Journal of Communication Engineering
Volume:9 Issue: 2, Summer-Autumn 2020

Providing high quality mobile internet service to passengers of high speed railway (HSR) has a key role to its market share. The LTE radio network has been raised as candidate for providing high data rate for this purpose. However, in the LTE radio network, handover (HO) becomes an important challenge at high moving speeds. The 3GPP standard body, has introduced several events for LTE HO decision making. To date, there has not been an analytical model to compare these events for using in HSR system. We have mathematically analyzed these events to compare their performances in which the effect of speed has also been considered. The results has been validated by comparison with simulation which shows close matching. The analytical model can be used for introducing new modified events which specially will be designed for HSR system.

 Radio frequency identification (RFID) and wireless sensor networks (WSNs) are two important and widely applied wireless technologies with limitless future potential. RFID is used to detect object location, while WSN is used for environmental sensing and monitoring. The integration of RFID and WSN not only provides identity and location but also facilitates environmental condition sensing. However, RFID data contains excessive duplication, which results in time delay and increased energy consumption, resulting in wastage of various network resources. This paper proposes a hybrid network designed by the integration of WSN and RFID and consisting of seven types of nodes. In this architecture, the entire network is divided into clusters and this clustering is obtained by particle swarm optimization. In addition, it also proposes an algorithm to overcome the issue of redundant data on this hybrid network. Simulation results show that the proposed algorithm reduces both data redundancy and processing time compared to existing algorithms.

Wireless body area networks (WBANs) are a kind of wireless sensor network created in order to make more acceptable utilization of the hospital resources, detect medical signs or symptoms earlier, and consequently decline the costs of medical care. As a majority of the wireless networks, it has no infra-structure, and thus sensor nodes embedded in the body enjoy small level of energy. Therefore, initial termination of the wireless node energy on the basis of the message transmission in the network may interrupt the entire network process. Also, increasing the temperature of the sensor node due to sending and receiving information, can cause an increase in normal body temperature and disrupt the body's functioning process. In this article, a temperature-aware routing in the wireless body area network based on meta-heuristic clustering method is presented. In this method, in order to find the appropriate cluster head to transfer data to the root, network parameters are examined in the form of membership function of the ant colony optimization meta-heuristic method. The simulation outputs indicate the greater ability of this new method in comparison to other available techniques under the same conditions.

In this paper, we simulated a diffusion adaptive network in the underwater environment. The communication method between the nodes of this network is assumed to be the visible light communication technology (VLC) which in the underwater condition is known as the UVLC. The links between the nodes in this case are contaminated with the optical noise and turbulence. These contaminations are modeled with the proper statistical distributions depending on the underwater conditions. The optical turbulence modeling link coefficients are shown to be following the Log-normal distribution which its mean and variance are directly dependent on the temperature and the salinity of the simulated water and the assumed distance between the diffusion network nodes. The performance of the diffusion network in using UVLC technology is then analyzed both with simulations and theoretical calculations and the results are presented using the steady-state error metrics. Our analysis showed that the diffusion network can be implemented underwater with the VLC technology providing that the distance between the network nodes is less than 10 meters. Also, in order to guarantee the convergence of the adaptive network, the water salinity level and temperature must not exceed the values that are presented in our simulations.

An ultra-compact ultra-wide band (UWB) bandpass filter (BPF) with a very sharp rejection for the high-speed wireless communication applications is proposed. Thefunctional basis of the proposed structure is based on the multi-mode resonator (MMR)technique. The suggested ultra-wideband filter is realized by using two doublet parallelcoupling lines, two symmetrical open stubs and tri-section step-impedance open stubswhich are located at the center of the configuration. In order to analyze the suggestedconfiguration, the even-mode and odd-mode methods have been utilized because of theproposed UWB BPF is a symmetrical structure. Five modes which are including threeeven modes and two odd modes have been placed within the UWB band. By changing thedimensions of the tri-section step-impedance open stubs and two symmetrical open stubs,the resonant modes of the constructed MMR can be tuned. These two parts have beenmainly applied to adjust the resonant modes into desired passband. Changing thedimensions of the two symmetrical open stubs affects both the even and odd modes. Butthe tri-section step-impedance open stubs can only specially control the even-moderesonant frequencies, whereas the odd-mode ones are fixed. Consequently, the centerfrequency and the bandwidth of the proposed configuration can be simply adjusted.Experimental verification is provided and a reasonable agreement between simulated andmeasured results has been achieved. The proposed UWB BPF has a passband covers 3.55to 10.65 GHz and the measured 3 dB fractional bandwidth (FBW) is about 100%.

A planar multi-beam array with a co-planar Rotman lens beamformer is introduced for wireless applications. The array consists of 8 linear series-fed subarrays with proximity-coupled patch elements. The Rotman lens feeds the subarrays through coupling slots. To reduce beam squinting, the subarrays are fed from the center. The coupling slot feeds each arm of a subarray 180° out of phase. To compensate out-of phase feeding, two feeding arms of each subarray are designed in the opposite direction. Also, cross-polar radiation is reduced significantly. In order to reduce the size of radiating patches to fit within array cell size, they are formed by four sub-patches with indentions and are fed by microstrip line from feed layer with two matching sections to improve the bandwidth. Measured results of the array structure in terms of the S-parameter of beam ports and radiation patterns are presented.

