Friday 21 October 2022

5 Best Wireless communication Research ideas !!

In recent days the research topics on Wireless communication is keep on increasing. Evaluation of 5G technology created way for numerous research in wireless communication.  5 emerging topics advicable for reserach are discussed here

1. Self-Organized networks
Self-organizing networks are radio access networks (RANs) that automatically plan, configure, manage, optimize, and heal themselves. Software Defined Networks (SDN) are designed to curb down the challenge of traditional network which are unable to forwarding from single device on every packet. SDN has made the Networks more programmable. Software defined networking changes our technology by ensuring advancement in hardware and software equipment used in the network configuration. SDN is a three layered architecture.



2. Self Healing Software Defined Network 

OpenFlow Protocol is the most common protocol used for providing the interface called as Southbound APIs between control layer and physical layer. On the other hand interface provided in between application layer and control layer is called as Northbound APIs. SDN can create and control a virtual network – or control a traditional hardware – via software. While network virtualization allows organizations to segment different virtual networks within a single physical network, or to connect devices on different physical networks to create a single virtual network, software-defined networking enables a new way of controlling the routing of data packets through a centralized server. Self-Organizing Networks penalties are assigned for a given network, the process is fully automatic and well defined.

3. Quality of experince enhancement

 Quality of Experience (QoE) metric is used to evaluate the end-user experience.Anomaly detection in selforganizing mobile communication networks use network-centric approaches to identify dysfunctional serving nodes.Self-organizing mobile networks can be divided into three primary categories: self-configuration, self-optimization, and self-healing. These are commonly denoted as self-x functions. The self-healing function is activated whenever a fault or failure occurs.It use a parametric model to predict the QoE of users in the network and to use their QoE scores to detect serving eNodeBs that are dysfunctional, thus demonstrating a user-centric approach for the use case of anomaly detection in self-healing and self-organizing networks. For instance, support vector machines have previously demonstrated state-of-the-art potential in many binary classification applications and can be further exploited with different representations, such as one-class learning and data augmentation. 

4. Anomaly Detection in 5G networks

Anomaly detection plays an important part in data mining. An anomaly detection method could be classified as distribution-based (density-based), proximity-based (distance-based) or cluster-based. Another way to classify all those algorithms is based on what kind of problem to be solved and what data those algorithms are applied into, namely unsupervised, supervised and semi-supervised. Fault detection often requires certain KPI or performance measurement data for estimating the time and location of a network failure. Cell outage is the case when one typical cell ceases to function as expected and go out of service. In a cell outage scenario, operators need to act quickly to correct the problem and minimize its disruption to the overall network.

5. Network Mining and analysis

CRISP-DM is the abbreviation of cross-industry process for data mining, which is a standard methodology for planning and implementation of a data mining or machine learning project. It’s robust, flexible, cover all of the aspects, necessary actions required in a typical data mining project. It is also widely used in practice, even with client engagement. The methodology consists of several steps laid out in a sequential manner. In practice, the steps can be carried out in different order, and even can be iterated multiple times. Each step has a strong connection with other steps, therefore it’s often necessary to jump back and forth among tasks and repeat certain actions. 


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