A system and method for dynamically switching transmission of selected data from cellular core network to unidirectional point-to-multipoint downlink network or from unidirectional point-to-multipoint downlink network to cellular core network based on traffic flow analysis is provided. The system includes a cellular packet core 206, a broadcast offload packet core (BO-PC) 302, and a load manager 202. The cellular packet core 206 controls a cellular radio access network (RAN) 412 for providing bidirectional connectivity to a converged user equipment (UE) (204) to transmit or receive selected data through the cellular packet core 206 and the RAN 412. The BO-PC 302 controls a broadcast radio access network (RAN). The broadcast radio access network (RAN) includes at least one Broadcast Radio Head (BRH) 322 for providing unidirectional downlink path to the converged user equipment (UE) 204 to receive selected data through the at least one Broadcast Radio Heads (BRH) 322.

Embodiments of this application provide a blind detection method. A terminal side device receives first indication information from a network side device, where the first indication information is used to determine at least one of N time units, a first time unit in the N time units corresponds to a type of terminal operation, the terminal operation is not performing a first operation, a second operation, and a third operation, the N time units belong to a same transmission time unit, and any one of the N time units includes at least one symbol, where N is an integer greater than 0. The terminal side device determines the N time units based on the first indication information, and performs the corresponding terminal operation in the first time unit in the N time units.

The disclosed technology is directed towards load balancing baseband units in a communications network. A baseband physical layer 1 unit’s functions are disaggregated into Layer 1 (L1) distributed units and radio units, instead of deploying full-fledged baseband units at a service’ provider’s service areas (cells). A load balancer scales up the number of active distributed units based on increased actual demand, and scales down the active distributed units based on decreased demand. The L1 distributed units and radio units can be software-defined network functions, and need not be collocated, whereby the distributed units can be in the cloud or hub remotely located relative to the radio units deployed at the service areas. Examples of load balancing can be load balancing of transmitted data per carrier, per subcarrier, per user equipment, per transmission time interval (TTI / slot), per bearer, or per channel.

A 5G cellular network system is disclosed that includes a plurality of servers, each of the plurality of servers comprising a processor, memory, an operating system; a distributed unit (DU) and a worker. The DU is installed in the memory and comprising computer instructions, that when executed by the processor, processes and controls communications with at least one tower to handle communications between cellular devices. The worker is configured to communicate over a wide area network to a central unit (CU) in a core network for processing the communications to/from the DU and the at least one tower.

Various embodiments herein provide techniques for integrated access and backhaul (IAB) nodes. For example, embodiments include techniques associated with: rate-proportional routing for network coding; utilizing multiple routes in IAB networks; user equipment (UE) and parent selection for efficient topology in IAB networks; establishing efficient IAB topologies; and/or adaptive coded-forwarding for network coding. Other embodiments may be described and claimed.

Apparatuses, systems, and techniques to perform one or more APIs. In at least one embodiment, a processor is to perform an API to indicate a number of 5G-NR cells that are able to be performed concurrently by one or more processors; a processor is to perform an API to indicate whether one or more processors are able to perform a first number of 5G-NR cells concurrently; a processor comprising one or more circuits is to perform an API to indicate whether one or more resources of one or more processors are allocated to perform 5G-NR cells; and/or a processor comprises one or more circuits to perform an API to indicate one or more techniques to be used by one or more processors in performing one or more 5G-NR cells.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a wireless node may establish a first connection between a child wireless node and a first base station and a second connection between the child wireless node and a second base station, wherein the first connection is an F1-U direct path and the second connection is an F1-U alternative path. The wireless node may forward at least a portion of user-plane traffic between the child wireless node and the first base station via the second connection and the second base station. Numerous other aspects are described.

Embodiments described herein provide for the leveraging of edge-based resources (e.g., processing, memory, storage, and/or other resources of one or more Multi-Access/Mobile Edge Computing devices (“MECs”), such as MECs associated with a radio access network (“RAN”) of a wireless network) to process data from and/or provide instructions to microcontroller devices, System on Chip (“SoC”) devices, configurable logic boards, Internet of Things (“IoT”) devices, and/or other types of devices or systems. For example, embodiments described herein may provide for the creation and configuration of logical devices or systems based on one or more microcontrollers, SoC devices, etc., edge-based processing of sensor data and/or other types of data received or generated by the microcontrollers, SoC devices, etc., and the generation of instructions to control physical devices communicatively coupled to the microcontrollers, SoC devices, etc.

Hybrid use of dual policies is provided to improve a communication system. In a multiple access scenario, when an inactive user equipment (UE) transitions to an active state, it may be become a burden to a radio cell on which it was previously camping. In some embodiments, hybrid load balancing is provided using a hierarchical machine learning paradigm based on reinforcement learning in which an LSTM generates a goal for one policy influencing cell reselection so that another policy influencing handover over active UEs can be assisted. The communication system as influenced by the policies is modeled as a Markov decision process (MDP). The policies controlling the active UEs and inactive UEs are coupled, and measureable system characteristics are improved. In some embodiments, policy actions depend at least in part on energy saving.

A method of providing user level mobility load balancing is provided, the method comprising: classifying a group of User Equipments (UEs) in a cell into multidimensional planes based on metrics associated with the UEs; defining thresholds for each dimension; using the defined thresholds determining to discard or select certain planes of a dimension and the UEs contained in the planes; and identifying a best UE of the UEs contained in selected planes for offload.