Abstract: Some embodiments include an apparatus having a low-dropout (LDO) voltage node; a driver including an output node coupled to the LDO voltage node to provide a current at the LDO voltage node; a comparator including an input node coupled to the output node of the driver and an output node coupled to an input node of the driver; a current generator coupled to the driver to generate a second current based on the first current; and a frequency compensation network coupled to the comparator and the current generator.

Abstract: A virtual Radio Access Network (vRAN) system (300) for provisioning a virtual Radio Access Network (RAN) that is portable across one or more RAN hardware platforms is provided. The virtual Radio Access Network (vRAN) system (300) includes a waveform development kit (WDK) (302), and a waveform execution environment (304). The waveform development kit (302) defines at least one portable Radio Access Network (RAN) application into a form that is instantiated on a RAN hardware (326). The waveform execution environment (304) (i) monitors real-time schedulable resources in real-time, and (ii) collects one or more statistics and monitors the one or more statistics for network automation. The waveform execution environment (304) includes a RAN hypervisor (314) that virtualizes at least one attribute of a spectral resource required to provision the RAN that is portable across at least one hardware platform of the one or more RAN hardware platforms in the RAN hardware.

Abstract: A radio mapping architecture for applying machine learning techniques to mobile wireless radio access networks, including a base station, a user equipment (UE), and a network is provided. The radio mapping architecture includes a spectrum monitoring unit and a server and utilizes the UE. The server includes a radio mapping database and a Machine Learning module. The UE or the spectrum monitoring unit captures Radio parameters to derive an input schema for the radio mapping database. The spectrum monitoring unit extracts the Radio parameters that correspond to the base station and the UE and updates them in the radio mapping database periodically. The input schema for the radio mapping database is updated with the Radio parameters sensed by the spectrum monitoring unit and the UE.

Abstract: Various embodiments of the disclosure described a system and method that implements Hi-PHY operations in a mobile network using a microservices-based architecture across a variety of heterogeneous multi-core processing nodes. Further, the system and method facilitate the optimal mapping of microservices to each element (e.g., hardware processing element or the like) of the processing node(s) based on defined optimization targets associated with deployment constraints. The system and method described may enable the portability of Hi-PHY operations by separating the functionality and implementation aspects of each microservice. Further, the system and method enable the scalability of Hi-PHY operations by creating multiple instances of microservices to distribute the processing load efficiently. The system and method described further enable the dynamic implementation of Hi-PHY processing chains through the utilization of microservices.

Abstract: Various embodiments related to a system and method for implementing a RAN telemetry framework in a mobile network, are described. The system and method may include a telemetry collection and processing (TCP) engine that may execute operations to establish communication between the TCP engine and an accelerator device. The TCP engine may be deployed on the CPU core of a server. Further, the system and method include receiving a message from the one or more accelerator device based on the established communication. The message includes one or more telemetry statistical information. Further, the system and method include executing one or more operation based on the received message. The one or more operation includes configuring one or more computing resource on the one or more accelerator device, reconfiguring one or more computing resource on the one or more accelerator device, periodically assimilating statistical information, and a telemetry operation.

Abstract: Configurations of a system and a method for implementing a framework that optimizes the execution and deployment of operations in a computationally intensive software applications including varying complexity workloads, are described. In one aspect, a portable framework (PF) may transform an algorithmic routine developed via an IDE into an intermediate form. The PF may enable adding constraint definitions to the intermediate form of the algorithmic software routine. The PF may further enable or provision including constraint definitions, hardware architecture description and multiple optimization metrics to the intermediate form. Based on the constraint definitions, the hardware architecture description, and the multiple optimization metrics the PF may determine computing resources from multiple heterogenous hardware resources deployed on a hardware platform. The execution of the operations may be optimized by deploying the operations to be executed on the determined computing resources.

Abstract: System and method for managing hardware containerization in a wireless network architecture, are described. In one aspect, capability information of a plurality of hardware units is transmitted to a host processor to select a set of hardware units in a system-on-chip (SoC). Configuration information that includes the selection of one or more hardware allocation parameters and one or more types of statistics for one or more processing flows is received by the selected set of hardware units. A hardware container is configured to enable SoC resource allocation related to a control group and a namespace of SoC resources via a plurality of hardware modules in the SoC. The hardware container is managed based on periodic collection and analysis of the statistical data via a plurality of instrumentation modules in the SoC, and the impact on the one or more processing flows is tracked at the host processor.

