RAN Cognitive Controller

10/20/2020
by   Anubhab Banerjee, et al.
0

Cognitive Autonomous Networks (CAN) deploys learning based Cognitive Functions (CF) instead of conventional rule-based SON Functions (SF) as Network Automation Functions (NAF) to increase the system autonomy. These CFs work in parallel sharing the same resources which give rise to conflicts among them which cannot be resolved using conventional rule based approach. Our main target is to design a Controller which can resolve any type of conflicts among the CFs in a dynamic way.

READ FULL TEXT

page 1

page 2

research
11/26/2018

A Rule-based Kurdish Text Transliteration System

In this article, we present a rule-based approach for transliterating tw...
research
01/20/2020

On the Necessity and Design of Coordination Mechanism for Cognitive Autonomous Networks

Cognitive Autonomous Networks (CAN) are promoted to advance Self Organiz...
research
03/03/2016

A knowledge representation meta-model for rule-based modelling of signalling networks

The study of cellular signalling pathways and their deregulation in dise...
research
04/17/2023

Provable local learning rule by expert aggregation for a Hawkes network

We propose a simple network of Hawkes processes as a cognitive model cap...
research
11/11/2022

Metaphors We Learn By

Gradient based learning using error back-propagation (“backprop”) is a w...
research
03/27/2013

Managing Uncertainty in Rule Based Cognitive Models

An experiment replicated and extended recent findings on psychologically...
research
06/22/2023

MFCCGAN: A Novel MFCC-Based Speech Synthesizer Using Adversarial Learning

In this paper, we introduce MFCCGAN as a novel speech synthesizer based ...

Please sign up or login with your details

Forgot password? Click here to reset