JOURNAL OF ADVANCED SIGNAL PROCESSING
Year:2020 | Volume:4 | Issue:1 (5)|Papers Count:13

In this paper, we investigate the physical layer secrecy of a multipair cooperative network in presence of an eavesdropper. Simultaneous ccommunication between the transmitter and receiver pairs is established through a massive antenna array equipped fullduplex relay station, while the passive eavesdropper overhears communication between one pair. We consider that the relay uses zeroforcing, maximum mixing ratio, and maximum transmission ratio linear processing techniques. In the first part of the paper, we study the secrecy rate of the adopted linear processing techniques. We derive closed-form expressions for the average secrecy rate as a functions of the system parameters, such as number of pairs, the number of relay’ s transmit and receive antennas, and the channel estimation coefficients. In the second part of the paper, in order to improve the system’ s secrecy, an optimal power allocation scheme is presented at the relay station and source nodes. The formulated problem is a complex non-convex problem that is solved by recasting as a geometric programming problem. The simulation results show that the proposed power allocation scheme significantly improves the system's secrecy rate.

One proposed approach in fifth-generation wireless communication to support more users is the dynamic use of orthogonal and non-orthogonal multiple access schemes. In this research, a dynamic orthogonal and non-orthogonal multiple access system is proposed to maximize the energy efficiency (EE), and several schemes are presented for allocation of sub-channels and power. Due to the complexity of the proposed resource allocation problem and its non-convexity property, it is not possible to find a global solution. Hence, the main problem is divided into two sub-problems which are sub-channels and power allocation. In the first step, the subchannel allocation problem is solved and its output is sub-channel allocation for all active users and determining the access mode for each sub-carrier. The second step is the power allocation sub-problem which is converted into a quasi-convex sub-problem by using the difference of convex functions algorithm iteratively, and ultimately. Then, the bisection method is applied for solving the quasiconvex sub-problem. Also, the KKT equations are provided for the feasibility problem of the bisection method. Finally, in the simulation section, the maximum EE versus the maximum power for each user is calculated. Besides, the impact of user’ s presence at the cell edge on the EE is discussed. According to the simulation results, our proposed resource allocation approach can improve the sum rate and EE of the system compared to the heuristic approach of the previous literature.

Different method are used for channel estimation in MIMO systems, Each of which has different functionality. MIMO systems are like equations with multiple variables, variables are transmitted symbols by transmitter (M) and equations are received symbols in receiver (N). Different mathematical methods are for decomposition of channel matrix, than Q&R Decomposition is one of these methods. Using decomposition for channel matrix with adaptive algorithms such as LMS and RLS in MIMO systems will simplify and reduce complexity. In this paper, the MIMO channel will be modeled by LMS and RLS algorithms and instead directly of estimated the channel matrix H that very complexity, in QR matrix, first estimated Q and then estimated R, that the channel matrix is estimated. According result, in MIMO systems, channel modeling with LMS and RLS adaptive algorithms and applying QR decomposition will result in the error reduction.

Mobility and its quality has direct and significant effect on quality of life. Passing over obstacles is unavoidable and its safe execution is a measure of mobility for community dwellers particularly for elderly and Parkinson patients with higher risk of falling. Algorithms for monitoring mobility in high risk people, need automatic detection to examine frequency and quality of passing over obstacles. Very few attempts can be found in the literature who just focus on the healthy population who need complex algorithms. Furthermore, in real life situations, people encounter a range of obstacle heights that should be detectable in such algorithms. In this paper a wavelet-based algorithm is examined and its performance is evaluated in detection of tall and short obstacles for two groups of healthy and Parkinson participants. Accuracy of this method was 98. 5% for the 19 healthy elderly participants, and 90. 6% for the 12 Parkinson patients. The maximum error in detection of obstacle crossing time was 0. 1 second for either feet and for both barrier heights.

