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The Internet of Things (IoT) comprises smart objects capable of sensing, processing, and transmitting application-specific data. These objects collect and transmit a huge amount of correlated and redundant data due to overlapped sensing regions, causing unnecessary exploitation of spectral bands and load balancing issues in the network. As a result, time-critical and delay-sensitive data experience a higher delay, lower throughput, and quality of service degradation. To circumvent these issues, in this paper, we propose a model that is energy efficient and is capable of maximizing the spectrum utilization with optimal Device-to-Gateway configuration. Initially, the network gateways perform spectrum sensing for available channels using an energy detection technique and forward them to a cognitive engine (CE). The CE assigns the best available channels in the licensed band to the network devices for communication. Each channel is divided into equal-length time slots for the timely delivery of critical data. In addition, the CE calculates the load on each gateway and uses particle swarm optimization algorithm for optimal load distribution among the network gateways. Our experimental results show that the proposed model is efficient for the resource-constrained IoT devices in terms of packet drop ratio, delay, and throughput of the network. Moreover, the proposed scheme also achieves optimal Device-to-Gateway configuration with efficient spectrum utilization in the licensed band.

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Object tracking is highly applicable in emerging technologies and is normally done using measurements from sensors. Unfortunately, due to the presence of deleterious noise, measurements are inaccurate and different estimation methods have been developed. Most of them are mainly for Gaussian noise, leaving non-Gaussian noise scenarios unresolved. Also, while particle filters were introduced to address a more general noise scenario, they are mathematically complex especially when used in high dimensional systems. To circumvent these problems, we propose the Separate Monte Carlo Mean (SMC-MEAN) which is formulated on the Bayesian particle filtering framework. The proposed method is applied to an autonomous object tracking problem in both Gaussian and non-Gaussian scenarios. Results are compared to the Kalman filter and Maximum A Posteriori (MAP) in Exponential and Logistic distributed noise. The proposed method outperforms the other methods by an average of 17% yet maintaining low mathematical complexity.

The demand for Telehealth is rapidly increasing worldwide. Digital solutions in the current epidemic are revealing the powers and flaws of current Telehealth infrastructures. Telehealth brings remote access to medical facilities and covering the extent of physicians and health services. The outbreak of COVID-19 emphasizes the necessity for timely tracking of persons who are infected, and preferably, their connections. Telehealth facilities are speedily becoming a frontline force in the struggle to lessen healthcare-linked COVID-19 spreads, and eventually shielding healthcare professional. Whereas telehealth can substitute competence and accessibility, its dependence on real-time communication of medical records over the cloud also generates danger. At each phase of the practice, hostile measures may happen, together with diagnostic blunders, technical problems, and patient confidentiality and safety defilements. This paper developed a highly secure and robust decoder for the Telehealth model to monitor the patients' vital signs and psychological signals. The proposed Telehealth system reduced the transmission power and congestion on the database and ensured secured reliable data at the receiving end.

Smart societies have an increasing demand for quality-oriented services and infrastructure in an industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numerous challenges. Among them, secured energy demand-side management (DSM) is of particular concern. The IIoT renders the industrial systems to malware, cyberattacks, and other security risks. The IIoT with the amalgamation of big data analytics can provide efficient solutions to such challenges. This paper proposes a secured and trusted multi-layered DSM engine for a smart social society using IIoT-based big data analytics. The major objective is to provide a generic secured solution for smart societies in IIoT environment. The proposed engine uses a centralized approach to achieve optimum DSM over a home area network. To enhance the security of this engine, a payload-based authentication scheme is utilized that relies on a lightweight handshake mechanism. Our proposed method utilizes the lightweight features of the constrained application protocol to facilitate the clients in monitoring various resources residing over the server in an energy-efficient manner. In addition, data streams are processed using big data analytics with MapReduce parallel processing. The proposed authentication approach is evaluated using NetDuino Plus 2 boards that yield a lower connection overhead, memory consumption, response time, and a robust defense against various malicious attacks. On the other hand, our data processing approach is tested on reliable datasets using Apache Hadoop with Apache Spark to verify the proposed DMS engine. The test results reveal that the proposed architecture offers valuable insights into the smart social societies in the context of IIoT.

