It would be dire need of accurate and fast wireless communication in the present as well as future era. Few years ago, error free wireless link design was only challenge and it had opened a way of digital communication. Now speed of communication becomes vital and essential part of research in the field of wireless communication. In wired communication category, optical communication is a solution to achieve targeted data speed but wireless channel for serial communication is highly disturbed with the phenomena of multipath and frequency selective fading for a data rate over a specific limit. A new technology named Orthogonal Frequency Division Multiplexing (OFDM) is a perfect key to open this locking situation of limited data rate with optimum use of bandwidth in the multipath fading channel. Supporting high data rates and robust response against narrowband interferences, OFDM had penetrated itself in many broadband wireless services. There are many issues with OFDM too and one of them is synchronization between orthogonal frequency channels at receiver. It is mandatory condition in the use of OFDM technology to maintain orthogonality among subcarriers for error free communication. Timing and frequency synchronization errors are quite detrimental to this condition because these errors ultimately disturb the orthogonality which is perfectly set at transmitter. Synchronization errors need to be handled properly otherwise they create Inter-Symbol Interference (ISI) and Inter-Channel Interference (ICI) which after all resulted into the deterioration of Bit Error Rate (BER). This paper covers types of synchronization and its effects, algorithms to decrease it and analysis of the same.

Cellular networks are characterized by mobility in which subscribers move freely within the coverage area. Since the radio spectrum is a scarce resource, the available bandwidth is divided by using a combination of Time- and Frequency-Division Multiple Access (TDMA) Code Division Multiple Access (CDMA) and Frequency Division Multiple Access (FDMA). For communication process to succeed, the subscriber must be allocated some frequency band (FDMA), a time slot (TDMA) or pseudorandom binary sequence that modulates the carrier (CDMA). With the increasing number of users, these resources may become unavailable, leading to new call blocking or handover call blocking. Erlang B and Erlang C have been used in the past to model teletraffic blocking in Public Switched Telephone Network (PSTN). Unfortunately, Erlang B is only ideal when subscribers do not perform call re-attempts after their initial calls are blocked. On the other hand, Erlang C model is applicable only in networks where queuing is applied and can easily lead to higher blocking rates when the number of users is high. This is because it takes into consideration the number of instances in the queue as well as the resources under use. In this paper, teletraffic blocking probabilities that take into account additional cellular network concepts such as the number of mobile stations, call retries, channels reservation, overlays and underlays, user velocity, relative mobility, call priority, call arrival rates and signal to interference plus noise ratio (SINR) were synthesized. The simulation results showed that the developed teletraffic blocking probabilities were superior to the conventional Erlang B and Erlang C as they consider new concepts that exist in cellular networks that were not envisioned in traditional PSTN.

In the recent few years the research on Wireless Sensor Networks (WSN) and its variants have risen enormously. The researchers all across the globe are trying to develop a routing protocol that is energy efficient and provides adequate security level in data communication. One of the techniques the researchers use is Clustering of the sensor network. This technique inherently consumes less energy during data communication as the nodes have assigned a dedicated task to perform. A total of 35 clustering algorithms / protocols have been surveyed and comparison of these protocols based on the metrics like heterogeneity, clustering method, size of the cluster etc. have been presented.

In these days all businesses trying to use global applications on cloud computing infrastructure to reduce their costs and also decentralize their application. This movement also causes more security risks over the unbounded cloud environment. Therefore, accessing enterprise information for an unwanted user will be more than other environments.
Thus, the proposed Identity Management System (IDMS) tries to preserve security in communication between clients and server over cloud computing. The proposed method suggested token based Identity Management and also enhanced privacy by adding one. Dual Certificate Manager (DCM) block is a replacement for a combination of symmetric and asymmetric cryptography, which is commonly used for SSL/TLS protocol to immune data transmission, uses asymmetric cryptography in both participants.
Furthermore, for more privacy and invulnerability DCM uses Elliptic Curve Cryptography (ECC) as asymmetric cryptography algorithm.

Prediction of location has gained lot of attention in different applications areas like predicting the path or any deviation like taxi-route, bus route, human trajectory, robot navigation. Prediction of the next location or any path deviation in RFID enabled supply chain path followed in the process is quite a novel area for the related techniques. The paper defines the architecture for the outlier detection in RFID enabled Supply Chain Path based on historical datasets .Given the training datasets, different classification models are compared for the accurate prediction of the outlierness of the path followed by the tagged objects read by RFID readers during the supply chain process. Comparison of Hidden Markov Model(HMM), XGBoost(decision tree based boosting),Recurrent Neural Network(RNN) and state of art technique in RNN known as Long  Short Term Memory (LSTM) is done .To our knowledge LSTM has never been used for this application area for outlier prediction. For the longer path sequences, LSTM has outperformed over other techniques. The training datasets used here are in the form of the record of the outlier positions in particular path and at particular time and location. 

In this day and age of occupied time plans, individuals are confronting numerous issues in following the employees and specialists in colleges, schools, universities, doctor's facilities and so forth, hence it ends up vital that each assignment is expert intelligently, productively and in an auspicious way. To achieve this, easy accessibility of people of interest is a must. To alleviate this problem, we propose a solution called “Personnel Presence Locator System (PPLS)” that is an internetworked amalgam of small systems working independently. Moreover, in this article, we give an overview of the naturally multidisciplinary writing of human-detection, concentrating essentially on the extraction of five regularly required properties: in particular Location, Count, Presence, Track, and Identity. The objective of this work is to uncover the abilities and constraints of existing solutions from different disciplines, to manage the production of new frameworks like PPLS and point toward future research bearings.