Sparse network coding was introduced to reduce the computational complexity of the random linear network coding. In this method, most of the decoding matrix coefficients are zero. Partial decoding means the possibility of decoding a part of the raw packets is one of the capabilities of the sparse network coding method. We introduce three different models of sparse coding method as an approach to reduce decoding latency in real-time communication. More precisely, we first evaluate a sparse network coding for a no feedback configuration in terms of the performance of the total number of transmissions required, and the average packet decoding delay for a generation of raw packets, by introducing a Markov chain-based model. Then we evaluate the accuracy of the proposed model using extensive simulation and show that the proposed model can accurately estimate the number of required transmissions and decoding delay for a generation of packets. The results also evaluate the accuracy of the model in the erasure channel. In the following, we introduce the feedback-based model and we show that this model can create a better balance between the functions of the number of transmissions and the average decoding delay per packet. Finally, by focusing on the problem of finding the random spanning tree, we present a graph-based model for analyzing sparse network coding and show that although the proposed model is valid only for grade 2 sparsity, it also has the capacity to develop for lower sparsity.

Advent of new systems, such as the Internet of Things (IoT) and novel communication and broadcasting systems, calls for higher data rates, massive connectivity, better cell coverage, and other improvements. Orthogonal frequency division multiplexing (OFDM) and non-orthogonal multiple access (NOMA) are amongst the promising modulation and multiple access schemes which are candidates to be implemented in the physical layer of the new systems. High data rates are achievable via OFDM which mitigates Inter-Symbol Interference (ISI) caused by the delay spread of the wireless channels. On the other hand, NOMA improves the spectral efficiency of the system by allowing users to share frequency band resources. Therefore, OFDM based NOMA (OFDM-NOMA) techniques have the potential to considerably increase the attainable data rate in novel communication systems. High peak-to-average power ratio (PAPR) is one of the issues in OFDM systems which makes high-power amplifier (HPA) to work in the non-linear region and degrades system performance. Due to the special properties of OFDM-NOMA systems, most of the PAPR reduction methods are not suitable for them. In this paper, we analyze the performance of three PTS-based PAPR reduction methods in OFDM-NOMA systems. Functional block diagram of these schemes is presented. Finally, we will compare their computational complexity, PAPR reduction, and system bit error rate (BER) performance to select the most proper PAPR reduction scheme for OFDM-NOMA systems.

Challenges in the field of information and communication security are of great interest to researchers. The expansion of network boundaries, the intensification and complexity increase of network security attacks, has amplified the need for intelligent, automated and real-time systems to detect network anomalies and threats. To detect anomalies, network traffic needs to be monitored immediately. The anomaly involves significant and unusual changes in network traffic behavior compared to its normal behavior patterns. In this paper, in order to detect anomalies, a system based on self-organizing multi agent systems is presented. Multi agent systems are made up of agents that interact with each other to achieve a specific goal. These systems are used to solve problems that are difficult for a single agent to solve or integrate. The proposed system architecture is scalable and can adapt to changes in today's networks. The evaluation and analysis of the proposed system in the NSL-KDD dataset shows that the rate of anomalies detection has improved compared to the recently proposed methods. Also, by proposing an algorithm to optimize the agents’ choices and another one for intelligent agents’ decision weighting, the rate of anomaly detection is increased and the time of event analysis is reduced.

Hearing is an important part of human daily life. Although humans are exposed to various sounds from different sources and the numbers of receptors of the neural system are limited, they can process complex auditory scenes well. One of the reasons for this human ability is the phenomenon of attention. Auditory attention can be divided into two categories: bottom-up attention and topdown attention. In this paper, a model for simulating the bottom-up attention using weighted saliency maps in the auditory system is proposed. The dataset in this research work is obtained by combining different background noises with the sounds in the ESC database as salient regions, at different SNRs. To evaluate the model, the mean-error criterion was used, which is defined as the time difference between the actual salient point and the salient point detected by the model. The weighted combination of the conspicuity maps of the features using the Genetic algorithm makes the proposed model with an average error of 0. 92 seconds to perform better than the baseline model having an average error of 1. 91 seconds.

In order to satisfy the delay requirements of telecommunication systems, in this paper, we present a cooperative network with the short packet transmission in the Rayleigh fading channel. The desired relay can be implemented as a two-way half-duplex (HD) or a two-way full-duplex (FD). Also, for more accurate satisfaction and reduction of communication delays, sending and receiving with short packets is considered. Effective capacity appropriately measures the transmission rate under the delay constraint. Therefore, it is considered as a performance evaluation criterion here. With a two-way relay, two nodes exchange data with each other using a relay simultaneously. The priorities and requirements of the two nodes are not necessarily the same. Therefore, to increase performance, the system is modeled and solved as a multi-objective problem. In this way, the available power in the network is divided between the relay and two nodes, and the effective capacity of the two nodes is maximized. Depending on the different conditions, the optimal amount of allocated power to relay and nodes is calculated. However, due to the complexity and time consuming calculations, an approximate method which speeds up the calculation is presented. The approximated solution has a very close performance to the optimal allocated power. Finally, various comparisons have been made in different conditions between the performance of two-way HD and two-way FD relays. The improvement of multi-objective power allocation has been shown, especially when the relay is not located in the middle of two nodes.

