Abstract: The present disclosure discloses a fabricated air conditioner wall and an operation method thereof, and the fabricated air conditioner wall included a precast wall and a heat pump system embedded in the precast wall. The components of the fabricated air conditioner wall are mass-produced and assembled in factories. The fabricated air conditioner wall mainly includes an indoor heat exchanger, a throttle valve, a condensate water tank, a four-way valve, a wall-buried pipe, a compressor, and an outdoor heat exchanger. In a cooling mode, condensate water is collected in the condensate water tank to cool the refrigerant. In winter, when the precast wall is illuminated by sunlight, a temperature of an outer wall is often higher than a temperature of outdoor air, and this solar energy can be reasonably utilized by the wall-buried pipe, thereby improving the heating effect of the air conditioner itself.

Abstract: Concepts and technologies disclosed herein are directed to the optimization of over-the-air (“OTA”) file distribution for connected cars based upon a heuristic scheduling algorithm. A schedule provided by the heuristic scheduling algorithm is designed to distribute OTA data flow to connected cars over the network (geographically) and over a scheduling time horizon (timely), and is capable of reducing the negative impact of OTA file updates on overall wireless network performance. This schedule is created based upon historical statistics associated with connected car driving patterns and simulations of connected car-specific OTA traffic over the network. By leveraging connected cars that connect to different cells at different times based upon driving patterns, the heuristic scheduling algorithm is effective in reducing OTA impact on the network.

Abstract: A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.

Abstract: A system includes a first network edge data collector, a first network edge key performance indicator (KPI) engine configured to operate on first data collected by the first network edge data collector, a KPI metrics manager in communication with the first network edge KPI engine, the KPI metrics manager controlling a KPI metric catalog and wherein the first network edge KPI engine determines first edge KPI metric using a metric algorithm from the KPI metric catalog on the first data.

Abstract: The described technology is generally directed towards user equipment (UE) geolocation. A machine learning model can be trained to estimate UE locations based on historical network communication data associated with the UEs. In order to train the machine learning model, known previous UE locations and corresponding historical network communication data can be provided to the machine learning model. A variety of other information, such as topographical information, can also be provided to the machine learning model. The machine learning model can be trained to predict the known previous UE locations based on the corresponding historical network communication data and any other provided information. Once it is trained, the machine learning model can be deployed to estimate real-time UE locations based on historical network communication data associated with the UEs.

Abstract: An architecture for providing indoor planning data that can be used to increase the density of mobility networks. A method can comprise receiving, via network equipment, resource exhaustion data indicative of radio spectrum usage within a determined bin representing a defined geographic area; receiving, via the network equipment, traffic data associated with the determined bin, wherein the traffic data indicates a volume of data flowing into the determined bin; receiving, via the network equipment, coverage data representing a quality of service metric data indicative of a determined reference signal receive power metric; and based on applying a ranking process to the resource exhaustion data, the traffic data, and the coverage data, generating a ranked list of structures, wherein a structure of the ranked list of structures includes the determined bin.

Abstract: Facilitating model-driven automated cell allocation in advanced networks (e.g., 5G and beyond) is provided herein. Operations of a method can comprise determining, by a system comprising a processor, a solution to an integer programming problem based on input data associated with a network inventory and configuration data for network devices of a group of network devices included in a communications network. Also, the method can comprise determining, by the system, respective cell identities and respective root sequence index assignments for the network devices. Further, the method can comprise implementing, by the system, a deployment of the respective cell identities and respective root sequence index assignments at the network devices.

Abstract: Aspects of the subject disclosure may include, for example, collecting and storing data about a communication environment including one or more communication networks wherein respective communication networks of the one or more communication networks employ respective communication technologies for communication with remote user devices in the communication environment, providing traffic forecasts of communication traffic, creating importance layers for potential build locations for equipment of the one or more communication networks, identifying desirable build locations among the potential build locations of the one or more communication networks based on the traffic forecasts of communication traffic and the importance layers, receiving user input defining planning parameters for the communication environment and determining respective target goal values for respective build options for the one or more communication networks based on the planning parameters, the identified desirable build locations and the

Abstract: A device can receive, from a network node device, call trace event data relating to characteristics of a wireless communication session between the network node device and a user equipment. The device can sequence and combine the call trace event data for a period of the wireless communication session. The device can analyze the call trace event data to determine a category of network communication traffic transmitted via a communication channel between the network node device and the user equipment. In response to a determination that the network communication traffic comprises streaming video packets, the device can facilitate directing of network resources to be allocated to support the wireless communication session.

Abstract: Facilitating model-driven automated cell allocation in advanced networks (e.g., 5G and beyond) is provided herein. Operations of a method can comprise determining, by a system comprising a processor, a solution to an integer programming problem based on input data associated with a network inventory and configuration data for network devices of a group of network devices included in a communications network. Also, the method can comprise determining, by the system, respective cell identities and respective root sequence index assignments for the network devices. Further, the method can comprise implementing, by the system, a deployment of the respective cell identities and respective root sequence index assignments at the network devices.

