Integrated approach for efficient power consumption and resource allocation in MIMO-OFDMA

The growing interest towards wireless communication advancement with smart devices has provided the desired throughput of wireless communication mechanisms. But, attaining high-speed data packets amenities is the biggest issue in different multimedia applications. Recently, OFDM has come up with the useful features for wireless communication however it faces interference issues at carrier level (intercarrier interferences). To resolve these interference issues in OFDM, various existing mechanisms were utilized cyclic prefix, but it leads to redundancy in transmitted data. Also, the transmission of this redundant data can take some more power and bandwidth. All these limitations factors can be removed from a parallel cancellation mechanism. The integration of parallel cancellation and Convolution Viterbi encoding and decoding in MIMO-OFDMA will be an effective solution to have high data rate which also associations with the benefits of both the architectures of MIMO and OFDMA modulation approaches. This paper deals with this integrated mechanism for efficient resource allocation and power consumption. For performance analysis, MIMO-OFDMA system is analyzed with three different approaches likeMIMO-OFDM system without parallel cancellation (MIMO-OFDMA-WPC), MIMO-OFDMA System with parallel cancellation (MIMO-OFDMA-PC) and proposed IMO-OFDMA system with parallel cancellation and Convolution Viterbi encoding/decoding (pMIMO-OFDMA-PC &CVed) for 4x4 transmitter and receiver. Through performance analysis, it is found that the proposed system achieved better resource allocation (bandwidth) with high data rate by minimized BER rate and achieved least power consumption with least BER

Increasing Revenue by Applying Machine Learning to Congestion Management in SDN

With the advent of 5G, IoT and 4k videos, online gaming, movie streaming and other data intensive applications, the demand for data is sky rocketing. Due to this surge in data, the load on the network increases. This heightened network load causes degradation in network performance. Which can lead to the customer Service Provider (CSP)s loosing revenue if the Service Level Agreement (SLA) are not met. This report describes how machine learning techniques such as tit for tat can be applied to telecom networks. Machine learning applied to telecom networks help detect congestion and maintain SLAs while increasing yield (revenue). Several experiments are run with varying conditions on the network, such as low, medium and high loads; different levels of SLA for bandwidth and delay. Once the original conditions are tested without applying any smart blocking techniques, machine learning is applied to detect congestion in the network and block flows to maintain SLA and increase the number of flows that generate revenue

Sistemas Difusos: Una Aproximación a las redes 5G bajo el Paradigma SDN

The exploitation that has had the fuzzy systems related to advances of 5G networks (Fifth Generation Mobile Networks) and how this development has been framed by the paradigm of SDN (Software Defined Networks) architectures are reviewed in this article. The first part will review terms required for understanding the technologies and their evolution; on which different scenarios are evaluated because they have contributed to the development of the definition of 5G networks. Following, the research and development of the fuzzy systems applied to telecommunications, specifically 5G technology and SDN architectures will be described. Finally, the respective conclusions of the fuzzy systems in the 5G networks and SDN architectures will be exposed.En este artículo se revisó la utilización que ha tenido los sistemas difusos en torno a los avances delas redes 5G (Redes Móviles de Quinta Generación) y cómo este desarrollo ha sido enmarcado por elparadigma de SDN (Software Defined Networks). La primera parte revisó los términos requeridos paraentender las tecnologías planteadas y su evolución; en esta definición se evalúan diferentes escenariosque han contribuido al desarrollo de la definición de las redes 5G. Posteriormente se describió la investigación y desarrollo de los sistemas difusos aplicados a las telecomunicaciones, específicamente la tecnología 5G y las arquitecturas SDN. Finalmente, se expusieron las conclusiones respectivas de los sistemas difusos en las redes 5G y las arquitecturas SDN