Here's how you can future-proof your Mobile Communications career with in-demand skills.

Widerspread 5G in city- or industrial-style Landscapes seems to be in the best interest for Telco companies, however this might have a couple of drawbacks to consider. In City, big City environments, there is always the risk of overbooking, simply because of the sheer number of Radios Involved. Even the smartest traffic management will fail if overwhelmed by simple demand. That point is known to the operators which, during the european football championship, added additional network capacities to cooe with the demand. In industrial environment, the 5G network is likely to face different hazards due to Lots of metal in the production buildings. These problems can be, of course, handled by adding additional cell infrastructures.

Yes I agree with 5G benefits like high data speed and different use cases like urlcc,FWA and iot . However operators are not getting returns after a huge investment of 5G which slows down across the globe. End customer service is the same while browsing the data between 4G and 5G networks.

Will be helpfull to include EFIS system to provide spectrum management for sensors. Mobile network is harmonised enough. CEPT has done his work.

AI is hot in telecoms but if you want to stay ahead, focus on AI Agent frameworks. Here some ideas: 1. OpenAI Gym: It's a toolkit for developing and comparing RL algos. In telecoms, you could use it to train AI agents for dynamic spectrum management, etc. 2. TensorFlow Agents: It's a library for RL in TensorFlow, providing tools for building, training, and evaluating RL agents. It could be used for automated network traffic management, allowing the AI to learn and adapt to fluctuating traffic patterns, etc. 3. Bonsai: Not well known but an an industrial-grade platform for building AI models using machine teaching and RL. Useful in predictive maintenance of telecom infrastructure.

At this point in time, given that many weaknesses (Statistiken parrots, for example) and flaws (hallucinations), AI is a hot Marketing topic but does not seem much practical and reliable use. I heavily doubt that AI augmentation of already existing and well-established tools and Procedures will gain any tangible value beides, of course, for sales people justifying the need for costly updates

It is not easy to use AI for operations in the network because the problems in live networks which have a significant impact on customers require some actions to resolve the problem. Hence it is required to train AI more than 2 to 3 years for getting desired results in mobile networks

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