The electricity industry has been developed through the introduction of the smart grid. This has brought about two-way communication to the grid and its components. The smart grid has managed to increase the efficiency and reliability of the traditional power grid over the years. A smart grid has a system that is used to measure and collect readings for power consumption reflection, and the system is known as the Advanced Metering Infrastructure. The advanced metering infrastructure has its components too which are the smart metre, metre control system, collector or concentrator and communication networks (wide area network, neighbourhood area network, and home area network). The communication networks in the advanced metering infrastructure have created a vulnerability to cyber-attacks over the years. The reliability of the power grid to consumers relies on the readings from the smart metre, and this brings about the need to secure the smart metre data. This article presents a review of key management methods in advanced metering infrastructure environments. The article begins with an overview of advanced metering infrastructure and then shows the relationship between the advanced metering infrastructure and the smart grid. The review then provides the security issues related to advanced metering infrastructure. Finally, the article provides existing works of key management methods in advanced metering infrastructure and future directions in securing advanced metering infrastructure and the smart grid.

Diseases related to poor water and sanitation conditions have over 200 million cases reported annually, causing 5–10 million deaths world-wide. Water quality monitoring has thus become essential to the supply of clean and safe water. Conventional monitoring processes involve manual collection of samples from various points in the distribution network, followed by laboratory testing and analysis. This process has proved to be ineffective since it is laborious, time consuming and lacks real-time results to promote proactive response to water contamination. Wireless sensor networks (WSN) have since been considered a promising alternative to complement conventional monitoring processes. These networks are relatively affordable and allow measurements to be taken remotely, in real-time and with minimal human intervention. This work surveys the application of WSN in environmental monitoring, with particular emphasis on water quality. Various WSN based water quality monitoring methods suggested by other authors are studied and analyzed, taking into account their coverage, energy and security concerns. The work also compares and evaluates sensor node architectures proposed the various authors in terms of monitored parameters, microcontroller/microprocessor units (MCU) and wireless communication standards adopted, localization, data security implementation, power supply architectures, autonomy and potential application scenarios.

One of the viable solutions for effective spectrum management is cognitive radio. Single sensing systems are prone to interference; thus, the use of cooperative spectrum sensing. This paper aims to determine the required number of cognitive radios that would optimize the performance of a communication network in terms of energy utilization and bandwidth requirement. The cognitive sensing technique used was energy detection due to its reduced energy, computational, and communication resources requirement. The channel noise variance was set to −25 dB. Spectrum sensing was carried out at a frequency of 936 MHz and bandwidth of 200 kHz. Machine learning was first used to enhance the specificity of detection to minimize interference. Genetic Algorithm (GA) and Simulated Annealing (SA) were used to optimize the number of cognitive radios putting into consideration all constraints in the network. Genetic Algorithm gave a better result of two optimization techniques used. It gave an overall reduction of 40.74% in energy conserved without affecting the detection accuracy.

This chapter provides the Internet of Things (IoTs)-based Smart Agriculture System. The system aims at improving agricultural production in Botswana by remotely monitoring farms of all types using the Internet of Things (IoTs). The system uses sensors to monitor different parameters for these living things to ensure that a proper environment is maintained at all times. This chapter gives a detailed explanation of the data loggers which transmit data wirelessly to a central point located on the farm. The central location is referred to as a gateway, and it is where the farm employees can visualize and analyze data. The on-farm network of sensors and gateway is linked to an online server through General Packet Radio Service (GPRS) and Satellite to allow for remote online data acquisition (DAQ). In this chapter, low cost and reliable wireless data acquisition system are implemented in real time at the banana field. The moisture stress, reducing the usage of excessive water, rapid growth of the weeds is achieved with the implementation of sensor-based site-specific irrigation. Internet of Things-based remote control of irrigation can also be achieved in the system. The implemented system can be used to transfer the fertilizer and other chemicals to the field with the help of adding new sensors and valves.

This chapter gives an overview of environmental monitoring systems using wireless sensor network, big data, and Internet of Things (IoTs). This chapter outlines the effect of climate change on wild animals and also discusses innovations in response to climate change. Electric fences are commonly used to control and manage the movement of animals in game reserves, private game and farms to restrict intruders such as unwanted predators and humans from the bound area. Wireless sensor network-based system for intruder detection and monitoring is presented in this system to minimize the human-animal disputes in Africa. It is challenging to observe elephants monitoring since these huge animals travel for very long distances. The biggest challenge in the existing wireless-based anti-poaching system is the limited network or no coverage. As a result, the non-monitored animals are simply subjected to poaching. Taking advantage of WSN, an anti-poaching system is proposed in this chapter.

