In this paper, we focus on ensuring encrypted vehicular communication using wireless controller area network performance at high node densities, by means of Dedicated Short-Range Communication (DSRC) algorithms. We analyses the effect of the vehicular communication parameters, message-rate, data-rate, transmission power and carrier sensing threshold, on the application performance. After a state-of-the-art analysis, we propose a data-rate DSRC algorithm. Simulation studies show that DSRC performs better than other decentralized vehicular communication algorithms for a wide range of application requirements and densities. Vehicular communication plays one of the most important roles for future autonomous vehicle. We have systematically investigated the impact of vehicular communication using the MATLAB application platform and achieved an accuracy of 93.74% after encrypting all the communications between the vehicles and securing them by applying the encryption on V2V communication in comparison with the existing system of Sensor Networks which stands at 92.97%. The transmission time for the encryption is 165 seconds while the rate of encryption is as low as 120 Mbps for the proposed awareness range of vehicles to vehicle using DSRC algorithm in Wireless-Controller Area Network for communication. Experimental results show that our proposed method performs 3% better than the recently developed algorithms.
Many technical approaches were implemented in the antenna manufacturing process to maintain the desired miniaturiza- tion of the size of the antenna model which can be employed in various applied systems such as medical communication systems. Furthermore, over the past several years, nanotechnology science has rapidly grown in a wide variety of applications, which has given rise to novel ideas in the design of antennas based on nanoscale merits, leading to the use of antennae as an essential linkage between the human body and the different apparatus of the medical communication system. Some medical applications dealt with different antenna configurations, such as microstrip patch antenna or optical nanoantenna in conjugate with sensing elements, controlling units, and monitoring instruments to maintain a specified healthcare system. This study summarizes and presents a brief review of the recent applications of antennas in different medical communication systems involving highlights, and drawbacks with explores recommended issues related to using antennas in medical treatment.
The necessity for an efficient algorithm for resource allocation is highly urgent because of increased demand for utilizing the available spectrum of the wireless communication systems. This paper proposes an Enhanced Bundle-based Particle Collision Algorithm (EB-PCA) to get the optimal or near optimal values. It applied to the Orthogonal Frequency Division Multiple Access (OFDMA) to evaluate allocations for the power and subcarrier. The analyses take into consideration the power, subcarrier allocations constrain, channel and noise distributions, as well as the distance between user's equipment and the base station. Four main cases are simulated and analyzed under specific operation scenarios to meet the standard specifications of different advanced communication systems. The sum rate results are compared to that achieved with employing another exist algorithm, Bat Pack Algorithm (BPA). The achieved results show that the proposed EB-PAC for OFDMA system is an efficient algorithm in terms of estimating the optimal or near optimal values for both subcarrier and power allocation.
In different modern and future wireless communication networks, a large number of low-power user equipment (UE) devices like Internet of Things, sensor terminals, and smart modules have to be supported over constrained power and bandwidth resources. Therefore, wireless-powered communication (WPC) is considered a promising technology for varied applications in which the energy harvesting (EH) from radio frequency radiations is exploited for data transmission. This requires efficient resource allocation schemes to optimize the performance of WPC and prolong the network lifetime. In this paper, harvest-then-transmit-based WP non-orthogonal multiple access (WP-NOMA) system is designed with time-split (TS) and power control (PC) allocation strategies. To evaluate the network performance, the sum rate and UEs’ rates expressions are derived considering power-domain NOMA with successive interference cancellation detection. For comparison purposes, the rate performance of the conventional WP orthogonal multiple access (WP-OMA) is derived also considering orthogonal frequency-division multiple access and time-division multiple access schemes. Intensive investigations are conducted to obtain the best TS and PC resource parameters that enable maximum EH for higher data transmission rates compared with the reference WP-OMA techniques. The achieved outcomes demonstrate the effectiveness of designed resource allocation approaches in terms of the realized sum rate, UE’s rate, rate region, and fairness without distressing the restricted power of far UEs.
Although the advanced technology in satellites and optical fiber communication systems exists now a day, but the researches in HF sky wave propagation for Mesopotamia (Iraq) area is suffered from shortage. In this paper, the novelty is that the communication path from Baghdad to any distance out of Iraqi border had been predicted, calculated and measured experimentally by using real data (Ionogram) supplemented by Nicosia Ionosound station 1000Km from Baghdad and a radio station model TS-130SE as a transmitter. The Predicted results generated by using MATLAB and NTIA/ITS software package like VOACAP. Radio communication using TS-130SE with 36 countries had been done experimentally. A comparison between the theoretical and experimental results was done. The experimental results were in the range of the predicated results which emphasis proposed method Presented in this paper .
This work addresses the critical need for secure and patient-controlled Electronic Health Records (EHR) migration among healthcare hospitals’ cloud servers (HHS). The relevant approaches often lack robust access control and leave data vulnerable during transfer. Our proposed scheme empowers patients to delegate EHR migration to a trusted Third-Party Hospital (TTPH); which is the Certification Authority (CA) while enforcing access control. The system leverages asymmetric encryption utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA), EEC and ECDSA added robust security and lightness EHR sharing. Patient and user privacy is managed due to anonymity through cryptographic hashing for data protection and utilizes mutual authentication for secure communication. Formal security analysis using the Scyther tool and informal analysis was conducted to validate the system’s robustness. The proposed scheme achieved EHR integrity due to the verification of the communicated HHS and ensuring the integrity of the HHS digital certificate during EHR migration. Ultimately, the result achieved in the proposed work demonstrated the scheme’s high balance between data security and accuracy of communication, where the best result obtained represented 7.7/ ms as computational cost and 1248 /bits as communication cost compared with the relevant approaches.
Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients loose all communication pathways except for their sensory and cognitive functions. One of the possible rehabilitation methods for these patients is to provide a brain machine interface (BMI) for communication; the BMI uses the electrical activity of the brain detected by scalp EEG electrodes. Classification of EEG signals extracted during mental tasks is a technique for designing a BMI. In this paper a BMI design using five mental tasks from two subjects were studied, a combination of two tasks is studied per subject. An Elman recurrent neural network is proposed for classification of EEG signals. Two feature extraction algorithms using overlapped and non overlapped signal segments are analyzed. Principal component analysis is used for extracting features from the EEG signal segments. Classification performance of overlapping EEG signal segments is observed to be better in terms of average classification with a range of 78.5% to 100%, while the non overlapping EEG signal segments show better classification in terms of maximum classifications.
