated signal is addressed. We propose an original methodology relying on the concept of blind deconvolution, which does not suffer from the drawbacks of the classical approaches relying upon the cyclostationarity of the received signal. Under suitable technical conditions, we show that the optimization of certain cost functions leads to the identification of the symbol rate. Simulation results illustrate the excellent performance of the method.

Blind channel estimation for periodic sequence DS-CDMA systems can be cast into the framework of "structured" blind estimation of multi-input/multi-output (MIMO) FIR systems, where the structure is imposed by the user's signatures. The well known subspace method can in particular be adapted to this context, but it suffers from a lack of robustness to an over-determination of the order of the channel. In a previous work, we showed that the use a structured linear prediction approach can overcome this drawback. However, the statistical performance of the corresponding estimate are disappointing. In this paper, we concentrate on the forward link channel estimation, and propose to use a weighted linear prediction approach. The optimal weighting matrix is in practice quite difficult to use. We therefore propose a sub-optimum matrix, leading to a quite simple estimation algorithm, and which is shown to have optimum performance when the signal to noise ratio converges to +/spl infin/. Some simulation results confirm the potential of the new approach.