This chapter presents a system to detect foot and mouth disease as early as possible in a herd of cattle using wireless sensor networks. The system combines animal behavior and sensor values to determine the status of the cattle in terms of foot and mouth disease. The system combines animal behavior and sensor values to determine the status of the cattle in terms of foot and mouth disease. The system first measures an average response of a cow under normal circumstances with the focus being on the measurements of body temperature; distance covered; and feeding rate every 2 h. Data regarding the state of the cow is sent at certain time intervals to the farmers using ZigBee via a gateway. This chapter provides results of the trials performed on the project. A signal is acquired from a cow sensor node and transmitted to the Gateway which is interfaced to a computer running LABVIEW software as the graphical user interface of the system. The trials were done both for negatively and positively diagnosed cows.

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, that is, to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the medium access control (MAC) layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

eLoran needs to satisfy the user requirements for accuracy, availability, continuity and integrity to fulfil its envisioned role as a backup system to GPS. The eLoran accuracy performance at receiver locations is dependent on the variations of the Additional Secondary Factor caused by changes in the ground conductivity. This paper focuses on eLoran accuracy performance analysis for maritime harbour entrance and approach. Based on observational ASF data, a new, updated and more accurate empirical model for eLoran time of arrival variance that improves upon the existing models in the literature is proposed. The time of arrival variance algorithm developed herein incorporates the long-term effects of the changes in terrain conductivity on the pseudorange measurement errors of the received signals at the user’s receiver location. The developed model has been used to determine the diluted position accuracy of eLoran over the North European maritime region, and for harbour entrance and approach (HEA) for SOLAS ports in Ireland and United Kingdom. The results show that if the European eLoran system was reintroduced, positioning accuracy of less than 20 m would be achievable in the North Sea and less than 10 m at the SOLAS ports if differential Loran was also available there. These would meet the navigational requirements for HEA. However, in the Irish sea down through the Bay of Biscay, the positioning error would exceed 80 m and be unacceptable for marine navigation, especially compared to GPS. This suggests that the inclusion of two or more eLoran transmitters located further South-West of Ireland are needed to enhance coverage in this area. The results of this work can also provide the radio planners and authorities regulating sea traffic with the insight of where to deploy new resources such as reference stations.

The optimization of 2D ultrasound arrays can be efficiently realized through the use of simulated annealing (SA) as reported in many recent works. The main limitation of SA resides in the amount of resources required and the optimization time. In this work, the application of the genetic algorithms (GA) in 2D arrays optimization is presented to evaluate the potential of these algorithms compared to the simulated annealing in terms of processing time and output beam profiles. GA have been used in the optimization of multivariable cost functions in many applications as power systems analysis, wireless sensor arrays in telecommunication and they provided satisfactory results in a relative short time. The 2D ultrasound arrays optimization can also be formulated in a similar way as the problems occurring in these domains, making genetic algorithms a potential candidate to solve them. Although GA are reported to not be as efficient as SA in the optimization of medium and large 2D arrays, the aim of this paper is to evaluate their real ability when compared to the SA. Preliminary results showed a fast convergence time of genetic algorithm for comparable acoustical properties for the optimized arrays compared to SA.

For most of the current steganography techniques, the information-hiding process modifies almost all cover components. Hiding data in the whole image may affect visual quality and increases the possibility of data loss after any possible attacks. In this chapter, a new region-based steganography method, CR-BIS, which hides data in the robust regions of the image, is proposed. First, the secret data are encrypted via a highly secure encryption algorithm. Second, SURF is used to locate the strongest sections in the image. Then data embedding is accomplished in a content-based style by varying the wavelet transform coefficients of those strong sections. The robustness of the proposed algorithm increases when second-level DWT is used to hide data, especially against JPEG compression. However, applying the same scheme to the median and the low-pass filters remains difficult. Utilizing higher DWT levels is useful to enhance the robustness.

Steganography is the art and science of invisible communication. It has recently been the core of attention by the information-security community. This chapter is concerned with summarizing the conclusions that have been arrived at throughout conducting the present work. It further showcases some possible future research challenges that need to be studied in this area.

