IEMN

Modulation type is one of the most important characteristics used in signal waveform identification. In this paper, an algorithm for automatic digital modulation recognition is proposed. The proposed algorithm is verified using higher-order statistical moments (HOM) of continuous wavelet transform (CWT) as a features set. A multilayer feed-forward neural network trained with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate among different M-ary shift keying modulation schemes and the modulation order without any priori signal information. Pre-processing and features subset selection using principal component analysis is used to reduce the network complexity and to improve the classifier's performance. The proposed algorithm is evaluated through confusion matrix and false recognition probability. The proposed classifier is shown to be capable of recognizing the modulation scheme with high accuracy over wide signal-to-noise ratio (SNR) range over both additive white Gaussian noise (AWGN) and different fading channels.

Modulation type is one of the most important characteristics used in signal waveform identification and classification. In this paper, an algorithm for blind digital modulation identification for multiple-input multiple-output (MIMO) systems is proposed. The suggested algorithm is verified using higher order statistical moments and cumulants of the received signal. A multi-layer neural network trained with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate among different M-ary shift keying linear modulation types and the modulation order without any priori signal information. This study covers different MIMO systems with and without channel state information (CSI). The proposed classifier is evaluated through the probability of identification where we show that our proposed algorithm is capable of identifying the modulation scheme with high accuracy in excellent signal-to-noise ratio (SNR) range.

Abstract: The sparse code multiple access (SCMA) is one of the promoting candidate of code-domain non-orthogonal multiple access (CD-NOMA) for the upcoming generations of wireless communications systems, and it has been actively investigated in recent years. The key distinguishing feature of SCMA comes from the gain of its multi-dimensional sparse codebooks. Nevertheless, all users have not the same business requirements, and their physical layer needs depend on many factors such as the maximum allowed delay, the required rate and the targeted quality of service. In this paper, an adaptive SCMA scheme is proposed to tackle this problem. The idea is to divide users into different groups such as an adaptive designed codebook is allocated to each group. Unlike the traditional SCMA, the sparsity degree, the constellation size, and the allocated power per user, can be adapted to each group requirements in order to increase the overall performance of an uplink SCMA system. Simulation resu...

The fifth-generation (5G) of cellular networks and beyond requires massive connectivity, high data rates, and low latency. Millimeter-wave (mmWave) communications is a key 5G enabling technology to meet these requirements thanks to its technical potentials that can be integrated with other 5G enablers such as ultra-dense networks (UDNs) and massive multiple-input-multiple-output (massive MIMO) systems. However, some technical challenges, which are mainly related to specific characteristics of mmWave propagation, must be addressed. All the aforementioned points will be discussed in this article before presenting the different existing architectures of massive MIMO mmWave systems. This survey mainly aims at presenting a comprehensive state-of-the-art review of the channel estimation techniques associated with the different mmWave system architectures. Subsequently, we will provide a comparison among existing solutions in terms of their respective benefits and shortcomings. Finally, some open directions of research are discussed, and challenges that wait to be met are pointed out. INDEX TERMS Millimeter-wave communications, massive MIMO, channel estimation, 5G, cellular systems, spatial channel model, lens antenna array, hybrid architecture, few-bit ADCs, compressive sensing, beamforming. NOMENCLATURE 2D

The rapid development of information and wireless communication technologies together with the large increase in the number of end-users have made the radio spectrum more crowded than ever. Besides, providing a stable and reliable service is challenging, as electromagnetic environments are evolving and becoming more sophisticated. Accordingly, there is an urgent need for more reliable and intelligent communication systems that can improve the spectrum efficiency and the quality of service to provide agile management of network resources, so as to better meet the needs of future wireless users. Specifically, Automatic Modulation Recognition (AMR) plays an essential role in most intelligent communication systems especially with the emergence of Software Defined Radio (SDR). AMR is an indispensable task while performing spectrum sensing in Cognitive Radio (CR). Thanks to the significant advancements in Deep Learning (DL) applications, new and powerful tools have been provided which can tackle problems in this space. Thus, today, integrating DL models into AMR has gained the attention of many researchers. This work aims to provide a comprehensive state-of-the-art review of the most recent Machine Learning (ML) based AMR methods for Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) systems. Furthermore, the architecture of each model will be identified along with a detailed comparison in terms of specifications and performance. Finally, an outline of the open problems, challenges, and potential research directions is provided along with discussion and conclusion.

Wireless communication systems must answer drastic requirements, such as reliability, availability and interoperability in vehicular applications. Cognitive radio system is suitable technology able to answer these needs. It allows dynamic spectrum allocation and very often spectrum reuse especially in rural areas. In consequence, it require an accurate knowledge of the radio spectrum in which it operates while the vehicle is moving. Focusing on MIMO-MC-DS-CDMA systems, we present a blind technique that aims at recovering both spectral and temporal signal parameters. The proposed approach leads to a fast efficient parameters estimation, insensitive to receiver phase and frequency offsets, which is suitable for vehicular applications.

Spherical microphone arrays are widespread nowadays, especially with the advent of techniques for decomposing acoustic fields on the basis of spherical harmonics (i.e. Ambisonics). In these approaches, the corresponding arrays require a quadratically increasing number of microphones as the degree of the components to be estimated increases. Besides, for some applications, it is unnecessary to represent the whole solid angle of the sound field from the array point of view: for instance as soon as the array is placed near the boundaries of the acoustic field of study (i.e. walls in a room). To tackle these issues, one proposes a geometry which uses the acoustic rigid boundary condition at room walls to decrease the number of required microphones. With one eighth of a sphere array placed in the corner of a room, only certain spherical harmonics are required for the sound pressure field decomposition, and the microphone number can drop up to 8 times lower when compared to the full spher...

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 spectrumsensing 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.

