Open Topics

Vol. 76, n° 1-2, January-February 2021
Content available on Springerlink

Time-shift immunity for wireless sensor network based on discrete wavelet packets

C. H. Kizil1, C. Diou1, C. Tanougast1

(1) Université de Lorraine LCOMS, Metz, Lorraine, France

Abstract Wavelet-based Ultra Wide Band communications rely on receiver collecting data simultaneously from many transmitters and without interference thanks to the orthogonality between primitive wavelet packets. Nevertheless, there is a particular case for which the communication fails. Indeed, the time-shift between primitive wavelet packets results in a loss of the orthogonality of these wavelet packets. This paper proposes an asynchronous Impulse Radio-Ultra Wide Band (IR-UWB) transmission suitable in Wireless Sensor networks without any distinction between the transmitters. The originality of the proposed solution is to ensure a time-shift immunity of IR-UWB receivers by finding the unique combination of shifted primitive packets. For this purpose, finding the one zero result of successive subtractions between received and primitive packets is performed. Considering a given wavelet, the proposed solution is able to decode the shifted-mixed primitive packets from multiple transmitters whatever the time-shift between each packets.

Keywords Component · Wavelet · Haar · WSN · Time-shift · IR-UWB

Low-complexity PAPR reductionmethod based on the TLBO
algorithm for an OFDM signal

Tarik HADJ ALI1, Abdelkrim HAMZA1

(1) University of Sciences and Technology Houari Boumediene (USTHB), LISIC Laboratory, FEI, Bab Ezzouar, 16111, Algiers, Algeria

Abstract To reduce the peak-to-average power ratio (PAPR) in the orthogonal frequency division multiplexing (OFDM) transmission technique, several reduction approaches have been used. Among these is the selective mapping (SLM) scheme, and while having been highly adopted, its considerable computational complexity for optimum phase factors search is challenging for practical systems. To overcome this issue with SLM while still reducing the PAPR, a variety of optimization algorithms have been applied for optimal phase factors search. Limitations in all these algorithms include the need for specific parameters for peak performance and a decrease in effectiveness for complicated problems that have a significant number of variables. In this work, a novel optimization algorithm, called teaching-learning–based optimization (TLBO), featuring less computational effort and no algorithm-specific parameter requirement, is applied to reduce the PAPR of the OFDM signal. MATLAB simulation results demonstrate that the proposed TLBO-SLM method efficiently performs better than conventional SLM and previously applied optimization algorithms.

Keywords Orthogonal frequency division multiplexing (OFDM) · Peak-to-average power ratio (PAPR) · Selective mapping (SLM) · Teaching-learning based optimization (TLBO)

Rogue device discrimination in ZigBee networks using wavelet transform and autoencoders

Mohammad Amin Haji Bagheri Fard1, Jean-Yves Chouinard1, Bernard Lebel2

(1) Department of Electrical and Computer Engineering, Université Laval, Quebec City, Canada
(2) Thales Canada Inc. – TRT, Quebec City, Canada

Abstract In modern wireless systems such as ZigBee, sensitive information which is produced by the network is transmitted through different wired or wireless nodes. Providing the requisites of communication between diverse communication system types, such as mobiles, laptops, and desktop computers, does increase the risk of being attacked by outside nodes. Malicious (or unintentional) threats, such as trying to obtain unauthorized accessibility to the network, increase the requirements of data security against the rogue devices trying to tamper with the identity of authorized devices. In such manner, focusing on Radio Frequency Distinct Native Attributes (RF-DNA) of features extracted from physical layer responses (referred to as preambles) of ZigBee devices, a dataset of distinguishable features of all devices can be produced which can be exploited for the detection and rejection of spoofing/rogue devices. Through this procedure, distinction of devices manufactured by the different/same producer(s) can be realized resulting in an improvement of classification system accuracy. The two most challenging problems in initiating RF-DNA are (1) the mechanism of features extraction in the generation of a dataset in the most effective way for model classification and (2) the design of an efficient model for device discrimination of spoofing/rogue devices. In this paper, we analyze the physical layer features of ZigBee devices and present methods based on deep learning algorithms to achieve high classification accuracy, based on wavelet decomposition and on the autoencoder representation of the original dataset.