This chapter deals with two main aspects; the first one is concerned with introducing an improved robust and secure image steganography system. The original algorithm presented by Mali et al. gives adequate results in terms of robustness; however, the algorithm cannot be considered reliable, as some data is lost. In order to overcome the problem of the lost data due to the misidentified blocks, an embedding map was proposed to specify the location of the blocks that can be used for embedding a secret message. Such a technique, the embedding map, is very important if one needs to start the extracting phase correctly and accurately. Besides, any loss in the embedding map will in turn lead to data loss. Consequently, the embedding map will be hidden using SURF and DWT to assure robustness and to increase the level of security of the proposed system. The secret data can be embedded using the original algorithm (DCT-based) proposed by Mali et al. More so, the experimental results show the ability of the new algorithm, namely IRSS, to overcome the problem of losing data even with JPEG compression or Gaussian noise.

With the expansion in digital-communication technologies and the rapid growth of network bandwidth, the Internet has turned out to be a commonly used channel for transmitting many documents—for instance, audio, video, image, and text—in digital form. Many practices have been offered and developed for providing the secure transmission of data. The focus of the current research is on the design of data-hiding techniques used for transmitting secret data where digital images are selected as the cover-media. This chapter has identified the problems in the present image-steganography schemes.

Worldwide interoperability for microwave access (WiMAX) base stations (BS) use the fractional frequency reuse (FFR) technique to control inter-cell interference in cellular networks. One of the challenges in FFR is the unused radio resource in the downlink (DL) sub-frame. This paper proposes a dynamic resource utilization approach to eliminate the resource wastage typical of the conventional FFR technique. The proposed approach not only enhances the radio resource utilization of the BS efficiently, but also takes into account the variations in the population density. We deal with the partial usage of sub-channel mode in the DL sub-frame of the WiMAX BS based on orthogonal frequency division multiplexing access. A new FFR data rate formula is derived based on theoretical analysis. Quantitative measurements demonstrate that the dynamic model gives optimal results, enhancing the conventional FFR in terms of a variety of metrics. The data rate, subcarrier efficiency, and spectral efficiency are increased by 2.176 Mbps, 0.14 bit/subcarrier/burst, and 0.218 bps/Hz, respectively. In addition, in the new approach, the DL sub-frame is fully utilized (100 %), the number of served users is increased by 28.57 %, and the number of utilized slots is increased by 34.48 %. The effective utilization of resources and bandwidth characteristic of this approach makes it a strong candidate for BS deployment in cellular networks where the user density changes constantly.

Resource allocation management is one of the effective factors in the performance of WiMAX base station. Various goals could be achieved when the resource allocation scheme exploits in the right direction. However, resource allocation schemes lack a uniform assessment metrics. Where, most of the researches trying to show author's perspective in the results to show design pros, whilst the overall performance in resource allocation perspective is mostly missing. This paper presents the coordination between goals and design parameters that must be considered in the design phase to exploit the available features of the PHY and MAC layers and avoid the limitations. Moreover, this paper proposes a new method of primary assessment for resource allocation algorithms to ease conducting a fair comparison between the relevant algorithms. The assessment methodology based on a set of evaluation questions. The obtained results showed that the new assessment method distinguishes the overall performance to provide fair comparison.

Wireless multi-hop relay networks have become very significant technologies in mobile communications. These networks ensure data rate transfer and covera ge extension with a low cost. In this study two typ es of relay are studied; Fixed Relay Node (FRN) and Moving Relay Node (MRN). Where system analyses for uplink and downlink transmission are derived in thi s study. Moreover the optimal relay location of FRN was proposed to provide a maximum achievable rate at user in cell edge region. Finally, a new algorith m was suggested to balance and control on the transmi tted power of MRN over cell size to provide the required SNR and throughput at the users inside veh icle with reducing the consumption transmitted rela y power. Numerical results indicate an enhancement in received signal strength for users at the cell edg e from (-90 to -65) dBm and 40% increment from all cell size after de ploying FRN at proposed locations. As well as, the results revealed that there is saving nearl y 75% from transmitted power in MRN after using proposed algorithm. ATDI simulator was used to verify the nu merical results, which deals with real digital cartographic and standard formats for terrain.

