The technologies described herein are generally directed to using portable situational awareness equipment with communication resources deployed to facilitate communications at a remote incident area, in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include identifying a remote incident area associated with an incident. The method can further include, based on the incident, estimating a deployment location for portable network equipment within the remote incident area, resulting in an estimated deployment location. Further, the method can include, based on the estimated deployment location and estimated signal propagation at locations within the remote incident area, selecting a placement location for communication equipment to facilitate communication with the portable network equipment.

According to one embodiment, a method, computer system, and computer program product for wireless network communication. The embodiment may include identifying a workflow among multiple industrial machines within an activity area. Performance of the workflow requires wireless communication among the multiple industrial machines. The embodiment may include identifying communication requirements and communication capabilities of the multiple industrial machines. In response to determining a wireless network is not available within the activity area, the embodiment may include deploying one or more relay computing devices to deployment locations within the activity area based on the workflow, the communication requirements, and the communication capabilities. The embodiment may include instructing the one or more relay computing devices to create a wireless network which enables wireless communication among the multiple industrial machines.

According to one embodiment, a method, computer system, and computer program product for wireless network communication. The embodiment may include identifying a workflow among multiple industrial machines within an activity area. Performance of the workflow requires wireless communication among the multiple industrial machines. The embodiment may include identifying communication requirements and communication capabilities of the multiple industrial machines. In response to determining a wireless network is not available within the activity area, the embodiment may include deploying one or more relay computing devices to deployment locations within the activity area based on the workflow, the communication requirements, and the communication capabilities. The embodiment may include instructing the one or more relay computing devices to create a wireless network which enables wireless communication among the multiple industrial machines.

Multiple mobile cellular network (MCN) communication systems can be networked together to form a network of MCN communication systems (NOM). Each MCN communication system within the NOM can operate as an independent cellular network to provide communications between user equipment within a covered area. The MCN can be managed by a network management control center (NMCC). The NMCC can be configured generate coverage maps of the NOM and NMC system coverage areas.

Multiple mobile cellular network (MCN) communication systems can be networked together to form a network of MCN communication systems (NOM). Each MCN communication system within the NOM can operate as an independent cellular network to provide communications between user equipment within a covered area. The MCN can be managed by a network management control center (NMCC). The NMCC can be configured generate coverage maps of the NOM and NMC system coverage areas.

The present invention relates to an apparatus, a method and a computer program for determining a duplex resource scheme for a localized communication in a mobile communication system, and to a method for a vehicle, which uses the determined resource scheme for the localized communication in the mobile communication system. The method for determining a duplex resource scheme for a localized communication in a mobile communication system comprises obtaining environmental perception data. The environmental perception data relates to a plurality of road users. The method further comprises predicting a plurality of radio resources required for a communication of the plurality of road users based on the obtained environmental perception data. The method further comprises determining the duplex resource scheme based on the predicted plurality of radio resources required for the communication of the plurality of road users.

A communication technique of integrating a 5th generation (5G) or pre-5G communication system for supporting a higher data transmission rate after a 4th generation (4G) communication system such as long term evolution (LTE) with an IoT technology, and a system thereof. The disclosure may be applied to an intelligent service (for example, a smart home, a smart building, a smart city, a smart car, or a connected car, health care, digital education, retails, security and a safety related service, and the like) based on the 5G communication technology and the IoT related technology. According to various embodiments, a device and a method for optimizing mobile initiated communication only (MICO) mode related parameter values for reducing power consumption of a terminal in a mobile communication system.

A communication technique of integrating a 5th generation (5G) or pre-5G communication system for supporting a higher data transmission rate after a 4th generation (4G) communication system such as long term evolution (LTE) with an IoT technology, and a system thereof. The disclosure may be applied to an intelligent service (for example, a smart home, a smart building, a smart city, a smart car, or a connected car, health care, digital education, retails, security and a safety related service, and the like) based on the 5G communication technology and the IoT related technology. According to various embodiments, a device and a method for optimizing mobile initiated communication only (MICO) mode related parameter values for reducing power consumption of a terminal in a mobile communication system.

Systems and methods that use historical data comprising capacity gain solutions and their associated gains at various locations to train a machine learning model. The trained machine learning model, upon receiving a new location (e.g., latitude and longitude coordinates), recommends the top n (e.g., the top 3) solutions that should be deployed at the new location to improve telecommunications network performance. The machine learning model uses clustering techniques to perform the recommendations.

Systems and methods that use historical data comprising capacity gain solutions and their associated gains at various locations to train a machine learning model. The trained machine learning model, upon receiving a new location (e.g., latitude and longitude coordinates), recommends the top n (e.g., the top 3) solutions that should be deployed at the new location to improve telecommunications network performance. The machine learning model uses clustering techniques to perform the recommendations.