Keywords Physical layer · Wireless networks · ZigBee devices · Data preamble · RF-DNA · Autoencoder learning · Wavelet-transform

Capacity analysis of maximal ratio combining
over Beaulieu-Xie fading

Veenu Kansal1, Simranjit Singh1

(1) Department of Electronics and Communication Engineering, Punjabi University, Patiala, India

Abstract The present paper analyzes an L-branch maximal ratio combining (MRC) receiver over the Beaulieu-Xie (BX) fading channel. The expression of the probability density function (PDF) of the signal-to-noise ratio (SNR) of an MRC receiver in BX fading is derived by using the characteristic function approach. The obtained PDF is then utilized to calculate the various link-level and system-level parameters. This paper focuses on deriving closed-form expressions for different adaptive transmission techniques based on instantaneous channel state information in BX fading. The accuracy of our derived expressions is verified by comparing them with Monte Carlo simulations.

Keywords MRC diversity . Beaulieu-Xie fading model . Femtocells . Channel capacity

Correction to: Capacity analysis of maximal ratio combining over Beaulieu-Xie fading

Veenu Kansal1, Simranjit Singh1

(1) Department of Electronics and Communication Engineering, Punjabi University, Patiala, India

Downlink channel estimation for millimeter wave communication combining low-rank and sparse structure characteristics

Jin Zhou1

(1) School of Science and Technology, Tianjin University of Finance and Economics, Tianjin 300222, China

Abstract The acquisition of channel state information (CSI) is essential in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. The mmWave channel exhibits sparse scattering characteristics and a meaningful low-rank structure, which can be simultaneously employed to reduce the complexity of channel estimation. Most existing works recover the low-rank structure of channels using nuclear norm theory. However, solving the nuclear norm-based convex problem often leads to a suboptimal solution of the rank minimization problem, thus degrading the accuracy of channel estimation. Previous contributions recover the channel using over-complete dictionary with the assumption that the mmWave channel can be sparsely represented under some dictionary. While over-complete dictionary may increase the computational complexity. To address these problems, we propose a channel estimation framework based on non-convex low-rank approximation and dictionary learning by exploring the joint low-rank and sparse representations of wireless channels. We surrogate the widely used nuclear norm theory with non-convex low-rank approximation method and design a dictionary learning algorithm based on channel feature classification employing deep neural network (DNN). Our simulation results reveal the proposed scheme outperform the conventional dictionary learning algorithm, Bayesian framework algorithm, and compressed sensing-based algorithms.

Keywords Sparse representation . Non-convex theory . Low-rank approximation . Channel state information . Deep neural network

Outage probability of dual-hop cooperative communication networks over the Nakagami-m fading channel with RF energy harvesting

Hoang Duc Vinh1, Tran Manh Hoang2, Pham Thanh Hiep3

(1) Viet Nam Post, Ha Noi, Vietnam
(2) Telecommunication of University, Nha Trang, Vietnam
(3) Le Quy Don Technical University, Ha Noi, Vietnam

Abstract Cooperative communication systems with wireless power transfer are being investigated for future advanced wireless networks. In this research, we propose applying a wireless power transfer to dual-hop cooperative communication systems, in which a relay node harvests the energy from the radiofrequency in order to forward the received signal, and a source node can communicate with a destination node directly or through the selected relay nodes. The system performance is evaluated by an outage probability that is calculated over independent and identically distributed (i.i.d) Nakagami-m distributions in two scenarios, i.e., integer m and arbitrary m. Furthermore, the closed forms of the outage probability expressions are derived in the case of both the amplify-and-forward (AF) and decode-and-forward (DF) protocols. The Monte Carlo method is utilized to simulate the system with the aims of evaluating the system performance and verifying the theoretical analysis. The numerical results highlight that the proposed calculation method and the closed form of the outage probability are accurate. We also compare the system performance of both the AF and DF protocols and show the effect of parameter m on the performance of the system.