This paper aims to improve the detection accuracy of the energy detection-based cognitive radio system using machine learning while varying the number of cognitive radios used for sensing. It has been an exploratory study in order to identify a suitable number of machine learning-enabled cognitive radios that could be used to improve the performance of the system in terms of sensitivity. Several machine learning techniques have been tested at a low SNR (-25dB) in order to simulate conditions where energy detectors perform poorly. The number of cognitive radios has been varied from three to eighteen in order to explore the potential of increasing the data available for machine learning. Results have revealed that with three cognitive radios, the overall detection accuracy of 97% could be achieved in the energy-detection based system despite the low SNR condition. It has also been discovered that increasing the number of cognitive radios has improved the True positive rate for primary user detection from 98% to >99% with Fine Tree algorithm but at the expense of the overall accuracy of the system. Therefore, demands of specific applications are required in order to identify the number of cognitive radios to employ. Overall, the research presents the potential of using a minimal resource-demanding cognitive radio sensing method (energy detection) for sensing without compromising the detection accuracy of the system. It also improves the spectrum utilization of the system by reducing the probability of false alarms considerably. It highlights improvements that can be made to the conventional energy-detection system through machine learning while retaining the simplicity of the cognitive radio system

In this paper a robust approach for detecting QRS complexes and computing related R-R intervals of ECG signals named (RDQR) has been proposed. It reliably recognizes QRS complexes based on the deflection occurred between R & S waves as a large positive and negative amplitude differences in comparison with respect to other ECG signal (P and T) waves. The proposed detection approach applies the new direct algorithm applied on the entire ECG itself without any additional transform like (wavelet, cosine, Walsh transform, etc.). According to the strategy based on positive and negative deflection it overcomes the problem of QRS direction positive (upright) or negative (inverted). Three different types of ECG online database with duration of 10 sec (MIT-BIH Arrhythmia, ST Change Database and Normal Sinus Rhythm) are used to validate the detection performance. The results are demonstrated that the proposed detection approach achieved (100%) accuracy for QRS detection also very high accuracy in evaluating related R-R intervals.

In all applications which are based on Mobile Ad-Hoc Networks, node mobility has a significant impact on the performance of routing protocols; consequently affect the usefulness of these applications. This paper presents an investigation and analysis of the performance of different routing protocols (AODV, DSR and OLSR) under freeway mobility pattern in motorway surveillance system based on Ad hoc camera network as a case study. The evaluation and analysis were performed for several different performance metrics and under varying network conditions. It has been shown from the results that under various mobility speeds and different traffic loads, AODV outperforms DSR and OLSR protocols, with respect to network throughput and protocol overhead. The conclusions of this study are important to provide a qualitative assessment of the applicability of these protocols to realworld motorway surveillance systems, and also as a basis for developing new ways to improve routing performance under different freeway mobility pattern conditions.

Multi-hop relay is considered to be one of the main aspects of the LTE-A to meet the growing demand for coverage extension and capacity enhancement by improving LTE performance. It has recently been the center of attention by the wireless communications community.

This chapter introduces three new methodologies to enhance the performance of LTE cellular networks (Yahya, Aldhaibani, & Ahmed, 2014). The first methodology focuses on RN deployment in the cell and called Optimum RN Deployment (ORND) to enhance the coverage area and capacity at cell-edge region. RN is considered as a solution to address low SINR at the cell edge, resolve coverage holes due to shadowing, and to meet the access requirement of nonuniform distributed traffic in densely populated areas to improve coverage and throughput. However, the interference between stations is an important problem that is associated with the RN deployment in the cell. This methodology considers the mitigation of the interferences between the stations and ensures the best capacity with the optimization of transmission power. ORND is based on mathematical analysis of determination of the optimum location for RN, optimal number of relays per cell, suitable power for each RN, and design a frequency reuse scheme, which exploits available radio spectrum. Second methodology, called Enhance Relay Link Capacity (ERLC), addresses the relay link problem, where this link carries information generated by the RN and users attached to it to BS. Although the long distance between the proposed relay location and BS improves the coverage at cell boundaries, this distance also degrades the relay link efficiency and increases the probability of outage. On the other hand, the approximation of the relay location does not achieve the desired goals to enhance coverage at the cell-edge region. ERLC introduces active solution and easy implementation to solve relay link problem. The values of parameters which are used in these models are based on the LTE system specifications and presented by (3GPP, TS. ETSI, 2007) and mentioned in Table 4.1. Third methodology focuses on enhancing the throughput and RSS for the users inside public transportation vehicles as well as proposes a new algorithm called Balance Power Algorithm (BPA) that aims to minimize the transmission power consumption for Moving Relay (MR). Summary of research on improving coverage and capacity is shown in Fig. 3.1.