A wireless sensor network consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Different approaches have used for simulation and modeling of SN (Sensor Network) and WSN. Traditional approaches consist of various simulation tools based on different languages such as C, C++ and Java. In this paper, MATLAB (7.6) Simulink was used to build a complete WSN system. Simulation procedure includes building the hardware architecture of the transmitting nodes, modeling both the communication channel and the receiving master node architecture. Bluetooth was chosen to undertake the physical layer communication with respect to different channel parameters (i.e., Signal to Noise ratio, Attenuation and Interference). The simulation model was examined using different topologies under various conditions and numerous results were collected. This new simulation methodology proves the ability of the Simulink MATLAB to be a useful and flexible approach to study the effect of different physical layer parameters on the performance of wireless sensor networks.
The reliability and feasibility of optical coherent communication system are strongly conditioned by laser phase noise and fluctuations of the state of polarization (SOP) of the optical field at the output of conventional single mode fiber. The double frequency parameter shift keying (DFPSK) system has been proposed in the literature as an efficient scheme that allows compensation of both effects by sending a reference channel that is suitably frequency shifted by using polarization modulation. This paper presents a comprehensive theoretical analysis for the performance of this system in the presence of dichroism which is introduced when the transmission channel has polarization dependent losses or amplifications. The results indicate that the performance of DFPSK system is affected by dichroism even in the low noise frequency regime.
This research presents a technique of an electro optic effect for enhancement the an accomplishment of an electro optics switch using Mat lab simulation program . this technique includes design a mathematical model for evaluate the effect of different parameters such as refractive index (n), distance of separation between waveguides (d), length of electrodes (L), relative refractive index (Δn), and switching voltage (V ), on the DC bias voltage of an electro optics switch. In this work the investigation of performance of an electro optics switch by analysis of an effect of distance between waveguides and the changing of refractive index on the bias voltage (V), and which optimizes when the wavelength is from 1300 into 1550 nm. Finally, an electro-optic active switch is designed and optimized, using the analytical model and which considers important device in the modern optical communication system.
In this study, we propose a compact, tri-band microstrip patch antenna for 5G applications, operating at 28 GHz, 38 GHz, and 60 GHz frequency bands. Starting with a basic rectangular microstrip patch, modifications were made to achieve resonance in the target frequency bands and improve S11 performance, gain, and impedance bandwidth. An inset feed was employed to enhance antenna matching, and a π–shaped slot was incorporated into the radiating patch for better antenna characteristics. The design utilized a Rogers RT/Duroid-5880 substrate with a 0.508 mm thickness, a 2.2 dielectric constant, and a 0.0009 loss tangent. The final dimensions of the antenna are 8 x 8.5 x 0.508 mm3. The maximum S11 values obtained at the resonant frequencies of 27.9 GHz, 38.4 GHz, and 56 GHz are -15.4 dB, -18 dB, and -26.4 dB, respectively. The impedance bandwidths around these frequencies were 1.26 GHz (27.245 - 28.505), 1.08 GHz (37.775 - 38.855), and 12.015 GHz (51.725 - 63.74), respectively. The antenna gains at the resonant frequencies are 7.96 dBi, 6.82 dBi, and 7.93 dBi, respectively. Radiation efficiencies of 88%, 84%, and 90% were achieved at the resonant frequencies. However, it is observed that the radiation is maximum in the broadside direction at 28 GHz, although it peaks at −41o/41o and −30o/30o at 38 GHz and 56 GHz, respectively. Furthermore, the antenna design, simulations, and optimizations were carried out using HFSS, and the results were verified with CST. Both simulators showed a reasonable degree of consistency, confirming the effectiveness and reliability of the proposed antenna design.
Wavelet-based algorithms are increasingly used in the source coding of remote sensing, satellite and other geospatial imagery. At the same time, wavelet-based coding applications are also increased in robust communication and network transmission of images. Although wireless multimedia sensors are widely used to deliver multimedia content due to the availability of inexpensive CMOS cameras, their computational and memory resources are still typically very limited. It is known that allowing a low-cost camera sensor node with limited RAM size to perform a multi-level wavelet transform, will in return limit the size of the acquired image. Recently, fractional wavelet filter technique became an interesting solution to reduce communication energy and wireless bandwidth, for resource-constrained devices (e.g. digital cameras). The reduction in the required memory in these fractional wavelet transforms is achieved at the expense of the image quality. In this paper, an adaptive fractional artifacts reduction approach is proposed for efficient filtering operations according to the desired compromise between the effectiveness of artifact reduction and algorithm simplicity using some local image features to reduce boundaries artifacts caused by fractional wavelet. Applying such technique on different types of images with different sizes using CDF 9/7 wavelet filters results in a good performance.
Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications such as noise cancellation. Noise cancellation is a common occurrence in today telecommunication systems. The LMS algorithm which is one of the most efficient criteria for determining the values of the adaptive noise cancellation coefficients are very important in communication systems, but the LMS adaptive noise cancellation suffers response degrades and slow convergence rate under low Signal-to- Noise ratio (SNR) condition. This paper presents an adaptive noise canceller algorithm based fuzzy and neural network. The major advantage of the proposed system is its ease of implementation and fast convergence. The proposed algorithm is applied to noise canceling problem of long distance communication channel. The simulation results showed that the proposed model is effectiveness.
A considerable work has been conducted to cope with orthogonal frequency division multiple access (OFDMA) resource allocation with using different algorithms and methods. However, most of the available studies deal with optimizing the system for one or two parameters with simple practical condition/constraints. This paper presents analyses and simulation of dynamic OFDMA resource allocation implementation with Modified Multi-Dimension Genetic Algorithm (MDGA) which is an extension for the standard algorithm. MDGA models the resource allocation problem to find the optimal or near optimal solution for both subcarrier and power allocation for OFDMA. It takes into account the power and subcarrier constrains, channel and noise distributions, distance between user's equipment (UE) and base stations (BS), user priority weight – to approximate the most effective parameters that encounter in OFDMA systems. In the same time multi dimension genetic algorithm is used to allow exploring the solution space of resource allocation problem effectively with its different evolutionary operators: multi dimension crossover, multi dimension mutation. Four important cases are addressed and analyzed for resource allocation of OFDMA system under specific operation scenarios to meet the standard specifications for different advanced communication systems. The obtained results demonstrate that MDGA is an effective algorithm in finding the optimal or near optimal solution for both of subcarrier and power allocation of OFDMA resource allocation.
