SIMULATION METHODOLOGY FOR COMMUNICATION NETWORKS

                  SIMULATION METHODOLOGY FOR COMMUNICATION NETWORKS

SIMULATION METHODOLOGY FOR COMMUNICATION NETWORKS:
           Simulation methodology of communication network is used to create, characterize and validate the communication solutions, computer networks and distributed or parallel systems. It enables to predict the network behavior and the network performance. It helps one to create, run and analyze any desired communication scenario.

There are three types of commonly used simulations:
             •LIVE: Simulation involving real people operating real systems.
             •VIRTUAL: Simulation involving real people operating simulated systems.
             •CONSTRUCTIVE: Simulation involving simulated people operating simulation systems. Real people can stimulate but are not involved in determining the outcomes.

OBJECTIVES OF SIMULATION IN COMMUNICATION NETWORKS:
  The following are some of the objectives of using simulation to design and analyze communication networks:
             •To determine the system wide impact of making local changes to the network.
             •To improve system performance.
             •To reduce expenditures.
             •To reduce system development time.

                          
                                          Fig 1. Evaluation techniques in simulation

SIMULATION SOFTWARE FOR NETWORKS:
              The major task in building a simulation model of a communication network is to convert a system description into a computer program. An analyst may use either general - purpose programming language (e.g. C or C++) or simulation software for this purpose. There are three types of software for simulating communication networks:
           •General - purpose simulation language (e.g. Arena, GPSS/H).
           •Communications - oriented simulation language (e.g. OPNET modeler).
           •Communications - oriented simulator (e.g. COMNET III).

                               
                           
                               Fig 2. An example of simulation in a Network Simulator tool

ADVANTAGES AND DISADVANTAGES OF SIMULATION METHODOLOGY:

    The advantages of simulation are:
          •It helps to determine the behavior and efficiency of a system before it is constructed.
          •The results are accurate compared to the analytical model.
          •It is easy to perform “What – If “analysis.

    The disadvantages of simulation are: 
          •Simulation methodology is not precise.
          •Expensive to build a simulation model and conduct simulation.
          •Sometimes the simulation results are difficult to interpret.

FUTURE WORK:
          In future, more complete simulation packages, providing color graphics input – output, symbolic debugging, with a variety of data display capabilities ranging from tables to charts to graphs, will be available. Efforts are also made towards the development of firmware simulation systems using hybrid hardware/software.

AI IN WIRELESS COMMUNICATION

AI IN WIRELESS COMMUNICATION

First  let’s  discuss  about  what’s  Artificial Intelligence and what’s Wireless Communication?

WIRELESS COMMUNICATION:

           Wireless communication is the communication where the data is transferred and delivered wirelessly. This is a broad term that incorporates all procedures and forms of connecting and communicating between two or more devices using wireless signal through wireless communication technologies and devices.

ARTIFICIAL INTELLIGENCE:

           Artificial intelligence is the science which refers to the reflection of human intelligence in machine and are programmed to think like humans. AI makes it possible for  machine to learn from experience and adjust to new inputs and perform human like tasks. AI machine decides the maximum probability of correct decision according to the environment.

What happens when AI technology and wireless communication gets converged?

             The traffic dense will increase up to 1000 times in 5G because of growing of user data speed and growing of end user terminals. A promising method is to introduce artificial intelligence technology into network control and management instead of manual optimization process.

                                      

AI which includes machine learning, deep learning are well known technique in computer science discipline but now they started to emerge in wireless communication. Using AI, the networks are managed efficiently and performance is enhanced.

Some tools are used to apply AI in wireless communication field:
         1) FUZZY LOGIC
         2) REINFORCEMENT LEARNING
         3) NEURAL NETWORKS
         4) DEEP LEARNING

APPLICATIONS OF AI IN WIRELESS COMMUNICATION (5G):

i) AI for 5G resource management, including spectrum resources, energy sources, cloud resources, computing resources and communication infrastructure.
ii) Help to predict problems like network collision, network overhead, multi - media traffic load.
iii) Coordinated multiple points transmission\reception, large scale antenna array and multiple hop relay are some applications in 5G.

FUTURE OF AI IN WIRELESS COMMUNIATION:

         AI is the powerful tool with potential applications areas like wireless signal processing, channel modeling and resource management. In future, AI will intelligently and fluently interact with human experts, providing them with clever explanations and answers.