The well-known generational phase of mobile telecommunications started in the early 1980s, beginning with the introduction of the so-called First Generation (1G) of mobile telecommunications standards. The 1G analog cellular systems supported voice communication with limited roaming and short-range radio waves telephones. Later, Second Generation (2G) was introduced as a digital systems and promised higher capacity and better voice quality. 2G cellular telecom networks were commercially launched on GSM (Global Systems for Mobile Communication) standard in Finland in 1991 (Dahlman, Parkvall, & Skold, 2011a).

Cell edge users face not only a high propagation loss in their own cell but also have considerable interference from neighboring cells. Therefore, most of the interferences increase when the user approaches to cell boundaries. The signal from BS degrades due to an increase in the path loss from BS, while signals as interference from neighboring cells increase. Figure 4.1 shows RSS for user along with cell diameter. A low level of RSS at cell boundaries with an increasing level of interference causes blocking for many users in this region as shown in Fig. 4.1.

Mobile communications have come a long way since the introduction of the first mobile telephone systems in the 1950s by German National Railway (Dahlman, Parkvall, & Skold, 2011). Aside from the fact that the user equipments (UEs) were bulky and power hungry, there were other serious issues such as frequency allocation and the transmitted power of the base station (BS). Therefore, these primitive services severely limited the number of active users to the number of channels assigned to a particular frequency zone (Sesia, Toufik, & Baker, 2011).

Wireless Sensor Networks (WSNs) provide reliable and affordable infrastructure for various applications ranging from environmental monitoring, industrial automation, telemedicine, to military surveillance. These networks allow monitoring processes to be conducted remotely, in real-time and with minimal human intervention. Water quality monitoring is essential to the provision of clean and safe water. In Botswana, Water Utilities Corporation (WUC), has adopted a conventional like process that employs several independent hand held meters for sampling different water quality parameters manually. However, this process has proved to be ineffective since it is expensive, time consuming, requires considerable human resource capacity and lacks real-time results to promote proactive response to water contamination. In this work, an integrated WSN based solution that employs Libelium's Waspmote platform has been developed. The sensor node is based on ATMEL's ATmega 1281 8-bit low power microcontroller which can operate for more than a year without recharging its battery. Results have shown that the proposed system managed to sample associated water quality parameters in real time with the same accuracy as currently adopted methods. In addition, the system is autonomous, easy to install, highly scalable and has a relatively high sampling rate which improves the temporal resolution of the monitoring process.

Camera-based surveillance is an important technology to monitor people, assets and places, for the applications of increasing physical security. Access to information services whilst on the move is becoming increasingly prevalent within transport systems. This paper examines motorway vehicles equipped with wireless communication nodes to obtain images from the cameras distributed along a motorway. Exchanging the data (images) still remains a challenge to provide access aboard vehicles, particularly when travelling on high-speed motorways. This paper performed an analysis to examine the performance of a motorway surveillance systems based on Ad Hoc networks (WAHCN). The paper focus on studying the effect of the number of hops between sender (camera) and receiver (vehicle), packets rate, and packet size on the performance and behavior of the motorway surveillance systems which used (WAHCN) to demonstrate a clear view of the suitable values for these parameters to get high performance and good image quality in these type of systems.

The demand for faster internet connections to access wireless multimedia applications, Aeronautical Communication Networks (ACNs) and internet services has resulted into rise of developing broadband wireless technologies in recent years. The demand for higher data rates was the backbone for developing wireless communication technologies such as Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) and High-Speed Packet Access (HSPA). The big challenge with wireless communications lies with providing Quality of Service (QoS) under various environmental challenges and maximizing resource utilization at the same time. In wireless communication, the support for QoS is difficult due to the unpredictable nature of wireless channels. Opportunistic Scheduling plays a big role towards meeting QoS requirements and managing resources in aeronautical communication networks. Various opportunistic schedulers focus on increasing the system capacity of a wireless communication network, while some aim on improving the system’s fairness and throughput. With such interest in opportunistic scheduling, the paper focuses on reviewing recently proposed opportunistic scheduling algorithms, the objectives they were designed for, and their shortcomings. An effective opportunistic scheduling algorithm with hierarchical modulation technique is presented in this paper. The algorithm focuses on the ability to allocate resources between two users with different channel conditions; that is a user with good channel conditions and a user with bad channel conditions, to maximize the system’s throughput and maintain fairness.