The rapid growth in microelectronics and crunching RISC in the field of bio-medical sciences incorporated of soft tools to diagnose various parameters of human fluids. Conventional method of blood sample analysis makes use of laboratory technique of titration, which is operator-dependent and results in lot of errors depending on the skill of the technician. In order to eliminate the human errors involved in the conventional method, in this paper an attempt has been made to present a capillary centrifuge technique driven by high speed DC motor fed by Morgan chopper and controlled by powerful ARM processor. It results in accurate analysis of the blood samples. The various techniques involved in accurate sensing of speed using timer and generation of firing pulses to thyristor in the Morgan chopper is judiciously achieved. This paper clearly brings out the advantages of the proposed blood measurement technique which effectively gives blood analysis faster and at a low cost.
Vehicular Ad hoc Networks (VANETs), a subsection of Mobile Ad hoc Networks (MANETs), have strong future application prospects. Because topology structures are rapidly changing, determining a route that can guarantee a good Quality of Service (QoS) is a critical issue in VANETs. Routing is a critical component that must be addressed in order to utilize effective communication among vehicles. The purpose obtained from this study is to compare the AODV and GPSR performance in terms of Packet Delivery Ratio, Packet Drop Ratio, Throughput, and End-to-End Delay by applying three scenarios, the first scenario focuses on studying these protocols in terms of QoS while changing the number of vehicles at a constant speed of 40Km/h, and for the second scenario changing the speed value while keeping a constant number of vehicles which is 100, the third involves changing the communication range at a constant speed and vehicle number. This study represents a foundation for researchers to help elaborate on the strength and weaknesses of these two protocols. OMNeT++ in conjunction with SUMO is used for simulation.
Beam squint phenomenon is considered one of the most drawbacks that limit the use of (mm-waves) array antennas; which causes significant degradation in the BER of the system. In this paper, a uniform linear array (ULA) system is exemplified at millimeter (mm-waves) frequency bands to realize the effects of beam squint phenomena from different directions on an equivalent gain response to represent the channel performance in terms of bit error rate (BER). A simple QPSK passband signal model is developed and tested according to the proposed antenna array with beam squint. The computed results show that increasing the passband bandwidth and the number of antenna elements, have a significant degradation in BER at the receiver when the magnitude and phase errors caused by the beam squint at 26 GHz with various spectrum bandwidths.
Ad-Hoc networks have an adaptive architecture, temporarily configured to provide communication between wireless devices that provide network nodes. Forwarding packets from the source node to the remote destination node may require intermediate cooperative nodes (relay nodes), which may act selfishly because they are power-constrained. The nodes should exhibit cooperation even when faced with occasional selfish or non-cooperative behaviour from other nodes. Several factors affect the behaviour of nodes; those factors are the number of packets required to redirect, power consumption per node, and power constraints per node. Power constraints per node and grade of generosity. This article is based on a dynamic collaboration strategy, specifically the Generous Tit-for-Tat (GTFT), and it aims to represent an Ad-Hoc network operating with the Generous Tit-for-Tat (GTFT) cooperation strategy, measure statistics for the data, and then analyze these statistics using the Taguchi method. The transfer speed and relay node performance both have an impact on the factors that shape the network conditions and are subject to analysis using the Taguchi Method (TM). The analyzed parameters are node throughput, the amount of relay requested packets produced by a node per number of relays requested packets taken by a node, and the amount of accepted relay requested by a node per amount of relay requested by a node. A Taguchi L9 orthogonal array was used to analyze node behaviour, and the results show that the effect parameters were number of packets, power consumption, power constraint of the node, and grade of generosity. The tested parameters influence node cooperation in the following sequence: number of packets required to redirect (N) (effects on behaviour with a percent of 6.8491), power consumption per node (C) (effects on behaviour with a percent of 0.7467), power constraints per node (P) (effects on behaviour with a percent of 0.6831), and grade of generosity (ε) (effects on behaviour with a percent of 0.4530). Taguchi experiments proved that the grade of generosity (GoG) is not the influencing factor where the highest productivity level is, while the number of packets per second required to redirect also has an impact on node behaviour.
In recent years, increased importance of Smart Grid, which includes monitoring and control the consumption of customers of electric power. In this paper, Wireless Smart Electrical Power Meter has been designed and implemented which ZigBee wireless sensor network (WSN) will be used for wireless electrical power meter communication supported by PIC microcontroller which used for power unit measurements. PIC microcontroller will be used for evaluating all electric power parameters at costumer side like V rms , I rms , KWh, and PF, and then all these parameters will be send to base station through wireless network in order to be calibrated and monitored.
The demand for a secured web storage system is increasing daily for its reliability which ensures data privacy and confidentiality. The proposed paper aims to find the most secure ways to maintain integrity and protect privacy and security in healthcare management systems. The Advanced Encryption Standard (AES) algorithm is used to encrypt data transferred by providing a means to check the integrity of information transmitted and make it more immune to cyberattack techniques, this was implemented by using Keyed-Hash Message Authentication Code (HMAC) and Secured Hash Algorithm-256 (SHA-256). The risk of exposure to attackers can be avoided by using honeypot systems combined with Intrusion detection systems (IDSs) as a firewall system is not effective against such attacks alone. The experimental results evaluate the proposed security health information management system by comparing the performance of the encryption algorithm based on encryption time, memory and CPU usage, and entropy for different plaintext lengths. In addition, it can be seen that when changing the AES key size, more memory and time are required the longer the key size is used. The 128 bits AES key is therefore advised if the system must operate in hard real-time.