Cosine Modulated Filter Banks (MFB) have been widely studied [MAL92, KOI92, MAU94] and are successfully used in signal and image processing. A perfect reconstruction factorization of filter banks based on cosine modulation of a linear phase prototype filter of ...

This paper proposes a layered video transmission scheme to extend the coverage area for DSL video delivery. The proposed architecture is based on a joint source-channel coding approach, and combines layered video transcoding with unequal error protection using hierarchical multi-carrier transmission. Based on a new image quality metric, the developed method automatically determines the optimal system parameters in terms of end-user perceived quality. Simulation results show that the proposed quality-oriented video delivery architecture extends the coverage area for DSL video distribution significantly for the end user, while providing more robust video services. Index Terms-Digital subscriber line (DSL), image quality, joint source channel coding (JSCC), layered video transmission, transcoding, unequal error protection (UEP).

Dans le cadre d'une transmission vidéo MPEG-2 sur ligne téléphonique par la technologie ADSL, nous présentons un système de codage conjoint source-canal par lequel les informations les plus pertinentes vis-à-vis de la qualité visuelle à la réception sont surprotégées en contrepartie d'une moins bonne protection pour les données secondaires. Nous montrons la faisabilité d'un tel système et ses performances en terme de taux d'erreur binaire atteints sur une ligne de test ADSL. Mots Clef Transmission vidéo MPEG-2, ADSL, Data Partitionning, modulation multiporteuse DMT, transfert de puissance, qualité de service. 2 Rappel des principes de base 2.1 Le mode Data Partitionning de la norme MPEG-2 Le standard de compression d'images MPEG-2, normalisée par l'ISO [5] est basée sur l'emploi de la

In this paper, we propose a methodology for estimating the statistics of the intercell interference power in the downlink of a multicellular network. We first establish an analytical expression for the probability law of the interference power when only Rayleigh multipath fading is considered. Next, focusing on a propagation environment where small-scale Rayleigh fading as well as large-scale effects, including attenuation with distance and lognormal shadowing, are taken into consideration, we elaborate a semi-analytical method to build up the histogram of the interference power distribution. From the results obtained for this combined small- and large-scale fading context, we then develop a statistical model for the interference power distribution. The interest of this model lies in the fact that it can be applied to a large range of values of the shadowing parameter. The proposed methods can also be easily extended to other types of networks.

Equipe de reclierche associée au CNRS BP46-38402 Saint-Martjn-d'jidres-Tél. (76) 44.82.45 ABSTRACT Auto and cross spectral analysis is the basic tool for geophysicist in order to study resonances of the magnetosphere using natural electromagnetic waves recorded in several places. The comparisons of these records must be made by autoregressive (AR) spectral estimators because the signal duration is short. For this application we show that the presentation of AR autospectrmi by the position of the poles of the z transform is interresting. We make a direct comparison of the poles position for signal recorded at different places. Finally we present the influence of the choice of the order and discuss the particularities of the two dimensional autoregressive analysis. 1-INT)DUCTION Parametric methods have been intensively studied for one dimension A.Rl [1] [51 and two dimensional signal AP2 [2] and a lot of applications have been made in many domains such as geophysics, sismology and submarine acoustic. We study the use of these methods for a specific geophysical application the diagnosis of the magnetosphere.

Although the degree of protection for transmitted bits offered by Multi-Resolution Modulation (MRM) depends on the bits' perceptual importance, the channel capacity concept introduced by Shannon intentionally excludes the notion of information importance. In response to this exclusion, the authors introduce an alternate information theory-based quantity, called "weighted channel capacity", which explicitly integrates the notion of information importance and which can be used as an MRM optimization criterion. To accomplish this, the chain rule of mutual information was used to weight the influence of each bit according to its perceptual importance. Numerical results for the "weighted channel capacity" quantity are provided for the Hierarchical Pulse Amplitude Modulation (H-PAM) class on the AWGN channel.

It is well known that asynchronous impulsive noise is the main source of distortion that drastically affects the powerline communications (PLC) performance. Recently, more realistic models have been proposed in the literature which better fit the physical properties of real impulsive noise. In this paper, we consider a pulse train model and propose a thorough analysis of the impact of impulsive noise parameters, namely impulse width and amplitude as well as inter-arrival time, on the bit error rate (BER) performance of orthogonal frequency division multiplexing (OFDM) broadband PLC. A comparison with the conventional Bernoulli-Gaussian (BG) impulsive noise model exhibits the difference between the two approaches, showing the necessity of more realistic models.

In this paper, we present an original image quality metric for open-loop transcoding architectures based on frequency selective transmission. The proposed metric computes the normalized HVS-weighted mean squared error (NWMSE) between the reference digital video compressed bitstream, and its transcoded version. This computation is performed directly from the quantized DCT coefficients of the compressed bitstream. The resulting MSE error is implicitly weighted by the HVS sensitivity by considering the MPEG perceptual coding properties. Finally, rate control and error propagation are also taken into account, in order to improve transcoded video quality assessment. Experimental results are given which show that the proposed NWMSE metric correlates well with a conventional WPSNR. This validates the proposed assumptions used for the NWMSE computation. The major advantage of the approach is its simplicity since it does not need to perform the complete decoding of the compressed bitstream. Hence, the NWMSE metric is highly suited for real-time video applications.

Thanks to their high bandwidth ability, Asymmetric Digital Subscriber Lines (ADSL) and Very high speed DSL (VDSL) am access technologies that permit the transmission of several applications simultaneously on telephonic subscriber lines. Considering that these applications may require a different Quality of Service (QoS), and particularly different Bit Error Rates (BER), for transmission, this paper addresses the problem of providing simultaneously two BERs for transmission over a DMT-based ADSL or VDSL link. Both coded and uncoded systems are considered.