Improvement of data throughput via backhaul sharing is accomplished by accessing a cell site servicing data transmission at a first data rate and a connected backhaul network having a backhaul data rate. A determination of whether the first data rate exceeds the backhaul data rate is made and an excess data rate is determined. When the first data rate exceeds the backhaul data rate a neighboring cell site having a second backhaul networks is accessed. A determination is made of how much additional capacity the second backhaul network can handle. When the neighboring cell site can handle the excess data rate backhaul sharing using beamforming is initiated.

The disclosed technology is directed towards load balancing in an adaptive and automated way for wireless mobility networks to improve the overall harmonic-average UE throughput within each controlled group of cells (e.g., different frequency carriers serving a sector of a base station). A load balancer (e.g., analytics component) obtains various device traffic data including throughput data for cells of a group. Pairs of cells in a group (sharing a site and face) can be selected based on satisfying various criteria, with estimated throughput gain achieved by changing the handoff rates between the cell pairs. The technology iteratively repeats the overall process, driving a system to an optimal equilibrium.

The present disclosure relates to a communication method and system for converging a 5.sup.th-Generation (5G) communication system for supporting higher data rates beyond a 4.sup.th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A method for controlling a terminal in a base station of a mobile communication system, according to an embodiment of the present application, comprises the steps of: selecting at least one candidate terminal for offloading; obtaining information on a neighbor cell of at least one of the candidate terminals; obtaining throughput improvement information according to offloading on the basis of information on the candidate terminal and load information of the neighbor cell of the candidate terminal; obtaining information on a target cell corresponding to the candidate terminal on the basis of the throughput improvement information; selecting a target terminal to be offloaded from the candidate terminals on the basis of the throughput improvement information corresponding to the target cell; and transmitting, to the target terminal, a message instructing offloading to the target cell corresponding to the target terminal.

Based on a load prediction analysis performed by a machine learning enabled processor and a load balancer, the load of multiple distributed unit (DU) resources in a baseband unit (BBU) pool hub can be optimized. The BBU pool hub can comprise multiple DU functionality and redundant centralized unit (CU) functionality connected via a high-speed/low latency redundant switch to enable pooling of resources. DU resource pooling can facilitate efficiencies in the network by allocating resources based on active and/or inactive status, load, of radio units RUs as well Radio Bearers activity.

Embodiments of this application provide a load balancing method and a device. The method includes: determining, by a network device if periodicities of allocatable sounding reference signal SRS resources in a first cell are greater than periodicities of allocatable SRS resources in a second cell, a to-be-handed-over terminal based on transmission modes of terminals having accessed the first cell, where the first cell and the second cell are cells in a multi-carrier co-coverage network, and the network device covers the first cell and the second cell; and handing over, by the network device, the to-be-handed-over terminal to the second cell, where a periodicity of an SRS resource, allocated to the to-be-handed-over terminal, in the second cell is less than a periodicity of an SRS resource, allocated to the to-be-handed-over terminal, in the first cell.

The disclosed technology is directed towards load balancing in an adaptive and automated way for wireless mobility networks to improve the overall harmonic-average UE throughput within each controlled group of cells (e.g., different frequency carriers serving a sector of a base station). A load balancer (e.g., analytics component) obtains various device traffic data including throughput data for cells of a group. Pairs of cells in a group (sharing a site and face) can be selected based on satisfying various criteria, with estimated throughput gain achieved by changing the handoff rates between the cell pairs. The technology iteratively repeats the overall process, driving a system to an optimal equilibrium.

A method, a computer-readable medium, and an apparatus are provided. The apparatus may include a first IAB-donor-CU. The apparatus may receive a first request from a second IAB-donor-CU to route a first traffic between a first IAB node associated with the second IAB-donor-CU and a second IAB node associated with the first IAB-donor-CU. The apparatus may receive from the second IAB-donor-CU first QoS information for the first traffic. The apparatus may transmit a request to a third IAB-donor-CU to route a second traffic between a third IAB node associated with the first IAB-donor-CU and a fourth IAB node associated with the third IAB-donor-CU, where at least a part of content of the second traffic is based on the first traffic.

A communication control apparatus allocates capacity of a line that connects a plurality of baseband units managed by a plurality of operators to a radio unit shared by the plurality of operators to the plurality of operators. The communication control apparatus includes a memory and a processor coupled to the memory. The processor executes a process including: calculating a fairness coefficient indicating allocation fairness of the line with respect to each of the plurality of operators; acquiring needed capacity of the line needed by each of the plurality of operators and a gain achievable when the needed capacity is allocated to each of the plurality of operators; and deciding allocation capacity of the line for each operator based on the fairness coefficient, the needed capacity, and the gain.

Techniques for dual connectivity control based on downlink data are discussed herein. A Fourth Generation (4G) base station can receive downlink data to be transmitted to a user equipment (UE). The 4G base station can also receive data from the UE indicating that the UE is associated with a low power state. The 4G base station can further determine a capability of the base station (e.g., an available bandwidth) to transmit the downlink data to the UE. If an amount of downlink data is below a threshold, operations can refrain from establishing a dual connectivity connection. If an amount of downlink data is above a threshold, operations can include establishing a dual connectivity connection. In some cases, thresholds and/or the decision to initiate dual connectivity can be determined based on the state data associated with the UE, such as a battery status, a level of user interaction, and the like.

Techniques for dual connectivity control based on downlink data are discussed herein. A Fourth Generation (4G) base station can receive downlink data to be transmitted to a user equipment (UE). The 4G base station can also receive data from the UE indicating that the UE is associated with a low power state. The 4G base station can further determine a capability of the base station (e.g., an available bandwidth) to transmit the downlink data to the UE. If an amount of downlink data is below a threshold, operations can refrain from establishing a dual connectivity connection. If an amount of downlink data is above a threshold, operations can include establishing a dual connectivity connection. In some cases, thresholds and/or the decision to initiate dual connectivity can be determined based on the state data associated with the UE, such as a battery status, a level of user interaction, and the like.