Keywords Dual-hop cooperative communication · Energy harvesting · Arbitrary m parameter · Closed-form of outage probability

Approximate ASER analysis of MIMO TAS/MRC networks over Weibull fading channels

Mehmet Bilim1

(1) Department of Electrical & Electronics Engineering, Faculty of Engineering, Nuh Naci Yazgan University, Kayseri, Turkey

Abstract In this paper, the average symbol error rate (ASER) evaluation of multiple-input-multiple-output (MIMO) systems with transmit antenna selection (TAS) and maximal ratio combining (MRC) are analysed under Weibull fading conditions. The impact of additive white Gaussian noise (AWGN) and additive white generalized Gaussian noise (AWGGN) on the ASER evaluation of the MIMO TAS/MRC networks are considered. Closed form approximate and asymptotic ASER expressions of the considered network with AWGN for different quadrature amplitude modulation techniques are derived based on the probability density function approach. The closed-form approximate and asymptotic ASER expressions for the AWGGN case are also obtained. In addition, a comprehensive analysis of the ASER performance for the MIMO TAS/MRC networks is demonstrated by varying the fading parameter values, numbers of transmitter-receiver antennas and constellation size. Finally, the obtained theoretical results are confirmed through the exact simulation results.

Keywords MIMO transmissions . Additive white generalized Gaussian noise . Average symbol error rate

Minimizing the average achievable distortion using multi-layer coding approach in two-hop networks

Sayed Ali Khodam Hoseini1, Soroush Akhlaghi1, Mina Baghani1

(1) Department of Electrical Engineering, Shahed University, Tehran, Iran

Abstract Minimizing the average achievable distortion (AAD) of a Gaussian source at the destination of a two-hop block fading relay channel is studied in this paper. The communication is carried out through the use of a Decode and Forward (DF) relay with no source-destination direct links. The associated receivers of both hops are assumed to be aware of the corresponding channel state information (CSI), while the transmitters are unaware of their corresponding CSI. The current paper explores the effectiveness of incorporating the successive refinement source coding together with multi-layer channel coding in minimizing the AAD. In this regard, the closed form and optimal power allocation policy across code layers of the second hop is derived, and using a proper curve fitting approach, a close-to-optimal power allocation policy associated with the first hop is devised. It is numerically shown that the DF strategy closely follows the Amplify and Forward (AF) relaying, while there is a sizable gap between the AAD of multi-layer coding and single-layer source coding.

Keywords Multi-layer coding · Broadcast approach · Source coding · Rate-distortion theory · Relay-assisted channels · Calculus of variations

Energy-efficient forwarding strategies for wireless sensor networks in fading channels

R. Milocco1, P. Muhlethaler2, S. Boumerdassi3

(1) Grupo Control Automático y Sistemas (GCAyS), Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquén, Argentina
(2) Institut National de Recherche en Informatique et en Automatique, 2 Rue Simone IFF, 75012 Paris, France
(3) Conservatoire National des Arts et Metiers, Centre d’Etude et de Recherche en Informatique et Communications (CNAM/CEDRIC), 292 rue Saint-Martin, 75003 Paris, France

Abstract In the context of geographic routing in wireless sensor networks linked by fading communication channels, energy-efficient transmission is important to extend the network lifetime. To this end, we propose a novel method to minimize the energy consumed by one bit of information per meter and per second toward the destination in fading channels. Using the outage probability as a measure to maximize the amount of information delivered within a given time interval we decide energy-efficient geographic routing between admissible nodes in a wireless sensor network. We present three different approaches, the first is optimal and is obtained by varying both transmission rate and power, the other two are sub-optimal since only one of them is tuned. Simulation examples comparing the energy costs for the different strategies illustrate the theoretical analysis in the cases of log-normal and Nakagami shadow fading. With the method proposed it is possible to obtain significant energy savings (up to ten times) with respect to fixed transmission rate and power.

Keywords Wireless sensor networks · Outage probability · Shadow fading