Vincent Le Nir

Blind CP-OFDM and ZP-OFDM parameter estimation in frequency selective channels

A cognitive radio system needs accurate knowledge of the radio spectrum it operates in. Blind modulation recognition techniques have been proposed to discriminate between single-carrier and multicarrier modulations and to estimate their parameters. Some powerful techniques use autocorrelation- and cyclic autocorrelation-based features of the transmitted signal applying to OFDM signals using a Cyclic Prefix time guard interval (CP-OFDM). In this paper, we propose a blind parameter estimation technique based on a power autocorrelation feature applying to OFDM signals using a Zero Padding time guard interval (ZP-OFDM) which in particular excludes the use of the autocorrelation- and cyclic autocorrelation-based techniques. The proposed technique leads to an efficient estimation of the symbol duration and zero padding duration in frequency selective channels, and is insensitive to receiver phase and frequency offsets. Simulation results are given for WiMAX and WiMedia signals using realistic Stanford University Interim (SUI) and Ultra-Wideband (UWB) IEEE 802.15.4a channel models, respectively.

Jamming mitigation in cognitive radio networks using a modified Q-learning algorithm

The jamming attack is one of the most severe threats in cognitive radio networks, because it can lead to network degradation and even denial of service. However, a cognitive radio can exploit its ability of dynamic spectrum access and its learning capabilities to avoid jammed channels. In this paper, we study how Q-learning can be used to learn the jammer strategy in order to pro-actively avoid jammed channels. The problem with Q-learning is that it needs a long training period to learn the behavior of the jammer. To address the above concern, we take advantage of the wideband spectrum sensing capabilities of the cognitive radio to speed up the learning process and we make advantage of the already learned information to minimize the number of collisions with the jammer during training. The effectiveness of this modified algorithm is evaluated by simulations in the presence of different jamming strategies and the simulation results are compared to the original Q-learning algorithm applied to the same scenarios.

Blind coarse timing offset estimation for CP-OFDM and ZP-OFDM transmission over frequency selective channels

We present a blind coarse timing offset estimation technique for CP-OFDM and ZP-OFDM transmission over frequency selective channels. The technique exploits the cyclic prefix or zero-padding structure to estimate the starting position of the OFDM symbols without requiring any additional pilots. Simulation results are performed on various channel models with timing and frequency offsets. The presented technique is compared with the autocorrelation-based technique and various techniques in frequency selective channels. Our algorithm shows better performance results than those of the autocorrelation-based technique in NLOS channels, where the most predominant channel path is usually not the first arrival path.

Autonomous dynamic spectrum management for coexistence of multiple cognitive tactical radio networks

In this paper, dynamic spectrum management is studied for multiple cognitive tactical radio networks coexisting in the same area. A tactical radio network is composed of a transmitter which broadcasts the same information to its multiple receivers. First, we consider the problem of power minimization subject to a minimum rate constraint and a spectral mask constraint for a single tactical radio network with multiple receivers over parallel channels (parallel multicast channels). Then, we extend the iterative waterfilling algorithm to multiple receivers for the coexistence of multiple cognitive tactical radio networks, meaning that there is no cooperation between the different networks. The power allocation is performed autonomously at the transmit side assuming knowledge of the noise variances and channel variations of the network. Simulation results show that the proposed algorithm is very robust in satisfying these constraints while minimizing the overall power in various scenarios.

Pseudo-Random Binary Sequence Selection for Delay and Add Direct Sequence Spread Spectrum Modulation Scheme

Recently, correlation delay shift keying (CDSK) has been proposed as a modulation scheme for noncoherent detection which inherits the advantages of conventional spread-spectrum communications using a chaotic reference signal. The CDSK modulation scheme transmits the sum of a chaotic reference signal with its delayed modulated version. In this paper, we consider the utilisation of pseudo-random binary sequences (PRBS) instead of chaotic reference signals. This new modulation scheme is defined as the delay and add direct sequence (DADS) modulation scheme. DADS offers some interesting properties compared to CDSK, mainly the possibility to select some PRBS which improves the BER performance. To this end, a new criterion for PRBS selection is proposed. Theoretical analysis and simulation results show that the BER performance of CDSK is comparable to DADS with arbitrary PRBS, however the DADS performance can be improved by 3 dB with PRBS selection.