The reliance on networks and systems has grown rapidly in contemporary times, leading to increased vulnerability to cyber assaults. The Distributed Denial-of-Service (Distributed Denial of Service) attack, a threat that can cause great financial liabilities and reputation damage. To address this problem, Machine Learning (ML) algorithms have gained huge attention, enabling the detection and prevention of DDOS (Distributed Denial of Service) Attacks. In this study, we proposed a novel security mechanism to avoid Distributed Denial of Service attacks. Using an ensemble learning methodology aims to it also can differentiate between normal network traffic and the malicious flood of Distributed Denial of Service attack traffic. The study also evaluates the performance of two well-known ML algorithms, namely, the decision tree and random forest, which were used to execute the proposed method. Tree in defending against Distributed Denial of Service (DDoS) attacks. We test the models using a publicly available dataset called TIME SERIES DATASET FOR DISTRIBUTED DENIAL OF SERVICE ATTACK DETECTION. We compare the performance of models using a list of evaluation metrics developing the Model. This step involves fetching the data, preprocessing it, and splitting it into training and testing subgroups, model selection, and validation. When applied to a database of nearly 11,000 time series; in some cases, the proposed approach manifested promising results and reached an Accuracy (ACC) of up to 100 % in the dataset. Ultimately, this proposed method detects and mitigates distributed denial of service. The solution to securing communication systems from this increasing cyber threat is this: preventing attacks from being successful.
Lately, image encryption has stand out as a highly urgent demand to provide high security for digital images against use and unauthorized distribution. A lot of existing researches use chaotic systems, symmetric or asymmetric schemes for image encryption, but cryptosystem based on one encryption technique only, faces many challenges like weak security and low complexity. Therefore, incorporating two or more different ciphering methods yields a secure and efficient algorithm to protect image information. In this work, a new image cryptosystem is suggested by joining zigzag scan technique, RSA algorithm and chaotic systems. These three security factors introduce Triple Incorporated Ciphering stages system (TIC). Initially, the plaintext image is divided into 8 × 8 non-overlapping blocks, then the odd blocks are isolated from the even blocks. After that, a new modified zigzag scan in two different directions is adopted for shuffling pixels in the odd and even blocks. This operation effectively enhances the shuffling degree. Next, the RSA algorithm is utilized after combining the scrambled blocks in one matrix. Finally, chaotic systems are implemented on the resultant encrypted matrix to complete the ciphering process. The chaos is implemented in two steps; confusion and diffusion. Duffing map is exploited in the confusion stage, whereas L¨u system is adopted on the shuffled matrix in the diffusion stage. The simulation results show the superiority of TIC in both security and attacks robustness compared to other cryptographic algorithms. Therefore, TIC can be exploited in real-time communication systems for secure image transmission.
The incredible growth of FPGA capabilities in recent years and the new included features have made them more and more attractive for numerous embedded systems. There is however an important shortcoming concerning security of data and design. Data security implies the protection of the FPGA application in the sense that the data inside the circuit and the data transferred to/from the peripheral circuits during the communication are protected. This paper suggests a new method to support the security of any FPGA platform using network processor technology. Low cost IP2022 UBICOM network processor was used as a security shield in front of any FPGA device. It was supplied with the necessary security methods such as AES ciphering engine, SHA-1, HMAC and an embedded firewall to provide confidentiality, integrity, authenticity, and packets filtering features.
This work presents a wireless communication network (WCN) infrastructure for the smart grid based on the technology of Worldwide Interoperability for Microwave Access (WiMAX) to address the main real-time applications of the smart grid such as Wide Area Monitoring and Control (WAMC), video surveillance, and distributed energy resources (DER) to provide low cost, flexibility, and expansion. Such wireless networks suffer from two significant impairments. On one hand, the data of real- time applications should deliver to the control center under robust conditions in terms of reliability and latency where the packet loss is increased with the increment of the number of industrial clients and transmission frequency rate under the limited capacity of WiMAX base station (BS). This research suggests wireless edge computing using WiMAX servers to address reliability and availability. On the other hand, BSs and servers consume affected energy from the power grid. Therefore, the suggested WCN is enhanced by green self-powered based on solar energy to compensate for the expected consumption of energy. The model of the system is built using an analytical approach and OPNET modeler. The results indicated that the suggested WCN based on green WiMAX BS and green edge computing can handle the latency and data reliability of the smart grid applications successfully and with a self-powered supply. For instance, WCN offered latency below 20 msec and received data reliability up to 99.99% in the case of the heaviest application in terms of data.
In this paper we present the details of methodology pursued in implementation of an HMI and Demo Temperature Monitoring application for wireless sensor-based distributed control systems. The application of WSN for a temperature monitoring and control is composed of a number of sensor nodes (motes) with a networking capability that can be deployed for monitoring and control purposes. The temperature is measured in the real time by the sensor boards that sample and send the data to the monitoring computer through a base station or gateway. This paper proposes how such monitoring system can be setup emphasizing on the aspects of low cost, energy-efficient, easy ad-hoc installation and easy handling and maintenance. This paper focuses on the overall potential of wireless sensor nodes and networking in industrial applications. A specific case study is given for the measurement of temperature (with thermistor or thermocouple), humidity, light and the health of the WSN. The focus was not on these four types of measurements and analysis but rather on the design of a communication protocol and building of an HMI software for monitoring. So, a set of system design requirements are developed that covered the use of the wireless platforms, the design of sensor network, the capabilities for remote data access and management, the connection between the WSN and an HMI software designed with MATLAB.
Inter-symbol interference (ISI) exhibits major distortion effect often appears in digital storage and wireless communica- tion channels. The traditional decision feedback equalizer (DFE) is an efficient approach of mitigating the ISI effect using appropriate digital filter to subtract the ISI. However, the error propagation in DFE is a challenging problem that degrades the equalization due to the aliasing distorted symbols in the feedback section of the traditional DFE. The aim of the proposed approach is to minimize the error propagation and improve the modeling stability by incorporating adequate components to control the training and feedback mode of DFE. The proposed enhanced DFE architecture consists of a decision and controller components which are integrated on both the transmitter and receiver sides of communication system to auto alternate the DFE operational modes between training and feedback state based on the quality of the received signal in terms of signal-to-noise ratio SNR. The modeling architecture and performance validation of the proposed DFE are implemented in MATLAB using a raised-cosine pulse filter on the transmitter side and linear time-invariant channel model with additive gaussian noise. The equalizer capability in compensating ISI is evaluated during different operational stages including the training and DFE based on different channel distortion characteristics in terms of SNR using both 0.75 and 1.5 symbol duration in unit delay fraction of FIR filter. The simulation results of eye-diagram pattern showed significant improvement in the DFE equalizer when using a lower unit delay fraction in FIR filter for better suppressing the overlay trails of ISI. Finally, the capability of the proposed approach to mitigate the ISI is improved almost double the number of symbol errors compared to the traditional DFE.