Wireless sensor networks (WSNs) are made up of thousands of small sensor nodes that are capable of detecting, calculating, and transferring data via networks. Although there are certain resource limits, wireless transmission is still an effective way to transport information. The secure transfer of data is critical in a WSN. Key management techniques have been established for the purposes of security. Key pre-distribution is one of the key management methods used to assign keys to the devices before deploying them in the wireless sensor networks. The challenges of these schemes include memory consumption due to limited device resources, scalability, connectivity, and resilience against node capture attacks. Combinatorial designs with neutrality characteristics, which are based on mathematical structure and impose low computational overhead and communication overhead, are used in key pre-distribution and information security of wireless sensor networks. In this paper, some key pre-distribution methods based on the combinatorial designs are reviewed. Finally, the comparison of performance parameters is illustrated in tables. Suggestions to improve future research are considered as well.

Fog computing is a method for improving cloud computations performance attempts to expand the Internet of things processes and distribute cloud services in the network edge. This paper proposes a real-time outsourcing and offloading mechanism to optimize the cache and CPU consumption in resource allocation to IoT users in a fog-based processing environment. Based on this mechanism, the computations that require heavy processing are moved to the network edge, and computations with lower processing needs are processed inside user devices. According to the simulation results, the average users' average service latency in the proposed method SPA-(Offloading) for 200 users has been improved in the range of 0.8 to 0.6. In addition, the profits of cloud and fog service providers for 220 users are higher than other methods. Also, the average system cost performance was evaluated, which is better than the other methods. The results show that this mechanism improves cache consumption, processing time, and optimal resource allocation to IoT users.

A new design of a dual-band printed dipole antenna with integrated balun is presented in this study. The antenna in simple form is composed of a printed dipole, integrated balun, a Γ-shaped feed, and a square-shaped ground plane, which achieves a fundamental resonance at 2.4 GHz frequency. A pair of rectangular-shaped resonators are positioned on two sides of the Γ-shaped feed in the second designing step innovatively to accomplish the additional resonance at 5.5 GHz as the second frequency band of the WLAN. Two electromagnetically coupling mechanisms prepared between the Γ-shaped feed and dipole arms, and rectangular-shaped resonators, which lead to creating two operating frequency bands. An equivalent circuit and a parametric study presented to explain the antenna performance in this work. Experiments approve that the proposed dual-band antenna has two impedance bandwidths of 14.1% (2.23-2.57 GHz) and 25.7% (4.83-6.26 GHz) with average gains of 12.10 dBi and 6.36 dBi over the first and second frequency bands, respectively, which is cover the 2.4/5.5 GHz WLAN frequency bands successfully.

The industrial revolution and the spread of electronic technologies and wireless communications have led to the production of small smart sensors with low consumption and low-cost benefits. Sensor nodes work as autonomous systems with low cost, small size, and wireless communication media but work with low resources. The most significant item in the operation of Wireless Sensor Networks (WSNs) is finding the spatial information of objects, including retrieval and identification of events, routing according to geometric position, monitoring and tracking. Localization in WSNs divides into two range-based and range-free categories. In this paper, to overcome the weaknesses of DV-Hop, a hybrid model based on the Krill Herd Algorithm and Ant Colony Optimization called KHAACO was proposed for locating unknown nodes. The aim of this study is to provide an approach for estimating the location of sensor nodes with minimal error and using KHAACO to estimate the location of unknown nodes and using the motion characteristics of other krill, foraging, and spatial dispersion of the KHA and optimizing it with ACO. The evaluation of the hybrid model in the MATLAB environment has been done based on error criteria and energy consumption. The results showed that the hybrid model compared to DV-Hop, DV-Hop-ACO, and DV-Hop-PSO reduced the Localization error. The value of reduction of localization error for 90 anchor nodes and 450 sensor nodes was equal to 9.95%.

In this paper, we investigate the multiple-input multiple-output systems (MIMO) and the co-channel interference cancelation in these systems. In recent years, the usages of array antennas in the receiver/ transmitter or both have greatly increased in telecommunication systems. Due to the increasing transmission data rate and the decreasing error rate, the MIMO systems in wireless communication systems are very important. In the third, fourth, and fifth generations of wireless communications in order to increase the network capacity and spectrum efficiency, the same frequency channel is allocated to different users. This leads to co-channel interference for the users with the same frequency channel. Thus, it is essential to eliminate inter-channel interference in telecommunication networks. In this paper, an adaptive algorithm is evaluated to eliminate the co-channel interference in MIMO systems. We also investigate the algorithm in indoor and outdoor environments using the Wiener model, with direct and indirect channels using the Rayleigh and Rice fading models and calculate the error probability in different conditions. In order to improve the performance of the system in uplink transmission, auxiliary antennas and linear arrays of antennas at the receiver are used. The results of the proposed algorithm are simulated and compared with the previous conventional methods.

Wireless Sensor Networks (WSNs) are used to observation and monitor events in different environments. The successful operation of WSNs depends on locating the sensor nodes. The location of the nodes must be available to detect the occurrence of events and receive packets sent by nodes. Therefore, a key step in the design phase of WSNs is to determine localization algorithms. One of the known algorithms for locating unknown nodes is the DV-Hop algorithm. DV-Hop localization algorithm is a classic range free localization algorithm in WSNs. This algorithm operates based on distance and number of steps and uses beacon nodes to detect the location of unknown nodes. But positioning error is one of the main problems in DV-Hop. Researchers have used a variety of methods to correct positioning errors. In this paper, we divide the methods used to improve DV-Hop into four categories (meta-heuristic algorithms, RSSI, Distance Vector, and Weighted Centroid Localization (WCL)). Each method, based on its own performance has capabilities and features that help reduce DV-Hop error. This paper covers all DV-Hop literature in Elsevier, Springer, IEEE and Other Journals. Based on the performed studies on different methods in order to improve DV-Hop, we came to the conclusion that the distance vector method is more efficient. Using distance vector to improve DV-Hop is equal to 38%. The distance vector method includes more accurate localization information by varying the distance and number of steps.