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Master Thesis: Predictive QoS Control for 3GPP Mobile Networks

Posted date: May 4, 2021

Location: Stockholm, AB, SE

Company: Ericsson


Why is Ericsson a good place to work?


Ericsson enables communications service providers to capture the full value of connectivity. The company’s portfolio spans Networks, Digital Services, Managed Services, and Emerging Business and is designed to help our customers go digital, increase efficiency, find new revenue streams, and create new user experiences. Ericsson’s investments in innovation have delivered the benefits of telephony and mobile broadband to billions of people around the world ensuring our solutions – and our customers – are at the forefront of innovation.   We support networks that connect more than 2.5 billion subscribers. With over 100,000 employees and customers in 180 countries, we combine global scale with technology and service leadership.  40 percent of the world’s mobile traffic is carried over an Ericsson network.  And, our Technology for Good and Connect to Learn programs include creating technology that makes it easier to save lives, feed societies, bring technology to emerging markets and connectivity to remote areas, and grow businesses and prosperity.


At Ericsson, we give our employees the freedom to think big and navigate their career, on a global scale.  We create technology that helps others, from helping people enjoy their favourite content to helping people recover from natural disasters by enabling better communications between rescue workers. Your ideas and innovations can turn into achievements that impact society and change the world, creating new connections, new possibilities, and new capabilities.  We find that Ericsson is at its best when we bring together the diverse skills of our people. Working across business areas, across cultures, across geographical borders, across technical disciplines. More often than not, across ground-breaking solutions. Next generation technology can be staggeringly complex. But the simpler it is to use; the more people benefit from it. Join us and help build technology that makes it simple to connect with information, business, societies, and each other.

 

Position Summary:

 

Quality of Service (QoS) is a vital part of mobile networks, especially considering the multi-service nature of fifth generation of mobile networks (5G): In 5G, low-latency, high-availability and/or guaranteed throughput applications will coexist with mobile broadband.

 

Currently, in third generation partnership project (3GPP) mobile networks, QoS control mechanism relies on creation of dedicated, prioritised data traffic tunnels (e.g., bearers in 4G, flows in 5G) spanning the Radio Access Network (RAN), backhaul interface and core network. Although providing means to setup these tunnels, the mechanism does not provide application owners means for monitoring their performance throughout the lifetime of the application. As a result and in order to avoid potential Service Level Agreement (SLA) violations, mobile network operators assign specific frequency bands exclusively to mission critical applications. However this approach may result in suboptimal resource allocation as the aforementioned applications may not make use of all the bandwidth all of the time.

 

In this master thesis, the student will explore a predictive solution, which, given a request for QoS from an application and based on historical traffic patterns, detects whether the request can be fulfilled in the foreseeable future. In case of a negative answer, the solution negotiates with the application owner a lower QoS, that is still within the margins of their SLAs. The process repeats periodically for incumbent application owners, in order to guarantee the most optimal network access resource allocation.

 

It is expected that the end result would demonstrate better resource allocation than the state of art, as well as introduce an improved feedback mechanism towards application owners.

 

The thesis would involve the following steps:

- Literature review, identifying relevant concepts and algorithms for analysis and optimisation.

- Informed proposal for a suitable solution.

- Implementation of the solution in different scenarios for a number of use cases.

- Testing in lab environment for the presented use case.

- Performance evaluation and comparison over state of art.

 

 

Qualifications:

- We are looking for a motivated, diligent and proactive individual who can work with other colleagues remotely but can also take their own initiative.

- MSc studies in Computer Science, Software Engineering, Electrical and Computer Engineering or similar area.

- Excellent programming skills in Python.

- Good knowledge of concepts in machine learning (e.g. deep learning) etc.

- Experiences with machine learning libraries Tensorflow, Keras, PyTorch, sci-kit learn etc.

- Like to build end to end prototypes and concepts.

- Be fluent in English.

 

Contact person: Athanasios Karapantelakis athanasios.karapantelakis@ericsson.com

Recruiter: Richard Tjong richard.tjong@ericsson.com

 

Please upload your Cover letter, CV and grade transcripts with your application.

Apply before: 23rd May

 

Do you believe that an organization fostering an environment of cooperation and collaboration to execute with speed creates better business value? Do you value a culture of humanness, where fact based decisions are important and our people are encouraged to speak up? Do you believe that diverse, inclusive teams drive performance and innovation? At Ericsson, we do. 

We provide equal employment opportunities without regard to race, color, gender, sexual orientation, transgender status, gender identity and/or expression, marital status, pregnancy, parental status, religion, political opinion, nationality, ethnic background, social origin, social status, indigenous status, disability, age, union membership or employee representation and any other characteristic protected by local law or Ericsson’s Code of Business Ethics.
 

Primary country and city: Sweden (SE) || || Stockholm || [[mfield2]]

Req ID: 540439 


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