The continuous growing developments in the traffic of mobile data limits the data throughput and capacity of cellular networks. “Heterogeneous Networks (HetNets)” are efficient solution to realize such demands. However, in HetNets, the congestion on the overloaded cellular network can be increased when the traffic of data is pushed from a cellular network to the Wi-Fi. In practice, offloading the cellular data traffic to a Wireless Local Area Network (WLAN) depending on the signal quality is a broadly deployed method to solve such problem. The use of Device to Device (D2D) communication further enhances the traffic offloading in WLAN systems and helps to obtain better throughput, end-to-end delay and network load. However, the critical offloading potential and its impacts on the whole performance is not totally understood. In this paper, the offloading of Long Term Evolution (LTE) traffic is presented using a WLAN for voice and video applications. A comparison is performed among two WLAN mecha- nisms; Distributed coordination function (DCF) and Point Coordination Function (PCF). As well, the effect of add- ing a D2D technology to the PCF is discussed. The WLAN effectively offloaded nodes at their Signal to Interference and Noise Ratio (SINR) becomes more than a specific threshold. Results presented that the PCF mechanism outper- forms the DCF one in terms of packet loss ratio, throughput and the maximum load of the entire network. In addi- tion, the use of a D2D serviced in the PCF helps in further reduction in the network load.
The phenomenal rise of the Internet in recent years, as well as the expansion of capacity in today’s networks, have provided both inspiration and incentive for the development of new services that combine phone, video, and text ”over IP.” Although unicast communications have been prevalent in the past, there is an increasing demand for multicast communications from both Internet Service Providers (ISPs) and content or media providers and distributors. Indeed, multicasting is increasingly being used as a green verbal exchange mechanism for institution-oriented programmers on the Internet, such as video conferencing, interactive college games, video on demand (VoD), TV over the Internet, e-learning, software programme updates, database replication, and broadcasting inventory charges. However, the lack of security within the multicast verbal exchange model prevents the effective and large-scale adoption of such important company multi-celebration activities. This situation prompted a slew of research projects that addressed a variety of issues related to multicast security, including confidentiality, authentication, watermarking, and access control. These issues should be viewed within the context of the safety regulations that work in the specific conditions. For example, in a public inventory charge broadcast, while identification is a vital necessity, secrecy is not. In contrast, video-convention programme requires both identification and confidentiality. This study gives a complete examination and comparison of the issues of group key management. Both network-dependent and network-independent approaches are used. The study also addresses the advantages, disadvantages, and security problems of various protocols.
In this paper, a new nonlinear dynamic system, new three-dimensional fractional order complex chaotic system, is presented. This new system can display hidden chaotic attractors or self-excited chaotic attractors. The Dynamic behaviors of this system have been considered analytically and numerically. Different means including the equilibria, chaotic attractor phase portraits, the Lyapunov exponent, and the bifurcation diagrams are investigated to show the chaos behavior in this new system. Also, a synchronization technique between two identical new systems has been developed in master- slave configuration. The two identical systems are synchronized quickly. Furthermore, the master-slave synchronization is applied in secure communication scheme based on chaotic masking technique. In the application, it is noted that the message is encrypted and transmitted with high security in the transmitter side, in the other hand the original message has been discovered with high accuracy in the receiver side. The corresponding numerical simulation results proved the efficacy and practicability of the developed synchronization technique and its application
Wireless Multimedia Sensor Networks (WMSNs) are being extensively utilized in critical applications such as envi- ronmental monitoring, surveillance, and healthcare, where the reliable transmission of packets is indispensable for seamless network operation. To address this requirement, this work presents a pioneering Distributed Dynamic Coop- eration Protocol (DDCP) routing algorithm. The DDCP algorithm aims to enhance packet reliability in WMSNs by prioritizing reliable packet delivery, improving packet delivery rates, minimizing end-to-end delay, and optimizing energy consumption. To evaluate its performance, the proposed algorithm is compared against traditional routing protocols like Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR), as well as proactive routing protocols such as Optimized Link State Routing (OLSR). By dynamically adjusting the transmission range and selecting optimal paths through cooperative interactions with neighboring nodes, the DDCP algorithm offers effective solutions. Extensive simulations and experiments conducted on a wireless multimedia sensor node testbed demonstrate the superior performance of the DDCP routing algorithm compared to AODV, DSR, and OLSR, in terms of packet delivery rate, end-to-end delay, and energy efficiency. The comprehensive evaluation of the DDCP algorithm against multiple routing protocols provides valuable insights into its effectiveness and efficiency in improving packet reliability within WMSNs. Furthermore, the scalability and applicability of the proposed DDCP algorithm for large-scale wireless multimedia sensor networks are confirmed. In summary, the DDCP algorithm exhibits significant potential to enhance the performance of WMSNs, making it a suitable choice for a wide range of applications that demand robust and reliable data transmission.
Audio encryption has gained popularity in a variety of fields including education, banking over the phone, military, and private audio conferences. Data encryption algorithms are necessary for processing and sending sensitive information in the context of secure speech conversations. In recent years, the importance of security in any communications system has increased. To transfer data securely, a variety of methods have been used. Chaotic system-based encryption is one of the most significant encryption methods used in the field of security. Chaos-based communication is a promising application of chaos theory and nonlinear dynamics. In this research, a chaotic algorithm for the new chaotic chameleon system was proposed, studied, and implemented. The chameleon chaotic system has been preferred to be employed because it has the property of changing from self-excited (SA) to hidden-attractor (HA) which increases the complexity of the system dynamics and gives strength to the encryption algorithm. A chaotic chameleon system is one in which, depending on the parameter values, the chaotic attractor alternates between being a hidden attractor and a self-excited attractor. This is an important feature, so it is preferable to use it in cryptography compared to other types of chaotic systems. This model was first implemented using a Field Programmable Gate Array (FPGA), which is the first time it has been implemented in practical applications. The chameleon system model was implemented using MATLAB Simulink and the Xilinx System Generator model. Self-excited, hidden, and coexisting attractors are shown in the proposed system. Vivado software was used to validate the designs, and Xilinx ZedBoard Zynq-7000 FPGA was used to implement them. The dynamic behavior of the proposed chaotic system was also studied and analysis methods, including phase portrait, bifurcation diagrams, and Lyapunov exponents. Assessing the quality of the suggested method by doing analyses of many quality measures, including correlation, differential signal-to-noise ratio (SNR), entropy, histogram analysis, and spectral density plot. The numerical analyses and simulation results demonstrate how well the suggested method performs in terms of security against different types of cryptographic assaults.