Perpetual coding is a sparse coding method in which coefficients are used in a structured way for coding operations. It has been shown that this method reduces the computational complexity of the random linear network coding method. The purpose of this paper is to articulate a mathematical model to illustrate the performance of perpetual coding, and to show that in a perpetual coding with the presence of an erasure channel the number of linear dependent packet transmissions is highly dependent on a parameter called the width ( ) ω which represents the number of consecutive non-zero coding coefficients present in each coded packet after a pivot element. Then, a mathematical analytical model for the number of transmitted packets is provided, which predicts the number of packets until the second round. Finally, we obtain the probability of the packet’ s decoding in round k and validate it by simulation. The results show that for low error probability and small (ω ) on the link, overhead value can even reach a number close to 70%. To reduce the transmitter overhead, the ( ) ω value must be selected correctly, and the correct choice of ( ) ω is highly dependent on the probability of channel error. Also, for  5, generation size g  256 and low erasure probability on the link, a destination can receive up to 70% overhead on average. Moreover, by increasing the width, the overhead decreases and for  60 it becomes negligible. We show that our mechanism reduces the delay by 37. 44 percent.

This paper presents a novel method in reversible data hiding in encrypted image. In the proposed method, after image encryption by image owner, data hider vacates room to embed data without having any knowledge of original content. It realizes employing most significant bit (MSB) of pixels in the encrypted image. These MSBs are integrated and data bits are embedded in the integrated ones. The integration provides more strength for lossless reconstruction of the original image at the recipient. Therefore, employing the integration and a proper predictor such as chessboard predictor, original image can be losslessly reconstructed at the recipient. Also, in the proposed scheme, error-free extraction of data is done under any circumstances. Proposed algorithm realizes lossless reconstruction of the original image even without having data hider key. Experimental results confirm that the proposed algorithm outperforms state of the art ones.

In recent years, text detection and recognition in natural images have been extensively studied. In this study, a robust multioriented scene text localization system was proposed to obtain high efficiency in text detection based on a convolutional neural network (CNN). The proposed method includes three layers of feature extraction, feature-merging, and output. An improved ReLU layer (i. ReLU) is introduced in the feature extraction layer. An improved inception layer (i. inception) is also provided to detect texts with valuable information. An extra layer has been used to improve the feature extraction, which enables the proposed structureto detect multi-oriented even curved and vertical texts. We have proposed a pipeline framework for character recognition. The proposed pipeline framework consists of two parallel pipelines that are processed at the same time, and can recognize 62 characters. The first pipeline consists of cropped words and the second pipeline consists of text angles. Then, we formed a dictionary and used it to correct the possible error of the recognized words. Experiments on the ICDAR 2013, ICDAR 2015 and ICDAR 2019 datasets demonstrated the architectural superiority of the proposed structure over the previous works.

The multipliers are important blocks that used in digital processing modern systems. So, design of the efficient multiplier is important advantage for digitally computational system. In some processing fields as the signal processing, the specified level of the error is acceptable, so used of accurate multiplier in the all of the processing fields is not essential. One of the important blocks of the multiplier is the compressor that is used in stage of the partial multiplication for decreasing operations. In this paper, new design of the 5: 3 and 15: 4 approximate compressors are proposed, the power consumption, propagation delay and error distance of proposed compressors in the comparison others have proper operating, with used of the proposed approximate compressors designed the approximate 16*16-bit multiplier. The overall of the proposed approximate multiplier is simulated and implemented by 180 nm CMOS technology and 1. 8 V power supply by the Cadence tools. The result of simulation is shown that propagation delay proposed 5: 3 compressors is 0. 76 ns and power consumption is 0. 935 μ W with ± 2 error distance. And also, the proposed 15: 4 compressor has 1. 12 ns propagation delay, 4. 75 μ W power consumption.