Simple iterative receivers for MIMO LP-OFDM systems

In this paper,Lp-ofdm is combined with differentMimo schemes in order to improve performance in terms of diversity gain and to exploit capacity brought by theMimo channel. The original contribution is the development of a generic iterative receiver designed forLp mimo transmission able to work whatever the antenna configuration and the spatial coding scheme. By using a globalMmse criterion, interference terms coming from space-time coding and linear precoding are jointly treated leading to a very good trade-off between performance and complexity compared to trellis based detectors particularly for high order modulations, high number of antennas and/or large size of precoding matrices.RésuméDans cet article, le précodage linéaire est associé à différents schémas multi-antennes dans un contexteOfdm afin d’améliorer les performances en termes d’exploitation de diversité et de capacité offertes par les canaux multi-antennes. La contribution originale est de proposer un récepteur itératif générique pour schémasLp-mimo pouvant s’adapter à n’importe quelle configuration d’antennes et de codage spatio-temporel. Les termes d’interférence qui proviennent du précodage linéaire et du codage spatio-temporel sont traités conjointement en utilisant un critère de minimisation de l’erreur quadratique moyenne globale. Le récepteur obtenu permet d’obtenir un très bon compromis entre les performances et la complexité de mise en ?uvre comparé à des détecteurs à base de treillis en particulier pour les modulations à nombre d’états élevé, des systèmes à plusieurs antennes d’émission et de réception et/ou des grandes tailles de matrice de précodage.

Throughput Optimization for Cooperative Spectrum Sensing in Cognitive Radio Networks

In this paper, the channel utilization (throughput vs. sensing time relationship) is analyzed for cooperative spectrum sensing under different combining rules and scenarios. The combining rules considered in this study are the OR hard combining rule, the AND hard combining rule, the Equal Gain Soft combining rule and the two-bit quantized (softened hard) combining rule. For all combining rules, the detection performance, with a Gaussian distribution assumption, is expressed in two different scenarios, CPUP (Constant Primary User Protection) and CSUSU (Constant Secondary User Spectrum Usability). A comparison, based on simulations, is conducted between these proposed schemes in both scenarios, in terms of detection performance and throughput capacity of the CR network.

Closed Form Expression of the Saddle Point in Cognitive Radio and Jammer Power Allocation Game

In this paper, we study the power allocation problem for a cognitive radio in the presence of a smart jammer over parallel Gaussian channels. The objective of the jammer is to minimize the total capacity achievable by the cognitive radio. We model the interaction between the two players as a zero-sum game, for which we derive the saddle point closed form expression. First, we start by solving each player’s unilateral game to find its optimal power allocation. These games will be played iteratively until reaching the Nash equilibrium. It turns out that it is possible to develop analytical expressions for the optimal strategies characterizing the saddle point of this minimax problem, under certain condition. The analytic expressions will be compared to the simulation results of the Nash equilibrium.

Consensus algorithms for distributed spectrum sensing based on goodness of fit test in cognitive radio networks

In this paper, we study a consensus algorithm for distributed spectrum sensing (DSS) in cognitive radio networks (CRN) integrating a Goodness of Fit based spectrum sensing scheme. Existing work in this area often applies energy detector as a local spectrum sensing method for DSS, however in this case one needs to make the assumption that the noise level is the same at every node in the network, otherwise the threshold can not be set properly. In GoF based spectrum sensing, the threshold for the binary test depends only on the desired false alarm probability and not on the local noise powers. Motivated by this nice feature of GoF based spectrum sensing, we consider the goodness of fit (GoF) test statistic to be exchanged among cognitive radio (CR) users (consensus variable) instead of the energy. Moreover, a weighted consensus based DSS scheme is proposed and compared to the conventional consensus based on DSS. Simulations are conducted to show the effectiveness of the consensus algorithm based on GoF test.

Distributed power allocation for parallel broadcast channels with only common information in cognitive tactical radio networks

A tactical radio network is a radio network in which a transmitter broadcasts the same information to its receivers. In this paper, dynamic spectrum management is studied for multiple cognitive tactical radio networks coexisting in the same area. First, we consider the problem of common rate maximization subject to a total power constraint for a single tactical radio network having multiple receivers and using parallel subchannels (parallel multicast channels). Mathematical derivations show that the optimal power allocation can be found in closed form under multiple hypothesis testing. An outer loop can be used to minimize the power subject to a common rate constraint. Then, we extend the iterative water-filling algorithm to the coexistence of multiple cognitive tactical radio networks without requiring any cooperation between the different networks. The power allocation is performed autonomously at the transmit side assuming knowledge of the noise variances and channel variations of the network. Simulation results show that the proposed algorithm is very robust in satisfying these constraints while minimizing the overall power in various scenarios.