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Challenges and Mitigation
36
Telco’s are yet to develop clear strategies on how to use MEC ecosystem players to establish a stronger proposition in the edge market, move up the value chain and play a role beyond hosting infrastructure and delivering connectivity. The complex...
Artificial Neural Network, Neural Architecture Search
68
Normal machine learning or deep learning applications with human intervention in feature selection provides a maximum accuracy of 70% or 80% for computer vision or big datasets. This is mainly due to poor feature selection, because of which the size...
Artificial Neural Network, Neural Architecture Search
92
Artificial neural network (ANN) is hot topic of research now, as there is no guarantee that a specific ANN model will give good accuracy for a problem. So, we need an appropriate architecture for neural system instead of repeated trial and error...
MEC
169
Technologies continue to evolve to manage the diversified market needs. With the advent of 5G, the Telco industry digitalization has already entered into a new transformation. Now Telcos focus is on customer experience rather than merely providing...
5G Imperatives in Engineering for CSPs and System Integrators
196
5G is about delivering business outcomes for CSPs. With the 5G Network Rollout, though the new kinds of spectrum bands grab all the headlines, the truth is that when it comes to 5G, radio access is just the tip of the iceberg. What lies beneath is...
Building a Future-Proof  Fibre Network with HCL - Part 2
89
The Communication Service provider landscape is preparing itself for digital transformation. As more and more devices, people, and things connect, the demands for fast, reliable connections continue to increase. To unleash value creation, new...
Leveraging AI/ML-driven Autonomous Networks for Next-Generation Enterprises
162
The promise of enhanced connectivity is the backbone of business innovation as it empowers business leaders to broaden their ambitions towards new products and solutions. This is the only way to ensure a future-ready posture that remains competitive...
Next-Generation Enterprises
258
The state of IT infrastructure has drastically changed with networks becoming a critical enabler of modern, digital enterprises. However, the rapid transformation from data center-based design to distributed architecture has not been easy, with...
OEMS as GSI
184

Mar 10, 2021

HCL unlocking 5G value with OEMs as GSI

Anchal Sardana Associate General Manager

Communication Service Providers(CSPs) are on their digital transformation journey where they are evolving themselves from dumb pipes to smart pipes connecting all the enterprises in digital way by bringing innovative use cases. The digital services...
Node Network
2,824
An end to end IoT system includes various networks in an IoT system, type of devices and the applications running in those networks. Constrained node network is deployed as an edge network in an IoT system. There are various classes of constrained...
open digital architecture
2,335

Aug 08, 2019

5G and its impact on OSS/BSS

Arun Kumar Sharma Deputy General Manager

With 5G under trials, the question is whether OSS/BSS is ready to support 5G solutions. Do 3 core technologies of 5G namely 5G NR, Virtualization and Network slicing require any changes in traditional OSS/BSS approach? This blog talks about the...
YET ANOTHER O-RAN BLOG
907
As part of the HCL’s 5G strategy, critical investments are being driven to enhance HCL’s play in the 5G Ecosystem. As the Radio Access Network (RAN) gets ‘opened’ or disaggregated, there is plenty of scope for new players to provide radio focused or...
Challenges and Mitigation
36
Telco’s are yet to develop clear strategies on how to use MEC ecosystem players to establish a stronger proposition in the edge market, move up the value chain and play a role beyond hosting infrastructure and delivering connectivity. The complex...
Multihoming
1,869

Apr 15, 2016

What is Multihoming?

Jayaramakrishnan Sundararaj Technical Manager

5G
202

Feb 17, 2021

Covid, 5G and AR/VR Adoption

Srinivas Panapakam Regional Sales Director

The AR/VR industry is projected to grow at the rate of 35% CAGR over next 4 years with an incremental growth of $125+ Billion according to Technavio(www.technavio.com) . This coincides well with the increasing 5G deployments in different parts of...
Containers and Virtual Machines – Essential to 5G
208
To reap benefit of 5G, networks need to be more flexible and agile and containers are the key as they will provide improved efficiency as well as reduced cost. However, every operator will evolve at its own pace and will have its own cloud...
Case for Blockchain in 5G
175

Feb 25, 2021

Case for Blockchain in 5G

Satish Pandita Area Sales Director

5G is one of the most instrumental factors to usher in the fourth industrial revolution – Industry 4.0. The three main use cases of 5G technology - Enhanced Mobile Broadband (eMBB), Massive Machine Type Communication (mMTC) and Ultra-reliable Low...
Next-Generation Enterprises
258
The state of IT infrastructure has drastically changed with networks becoming a critical enabler of modern, digital enterprises. However, the rapid transformation from data center-based design to distributed architecture has not been easy, with...

Carrier Wi-Fi: A Cost Effective Method for Network & Bandwidth Issues
Banish Bansal - Senior Technical Lead- ERS | February 18, 2015
479 Views

Realizing Carrier Wi-Fi

Mobile data consumption is growing exponentially with the rapid growth of smartphones/tablets and bandwidth-hungry applications (Video/Music Streaming, Rich Media Communication and personal Cloud services, etc.) that they run. Analysts predict that Wireless Data Traffic will increase by 300% in 2017, compared with what it was in 2012.


Successful MEC(Multiple Access Edge Computing) Implementation - Challenges and Mitigation
Anchal Sardana - Associate General Manager | June 10, 2021
36 Views

Telco’s are yet to develop clear strategies on how to use MEC ecosystem players to establish a stronger proposition in the edge market, move up the value chain and play a role beyond hosting infrastructure and delivering connectivity. The complex mix of Bare metal, MEC platforms, Hyperscalers, Enterprise with vertical use-cases, constitute the MEC development and deployment, making Telcos network challenging. Lack of vertical industry - automobile, manufacturing, retail, health, expertise which are required to customize and modify the use cases, artificial intelligence and machine learning based zero touch automation, service orchestration solution that is able to deal with both physical and virtual infrastructures in an integrated manner along with future proof OSS BSS infrastructure are some of the key challenges observed in implementation of MEC by Telcos. However, where there are challenges for one player it opens gamut of opportunities for other players. The MEC challenges has opened doors for system integrators to provide a mitigation approach and come up with the right set of propositions and business model for Telcos and other ecosystem players. HCL with its edge compute solution brings an end to end system integration capabilities from concept to run along with its state of art products for acceleration, an enhanced partner ecosystem from 5G MEC Lab, 12+ vertical industry expertise and ready to use in 11+ use cases. With its 5G MEC offerings HCL can strongly drive cross ecosystem collaboration at edge helping Telcos to evolve from Digital Service Providers to Experience Service Providers.

Artificial Neural Network, Neural Architecture Search (NAS) and its applications - Part 2
Jayaramakrishnan Sundararaj - Technical Manager | May 21, 2021
68 Views

Normal machine learning or deep learning applications with human intervention in feature selection provides a maximum accuracy of 70% or 80% for computer vision or big datasets. This is mainly due to poor feature selection, because of which the size of the neural network increases. It is important to decide the features to be used, the number of neural layers, as well as the neurons for each layer. NAS is part of an automated machine learning (AutoML) algorithm to find the best combination of data preparations, hyperparameters, training and evaluation of a model. Click here to continue e best combination of data preparations, hyperparameters, training and evaluation of a model.