Wireless sensor networks (WSNs) are broadly employed in lots of applications. WSN is comprised of spatially dispersed sovereign devices enabled with sensors to examine some physical phenomenon. The node localization, which is to be responsive of nodes’ location in the system, is a crucial component of numerous WSN functions and applications. Various localization algorithms have been proposed to precisely locate nodes in WSNs. The localization algorithms are normally categorized into range-based and range-free schemes based on range measurements. The range-based methods use exact computation measure (distance or time) among nodes in the network. So range-based methods need some additional hardware for such computation, thus expensive to be used in practice. Because of hardware constraints of sensor network devices, range-free methods are considered cost efficient alternatives. Though, these methods normally contain higher localization error in comparison with range-based methods. DV-Hop is an usual range-free method that use hop-based evaluation. In this article, we have modified DV-Hop method and applied a meta-heuristic (PSO) technique to overcome the positioning error. The algorithm has been implemented in MATLAB R2015a for the validation of results. The performance of implemented algorithm has been analyzed in terms of localization error, error variance, accuracy, and coverage. The results of modified algorithm confirm that our algorithm decreases the localization error and improved the localization accuracy as compared to DV-Hop and improved DV-Hop (IDV-Hop) algorithms.

Many cutting-edge technologies, such as MIMO, cognitive radio, multi-carrier modulation, and network coding, have been proposed for wireless communication to satisfy needs for a higher data rate in the upcoming time, leading to improved quality of service (QoS) regardless of the weather. Orthogonal and non-orthogonal multiple access techniques are two categories into which multiple access technologies can be subdivided. Large networking with effective implementation of wireless devices is supported by non-orthogonal multiple access techniques. Massive NOMA has been implemented to advance access efficiency by permitting several users to share a similar spectrum. Because of the robust co-channel interference between mobile users presented by NOMA, it offers important tasks for system model and resources management. In this study, two additional sets of demanding codes are explored. Multi-user shared access methods and expanded multi-user shared access (EMUSA) methods are both employed. In the MUSA technique, an algorithm is used for the allocation of resources to achieve minimum intercorrelation to the maximum extent in 5G networks. A novel idea proposed in this paper is to create complex codes starting from PN codes (i.e., ePN), thereby achieving promising results in the overall system performance. The first part of this paper describes the fundamental principles of MUSA, and in the next part the main idea of the proposed technique will be studied in detail. Using Monte-Carlo MATLAB simulation, the performance of the suggested approach is assessed in terms of BER vs. SNR. The efficiency of the proposed approach is evaluated in various settings, and the outcomes are contrasted with those of the traditional CDMA technique, using parameters, such as the number of active users and antennas at the receiver.

Software reliability is the probability of failure-free operations of software in a specific environment in a given time period. Various software reliability models have been designed by the researchers, but the JM model is the first influential model. The JM model was developed with the basic assumption that the faults are independent in this model and the debugging process is perfect. But practically, all debugging processes may not be perfect, especially when the faults are dependent; in this case, the fault that is actually to have been removed may also remove more than one fault and cause it to add some new faults. To handle this behavior of faults mutual dependency, we need a new model which may be less reliable or the result accuracy of the model may be lower than that of the existing ones, but it can handle more practical situations in the fault removal process. In this paper, we proposed a new software reliability model with the same assumption that at whatever time a failure is detected, it is not completely eradicated and there is a possibility of raising some new faults because of wrong analysis or inaccurate modifications in the software or the removal of the existing fault may also remove some other faults. The proposed model is more practical than the existing ones.

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