This paper presents a new strategy of sticky bomb detection. The detection strategy is based on measuring the magnetic field around the targeted car using compass device. A compass measure the earth gravitation of the car as (x,y,z) coordination , a threshold value of magnetic fields around the targeted car are recorded. If a difference is detected with any (x,y,z) coordination, an alert SMS message is sent to the car's owner. The detection system presented in this paper has been implemented based on Arduino board. The alarm signal is a Short Message Service (SMS) through Global System for Mobile Communication (GSM) module. The proposed method can gives the people of unstable countries a chance to discover whether their cars have been trapped with an IED bomb or their car still safe.
Cryptography is one of the technological means to provide security to data being transmitted on information and communication systems. When it is necessary to securely transmit data in limited bandwidth, both compression and encryption must be performed. Researchers have combined compression and encryption together to reduce the overall processing time. In this paper, new partial encryption schemes are proposed to encrypt only part of the compressed image. Soft and hard threshold compression methods are used in the compression step and the Advanced Encryption Standard (AES) cipher is used for the encryption step. The effect of different threshold values on the performance of the proposed schemes are studied. The proposed partial encryption schemes are fast, secure, and do not reduce the compression performance of the underlying selected compression methods.
Today, the trends are the robotics field since it is used in too many environments that are very important in human life. Covid 19 disease is now the deadliest disease in the world, and most studies are being conducted to find solutions and avoid contracting it. The proposed system senses the presence according to a specific injury to warn of it and transfer it to the specialist doctor. This system is designed to work in service departments such as universities, institutes, and all state departments serving citizens. This system consists of two parts: the first is fixed and placed on the desk and the other is mobile within a special robot that moves to perform the required task. This system was tested at the University of Basrah within the college of engineering, department of electrical Engineering, on teaching staff, students, and staff during the period of final academic exams. The presence of such a device is considered a warning according to a specific condition and isn’t a treatment for it, as the treatment is prescribed by the specialist doctor. It is found that the average number of infected cases is about 3% of the total number of students and the teaching staff and the working staff. The results were documented in special tables that go to the dean of the college with the attendance tables to know the daily health status of the students.
The No Mobile Phone Phobia or Nomophobia notion is referred to the psychological condition once humans have a fear of being disconnected from mobile phone connectivity. Hence, it is considered as a recent age phobia that emerged nowadays as a consequence of high engagement between people, mobile data, and communication inventions, especially the smart phones. This review is based on earlier observations and current debate such as commonly used techniques that modeling and analyzing this phenomenon like statistical studies. All that in order to possess preferable comprehension concerning human reactions to the speedy technological ubiquitous. Accordingly, humans ought to restrict their utilization of mobile phones instead of prohibiting it, due to the fact that they could not evade the power of technological progression. In that matter, future perspectives would be employing data mining techniques to explore deep knowledge, which represents correlated relationship between the human and the mobile phone.
A wireless body area network (WBAN) connects separate sensors in many places of the human body, such as clothes, under the skin. WBAN can be used in many domains such as health care, sports, and control system. In this paper, a scheme focused on managing a patient’s health care is presented based on building a WBAN that consists of three components, biometric sensors, mobile applications related to the patient, and a remote server. An excellent scheme is proposed for the patient’s device, such as a mobile phone or a smartwatch, which can classify the signal coming from a biometric sensor into two types, normal and abnormal. In an abnormal signal, the device can carry out appropriate activities for the patient without requiring a doctor as a first case. The patient does not respond to the warning message in a critical case sometimes, and the personal device sends an alert to the patient’s family, including his/her location. The proposed scheme can preserve the privacy of the sensitive data of the patient in a protected way and can support several security features such as mutual authentication, key management, anonymous password, and resistance to malicious attacks. These features have been proven depending on the Automated Validation of Internet Security Protocols and Applications. Moreover, the computation and communication costs are efficient compared with other related schemes.
The monitoring of COVID-19 patients has been greatly aided by the Internet of Things (IoT). Vital signs, symptoms, and mobility data can be gathered and analyzed by IoT devices, including wearables, sensors, and cameras. This information can be utilized to spot early infection symptoms, monitor the illness’s development, and stop the virus from spreading. It’s critical to take vital signs of hospitalized patients in order to assess their health. Although early warning scores are often calculated three times a day, they might not indicate decompensation symptoms right away. Death rates are higher when deterioration is not properly diagnosed. By employing wearable technology, these ongoing assessments may be able to spot clinical deterioration early and facilitate prompt therapies. This research describes the use of Internet of Things (IoT) to follow fatal events in high-risk COVID-19 patients. These patients’ vital signs, which include blood pressure, heart rate, respiration rate, blood oxygen level, and fever, are taken and fed to a central server on a regular basis so that information may be processed, stored, and published instantly. After processing, the data is utilized to monitor the patients’ condition and send Short Message Service (SMS) alerts when the patients’ vital signs rise above predetermined thresholds. The system’s design, which is based on two ESP32 controllers, sensors for the vital signs listed above, and a gateway, provides real-time reports, high-risk alerts, and patient status information. Clinicians, the patient’s family, or any other authorized person can keep an eye on and follow the patient’s status at any time and from any location. The main contribution in this work is the designed algorithm used in the gateway and the manner in which this gateway collects, analyze, process, and send the patient’s data to the IoT server from one side and the manner in which the gateway deals with the IoT server in the other side. The proposed method leads to reduce the cost and the time the system it takes to get the patient’s status report.
Given the role that pipelines play in transporting crude oil, which is considered the basis of the global economy and across different environments, hundreds of studies revolve around providing the necessary protection for it. Various technologies have been employed in this pursuit, differing in terms of cost, reliability, and efficiency, among other factors. Computer vision has emerged as a prominent technique in this field, albeit requiring a robust image-processing algorithm for spill detection. This study employs image segmentation techniques to enable the computer to interpret visual information and images effectively. The research focuses on detecting spills in oil pipes caused by leakage, utilizing images captured by a drone equipped with a Raspberry Pi and Pi camera. These images, along with their global positioning system (GPS) location, are transmitted to the base station using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol. At the base station, deep learning techniques, specifically Holistically-Nested Edge Detection (HED) and extreme inception (Xception) networks, are employed for image processing to identify contours. The proposed algorithm can detect multiple contours in the images. To pinpoint a contour with a black color, representative of an oil spill, the CIELAB color space (LAB) algorithm effectively removes shadow effects. If a contour is detected, its area and perimeter are calculated to determine whether it exceeds a certain threshold. The effectiveness of the proposed system was tested on Iraqi oil pipeline systems, demonstrating its capability to detect spills of different sizes.