Abstract: A network device that determines RACH root sequences for AP devices within a given market. The network device can utilize a specialized graph coloring process or algorithm that has been adapted to, e.g., ensure that no two neighboring AP devices share the same RACH root sequences, provided certain additional constraints not found in graph coloring theory are met. For example, AP devices can have multiple RACH root sequence, whereas in traditional graph coloring problems, each vertex typically has only one color.

Abstract: A device can receive, from a network node device, call trace event data relating to characteristics of a wireless communication session between the network node device and a user equipment. The device can sequence and combine the call trace event data for a period of the wireless communication session. The device can analyze the call trace event data to determine a category of network communication traffic transmitted via a communication channel between the network node device and the user equipment. In response to a determination that the network communication traffic comprises streaming video packets, the device can facilitate directing of network resources to be allocated to support the wireless communication session.

Abstract: A device can receive, from a network node device, call trace event data relating to characteristics of a wireless communication session between the network node device and a user equipment. The device can sequence and combine the call trace event data for a period of the wireless communication session. The device can analyze the call trace event data to determine a category of network communication traffic transmitted via a communication channel between the network node device and the user equipment. In response to a determination that the network communication traffic comprises streaming video packets, the device can facilitate directing of network resources to be allocated to support the wireless communication session.

Abstract: A method and apparatus for providing planning of a plurality of base station controllers in a wireless network are disclosed. For example, the method obtains input data, and determines a limit for at least one base station controller parameter in accordance with the input data. The method determines if the limit for the at least one base station controller parameter is exceeded and determines an optimal output for an objective function, wherein the objective function is based on a plurality of penalty factors, if the limit for the at least one base station controller parameter is exceeded.

Abstract: Concepts and technologies disclosed herein are directed to the optimization of over-the-air (“OTA”) file distribution for connected cars based upon a heuristic scheduling algorithm. A schedule provided by the heuristic scheduling algorithm is designed to distribute OTA data flow to connected cars over the network (geographically) and over a scheduling time horizon (timely), and is capable of reducing the negative impact of OTA file updates on overall wireless network performance. This schedule is created based upon historical statistics associated with connected car driving patterns and simulations of connected car-specific OTA traffic over the network. By leveraging connected cars that connect to different cells at different times based upon driving patterns, the heuristic scheduling algorithm is effective in reducing OTA impact on the network.

Abstract: Techniques for locating a mobile device using a time distance of arrival (TDOA) method with disturbance scrutiny are provided. In an aspect, for respective combinations of three base station devices of a number of base station devices greater than or equal to three, intersections in hyperbolic curves, generated using a closed form function with input values based on differences of distances from the device to pairs of base station devices of the respective combinations of three base station devices, are determined. The intersection points are then tested for robustness against measurement errors associated with the input values and a subset of the intersection points that are associated with a degree of resistance to the measurement errors are selected to estimate a location of the device.

Abstract: In one embodiment, a method includes receiving, by one or more interfaces, a location of a physical object and receiving, by the one or more interfaces and from a data platform, an image associated with the physical object and the location of the physical object. The method also includes extracting, by one or more processors and from the image, an attribute associated with a feature of the physical object and classifying, by one or more processors, the attribute, wherein classifying the attribute comprises associating the attribute with a characteristic of the feature of the physical object. The method further includes classifying, by the one or more processors, the physical object and determining, by the one or more processors, to identify the physical object as eligible for modification.

Abstract: Concepts and technologies disclosed herein are directed to the optimization of over-the-air (“OTA”) file distribution for connected cars based upon a heuristic scheduling algorithm. A schedule provided by the heuristic scheduling algorithm is designed to distribute OTA data flow to connected cars over the network (geographically) and over a scheduling time horizon (timely), and is capable of reducing the negative impact of OTA file updates on overall wireless network performance. This schedule is created based upon historical statistics associated with connected car driving patterns and simulations of connected car-specific OTA traffic over the network. By leveraging connected cars that connect to different cells at different times based upon driving patterns, the heuristic scheduling algorithm is effective in reducing OTA impact on the network.

Abstract: A method and apparatus for providing planning of a plurality of base station controllers in a wireless network are disclosed. For example, the method obtains input data, and determines a limit for at least one base station controller parameter in accordance with the input data. The method determines if the limit for the at least one base station controller parameter is exceeded and determines an optimal output for an objective function, wherein the objective function is based on a plurality of penalty factors, if the limit for the at least one base station controller parameter is exceeded.

Abstract: A method and apparatus for providing planning of a plurality of base station controllers in a wireless network are disclosed. For example, the method obtains input data, and determines a limit for at least one base station controller parameter in accordance with the input data. The method determines if the limit for the at least one base station controller parameter is exceeded and determines an optimal output for an objective function, wherein the objective function is based on a plurality of penalty factors, if the limit for the at least one base station controller parameter is exceeded.