This paper presents the construction of large girth Quasi-Cyclic low density parity check (QC-LDPC) codes and a new multicarrier frequency hopping spread spectrum (MCFH-SS) system. The performance of newly obtained codes is evaluated by comparing with Reed Solomon (RS) codes. The computer simulation results show that the two girth-twelve QC-LDPC codes significantly outperform conventional RS codes with a gain of 2.1 dB at

Frequency hopping spread spectrum with noncoherent M-ary frequency shift keying system is considered. In this study Reed Solomon codes RS (255, 223) are employed in a standard error correction role to provide some Anti-Jamming (AJ) capability with 8-bit symbols. Noise has been added to RS encoded data, which is demodulated at RS decoder perfectly. Matlab simulations have been implemented for numerical results. Graphical results have been plotted between the probability of an erasure versus ρ using RS (255, 223) code for 1 and 2 kHz frequencies. The simulation results have proved that system having RS (255, 223) code with M = 32 require substantially less signal to jammer power ratio to achieve the same bit error probability.

The technical design challenge of Mobile WiMAX is to exploit the limited available spectrum of the downlink subframe efficiently while achieving the desired goals behind the resource management algorithms. Various goals can be achieved when the resource management algorithms exploited in the right direction. This paper presents the coordination between MAC layer scheduler objectives and PHY layer burst allocation algorithm design parameters. Utilizing PHY layer operation mode with MAC layer coordination leads to increase the proportion of the desired objectives achievement. The presented methodologies of the burst allocation algorithm design can achieve higher satisfaction of MAC requirements and avoid the limitations. The study has demonstrated that resource allocation algorithm requires many factors and parameters to be employed in the correct direction to enable efficient use of the downlink resources to satisfy MAC layer requirements.

The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named “Rising Falling Transition Method (RFTM)” is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.

Resource allocation management is one of the effective factors of WiMAX base station performance. Various goals could be achieved when the resource allocation scheme exploits in the right direction. However, the assessment of the resource allocation algorithms lacks to a uniform performance metrics. Where, most of the researches are trying to show authors perspectives in the finding results to show the design pros, whilst the overall performance in resource allocation perspective mostly not exist. This paper proposes a new style of primary assessment for the resource allocation algorithms to ease conducting a fair comparison between the relevant algorithms. The assessment methodology based on a set of evaluation questions. The obtained results show that the new assessment method distinguishes the overall performance to provide fair comparison.

The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user’s location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain.

The current growth of mobile data usage and emergence of new applications have greatly motivated the Third Generation Partnership Project (3GPP) to work on Long Term Evolution (LTE). LTE is the most recent standard in the mobile network technology to be developed based on GSM/EDGE and UMTS/HSPA network technologies with the aim of optimizing the capacity and speed of 3G mobile communication networks. In this chapter, the structures and features of fourth generation (4G) LTE are investigated at the early stages of telemedical research. The chapter also provides a comparison of WiMAX and LTE standards on various aspects, as well as the potential of technology in healthcare applications. Issues and challenges of wireless technologies in healthcare applications and services are finally presented.

The current growth of mobile data usage and emergence of new applications have greatly motivated the Third Generation Partnership Project (3GPP) to work on Long Term Evolution (LTE). LTE is the most recent standard in the mobile network technology to be developed based on GSM/EDGE and UMTS/HSPA network technologies with the aim of optimizing the capacity and speed of 3G mobile communication networks. In this chapter, the structures and features of fourth generation (4G) LTE are investigated at the early stages of telemedical research. The paper also provides a comparison of WiMAX and LTE standards on various aspects, as well as the potential of technology in healthcare applications. A survey on telemedicine services using traditional wireless system is presented. Finally, issues and challenges of wireless technologies in healthcare applications and services are deliberated.

Simultaneous multithreading by use of embedded parallel systolic filters is a novel technological approach to achieve multiprocessing. It is important for the designers to ensure that FPGA chips that are fully operational. There is great emphasis on the design area, performance, challenges and opportunities posed by multi-tasking as a result of the huge number of inputs and outputs required by the design. The Embedded Concurrent Computing Architecture proposed is implemented on a FPGA chip. There are expected speedups in the implementation based on the results shown in this proposal. Synthesis has been used in gathering of the results with implementation being achieved by use of low complexities in the FPGA usage and frequency. The efficiency of the new model is over 75% with the performance of the design is secured for a tolerance of 2 m for 25 m range. The Particle filter tolerance is less than 1m with an operating frequency of 212 MHz or thereabouts.