The use of image communication has increased in recent years. In this paper, new partial encryption schemes are used to encrypt only part of the compressed data. Only 6.25-25% of the original data is encrypted for four different images, resulting in a significant reduction in encryption and decryption time. In the compression step, an advanced clustering analysis technique (Fuzzy C-means (FCM)) is used. In the encryption step, the permutation cipher is used. The effect of number of different clusters is studied. The proposed partial encryption schemes are fast and secure, and do not reduce the compression performance of the underlying selected compression methods as shown in experimental results and conclusion.
In smart cities, health care, industrial production, and many other fields, the Internet of Things (IoT) have had significant success. Protected agriculture has numerous IoT applications, a highly effective style of modern agriculture development that uses artificial ways to manipulate climatic parameters such as temperature to create ideal circumstances for the growth of animals and plants. Convolutional Neural Networks (CNNs) is a deep learning approach that has made significant progress in image processing. From 2016 to the present, various applications for the automatic diagnosis of agricultural diseases, identifying plant pests, predicting the number of crops, etc., have been developed. This paper involves a presentation of the Internet of Things system in agriculture and its deep learning applications. It summarizes the most essential sensors used and methods of communication between them, in addition to the most important deep learning algorithms devoted to intelligent agriculture.
The evolution of wireless communication technology increases human machine interaction capabilities especially in controlling robotic systems. This paper introduces an effective wireless system in controlling the directions of a wheeled robot based on online hand gestures. The hand gesture images are captured and processed to be recognized and classified using neural network (NN). The NN is trained using extracted features to distinguish five different gestures; accordingly it produces five different signals. These signals are transmitted to control the directions of the cited robot. The main contribution of this paper is, the technique used to recognize hand gestures is required only two features, these features can be extracted in very short time using quite easy methodology, and this makes the proposed technique so suitable for online interaction. In this methodology, the preprocessed image is partitioned column-wise into two half segments; from each half one feature is extracted. This feature represents the ratio of white to black pixels of the segment histogram. The NN showed very high accuracy in recognizing all of the proposed gesture classes. The NN output signals are transmitted to the robot microcontroller wirelessly using Bluetooth. Accordingly the microcontroller guides the robot to the desired direction. The overall system showed high performance in controlling the robot movement directions.
This paper discusses the design and performance of a frequency reconfigurable antenna for Internet of Things (IoT) applications. The antenna is designed to operate on multiple frequency bands and be reconfigurable to adjust to different communication standards and environmental conditions. The antenna design consists of monopole with one PIN diode and 50Ωfeed line. By changing the states of the diode, the antenna can be reconfigured to operate in a dual-band mode and a wideband mode. The performance of the antenna was evaluated through simulation. The antenna demonstrated good impedance matching, acceptable gain, and stable radiation patterns across the different frequency bands. The antenna has compact dimensions of (26×19×1.6) mm3. It covers the frequency range 2.95 GHz -8.2 GHz, while the coverage of the dual- band mode is (2.7-3.8) GHz and (4.57-7.4) GHz. The peak gain is 1.57 dBi for the wideband mode with omnidirectional radiation pattern. On the other hand, the peak gain of the dual-band mode is 0.87 dBi at 3 GHz and 0.47 dBi at 6 GHz with an omnidirectional radiation pattern too.
Facial retouching, also referred to as digital retouching, is the process of modifying or enhancing facial characteristics in digital images or photographs. While it can be a valuable technique for fixing flaws or achieving a desired visual appeal, it also gives rise to ethical considerations. This study involves categorizing genuine and retouched facial images from the standard ND-IIITD retouched faces dataset using a transfer learning methodology. The impact of different primary optimization algorithms—specifically Adam, RMSprop, and Adadelta—utilized in conjunction with a fine-tuned ResNet50 model is examined to assess potential enhancements in classification effectiveness. Our proposed transfer learning ResNet50 model demonstrates superior performance compared to other existing approaches, particularly when the RMSprop and Adam optimizers are employed in the fine-tuning process. By training the transfer learning ResNet50 model on the ND-IIITD retouched faces dataset with the ”ImageNet” weight, we achieve a validation accuracy of 98.76%, a training accuracy of 98.32%, and an overall accuracy of 98.52% for classifying real and retouched faces in just 20 epochs. Comparative analysis indicates that the choice of optimizer during the fine-tuning of the transfer learning ResNet50 model can further enhance the classification accuracy.
Recently, the incorporation of state-of-the-art technology such as Electronic Healthcare Records (EHRs), networks, and cloud computing has transformed the traditional healthcare system. However, security problems have arisen as a result of the integration of technology. Secure remote user authentication is a core part of the healthcare system to validate the user's identification via an unsecure communication network. Since then, several remote user authentication schemes have been presented, each with its own set of pros and limitations. As a result, security, malicious attacks and privacy concerns are considered one of the main challenges related to the healthcare system. In this paper, we propose a safe user authentication scheme for patients in the healthcare system that overcomes these flaws and confirms the security of the proposed work using scyther, a formal security tool. In the healthcare environment, our work provides an effective means to construct an environment capable of setting, registering, storing, searching, analyzing, authentication, and verifying electronic healthcare information in order to protect the information of patients. Furthermore, our suggested scheme uses symmetric encryption based on the crypto- hash function for accessing the anomaly of the patient's identity and One-Time Password (OTP). Towards the end of the study, the performance analysis results indicate a delicate balance of security and performance that is frequently lacking in previous works.
Nowadays, multimedia communication has become very widespread and this requires it to be protected from attackers and transmitted securely for reliability. Encryption and decryption techniques are useful in providing effective security for speech signals to ensure that these signals are transmitted with secure data and prevent third parties or the public from reading private messages. Due to the rapid improvement in digital communications over the recent period up to the present, the security of voice data transmitted over various networks has been classified as a favored field of study in earlier years. The contributions to audio encryption are discussed in this review. This Comprehensive review mainly focuses on presenting several kinds of methods for audio encryption and decryption the analysis of these methods with their advantages and disadvantages have been investigated thoroughly. It will be classified into encryption based on traditional methods and encryption based on advanced chaotic systems. They are divided into two types, continuous-time system, and discrete-time system, and also classified based on the synchronization method and the implementation method. In the fields of information and communications security, system designers face many challenges in both cost, performance, and architecture design, Field Programmable gate arrays (FPGAs) provide an excellent balance between computational power and processing flexibility. In addition, encryption methods will be classified based on Chaos-based Pseudo Random Bit Generator, Fractional-order systems, and hybrid chaotic generator systems, which is an advantageous point for this review compared with previous ones. Audio algorithms are presented, discussed, and compared, highlighting important advantages and disadvantages. Audio signals have a large volume and a strong correlation between data samples. Therefore, if traditional cryptography systems are used to encrypt such huge data, they gain significant overhead. Standard symmetric encryption systems also have a small key-space, which makes them vulnerable to attacks. On the other hand, encryption by asymmetric algorithms is not ideal due to low processing speed and complexity. Therefore, great importance has been given to using chaotic theory to encode audio files. Therefore, when proposing an appropriate encryption method to ensure a high degree of security, the key space, which is the critical part of every encryption system, and the key sensitivity must be taken into account. The key sensitivity is related to the initial values and control variables of the chaotic system chosen as the audio encryption algorithm. In addition, the proposed algorithm should eliminate the problems of periodic windows, such as limited chaotic range and non-uniform distribution, and the quality of the recovered audio signal remains good, which confirms the convenience, reliability, and high security.
In this paper, a compact two-element cylindrical dielectric resonator antenna (CDRA) array with corporate feeding is proposed for X-band applications. The dielectric resonator antenna (DRA) array is excited by a microstrip feeder using an efficient aperture-coupled method. The designed array antenna is analyzed using a CST microwave studio. The fabricated sample of the proposed CDRA antenna array showed bandwidth extending from 10.42GHz to 12.84GHz (20.8%). The achieved array gain has a maximum of 9.29dB i at frequency of 10.7GHz. This is about 2.06dB i enhancement of the gain in comparison with a single pellet CDRA. The size of the whole antenna structure is about 50 50mm 2 .
This work presents a healthcare monitoring system that can be used in an intensive care room. Biological information represented by ECG signals is achieved by ECG acquisition part . AD620 Instrumentation Amplifier selected due to its low current noise. The ECG signals of patients in the intensive care room are measured through wireless nodes. A base node is connected to the nursing room computer via a USB port , and is programmed with a specific firmware. The ECG signals are transferred wirelessly to the base node using nRF24L01+ wireless module. So, the nurse staff has a real time information for each patient available in the intensive care room. A star Wireless Sensor Network is designed for collecting ECG signals . ATmega328 MCU in the Arduino Uno board used for this purpose. Internet for things used For transferring ECG signals to the remote doctor, a Virtual Privet Network is established to connect the nursing room computer and the doctor computer . So, the patients information kept secure. Although the constructed network is tested for ECG monitoring, but it can be used to monitor any other signals. INTRODUCTION For elderly people, or the patient suffering from the cardiac disease it is very vital to perform accurate and quick diagnosis. Putting such person under continuous monitoring is very necessary. (ECG) is one of the critical health indicators that directly bene ¿ t from long-term monitoring. ECG signal is a time-varying signal representing the electrical activity of the heart. It is an effective, non- invasive diagnostic tool for cardiac monitoring[1]. In this medical field, a big improvement has been achieved in last few years. In the past, several remote monitoring systems using wired communications were accessible while nowadays the evolution of wireless communication means enables these systems to operate everywhere in the world by expanding internet benefits, applications, and services [2]. Wireless Sensor Networks (WSNs), as the name suggests consist of a network of wireless nodes that have the capability to sense a parameter of interest like temperature, humidity, vibration etc[3,4]. The health care application of wireless sensory network attracts many researches nowadays[ 5-7] . Among these applications ECG monitoring using smart phones[6,8], wearable Body sensors[9], remote patient mentoring[10],...etc. This paper presents wireless ECG monitoring system for people who are lying at intensive care room. At this room ECG signals for every patient are measured using wireless nodes then these signals are transmitted to the nursing room for remote monitoring. The nursing room computer is then connected to the doctors computer who is available at any location over the word by Virtual Privet Network (VPN) in such that the patients information is kept secure and inaccessible from unauthorized persons. II. M OTE H ARDWARE A RCHITECTURE The proposed mote as shown in Fig.1 consists of two main sections : the digital section which is represented by the Arduino UNO Board and the wireless module and the analog section. The analog section consists of Instrumentation Amplifier AD620 , Bandpass filter and an operational amplifier for gain stage, in addition to Right Leg Drive Circuit. The required power is supplied by an internal 3800MAH Lithium-ion (Li-ion) battery which has 3.7V output voltage.
Vehicle Ad-hoc Network (VANET) is a type of wireless network that enables communication between vehicles and Road Side Units (RSUs) to improve road safety, traffic efficiency, and service delivery. However, the widespread use of vehicular networks raises serious concerns about users’ privacy and security. Privacy in VANET refers to the protection of personal information and data exchanged between vehicles, RSUs, and other entities. Privacy issues in VANET include unauthorized access to location and speed information, driver and passenger identification, and vehicle tracking. To ensure privacy in VANET, various technologies such as pseudonymization, message authentication, and encryption are employed. When vehicles frequently change their identity to avoid tracking, message authentication ensures messages are received from trusted sources, and encryption is used to prevent unauthorized access to messages. Therefore, researchers have presented various schemes to improve and enhance the privacy efficiency of vehicle networks. This survey article provides an overview of privacy issues as well as an in-depth review of the current state-of-the-art pseudonym-changing tactics and methodologies proposed.
Recently, Jones matrix parameter shift keying (JMPSK) technique has been proposed in the literature to achieve phase noise and polarization state insensitive optical communication systems. The aim of this paper is to examine the performance of this system in the presence of system impairments, namely channel dichroism. A comprehensive analysis is presented to assess the effect of dichroism on the bit-error-rate (BER) characteristics of JMPSK receiver.