Abstract: A system for offloading traffic from a cellular network to a broadcast network is provided. The offloading mechanism caters to both unicast and broadcast traffic. The system includes a converged cellular core network, World Wide Web, a CDN, a Broadcast Offload Packet Core (BO-PC), a cellular base station, a Broadcast Radio Head, and a converged UE. The converged cellular core network includes an enhanced packet core, a policy rules engine and a packet inspection and steering unit. The BO-PC includes a Broadcast Proxy, a subscriber database, a Broadcast Offload Service Center, a Broadcast Offload Gateway and an analytics engine. For offloading the unicast traffic, the packet inspection and steering unit identifies sessions that are offloaded for supporting offload of the traffic from the converged cellular core network to the broadcast network.

Abstract: A system for offloading traffic from a cellular network to a broadcast network is provided. The offloading mechanism caters to both unicast and broadcast traffic. The system includes a converged cellular core network, World Wide Web, a CDN, a Broadcast Offload Packet Core (BO-PC), a cellular base station, a Broadcast Radio Head, and a converged UE. The converged cellular core network includes an enhanced packet core, a policy rules engine and a packet inspection and steering unit. The BO-PC includes a Broadcast Proxy, a subscriber database, a Broadcast Offload Service Center, a Broadcast Offload Gateway and an analytics engine. For offloading the unicast traffic, the packet inspection and steering unit identifies sessions that are offloaded for supporting offload of the traffic from the converged cellular core network to the broadcast network.

Abstract: A system and method for switching one or more User Equipment (UEs) 116A-N from a unicast mode to a broadcast or multicast mode to transmit a streaming media content to the UEs 116A-N is provided. The system includes, an Over-the-top (OTT) platform 104, a CDN 112, the UEs 116A-N, a cellular core network 202, one-to-many offload core 204, an analytics engine 206, a database 208, one-to-many transmitter 210, a real time switching module 212, a Cellular base station 214 and a user specified rules module 222. The analytics engine 206 continuously analyzes real-time and historical data stored in the database 208 to identify the UEs 116A-N that receive a streaming media content through the unicast mode and the streaming media content to be offloaded. An offload is a process by which certain portions of the streaming media content is shifted from the unicast mode to the broadcast or multicast mode.

Abstract: A radio mapping architecture for applying machine learning techniques to mobile wireless radio access networks, including a base station, a user equipment (UE), and a network is provided. The radio mapping architecture includes a spectrum monitoring unit and a server and utilizes the UE. The server includes a radio mapping database and a Machine Learning module. The UE or the spectrum monitoring unit captures Radio parameters to derive an input schema for the radio mapping database. The spectrum monitoring unit extracts the Radio parameters that correspond to the base station and the UE and updates them in the radio mapping database periodically. The input schema for the radio mapping database is updated with the Radio parameters sensed by the spectrum monitoring unit and the UE.

Abstract: A system for deploying a Radio Access Network Containerized Network Function (RAN CNF) that is portable across a plurality of RAN hardware platforms is provided. The system includes a Software Development Kit (SDK), a schedule generator and a scheduler runtime unit. The SDK enables providing a RAN functionality in a physical layer (L1) software code in a platform-independent manner as a RAN pipeline of a plurality of RAN tasks. The RAN tasks include a first and second RAN task. The first RAN task invokes an Application programming interface (API) from a plurality of Application Programming Interfaces to call to the second RAN task. The schedule generator generates a schedule for allocating a node in the RAN pipeline to one or more processing elements. The scheduler runtime unit loads the RAN tasks corresponding to nodes in the RAN pipeline, based on the schedule generated by the schedule generator.

Abstract: Configurations of a system and a method for optimizing an allocation of computing resources via a disaggregated architecture, are described. In one aspect, the disaggregated architecture may include a Layer 2 (L2) controller that may be configured to optimize an allocation of computing resources in a virtualized radio access network (vRAN). The disaggregated architecture in a distributed unit may disaggregate an execution of the operations of the distributed unit by the computing resources deployed therein. Further, the disaggregated architecture may provision statistical multiplexing and provision a mechanism for allocating the computing resources based on real-time conditions in the network. The disaggregated architecture may provision a mechanism that may enable dynamic swapping, allocation, scaling up, management, and maintenance of the computing resources deployed in the distributed unit (DU).

Abstract: A system and method for switching one or more User Equipment (UEs) 116A-N from a unicast mode to a broadcast or multicast mode to transmit a streaming media content to the UEs 116A-N is provided. The system includes, an Over-the-top (OTT) platform 104, a CDN 112, the UEs 116A-N, a cellular core network 202, one-to-many offload core 204, an analytics engine 206, a database 208, one-to-many transmitter 210, a real time switching module 212, a Cellular base station 214 and a user specified rules module 222. The analytics engine 206 continuously analyzes real-time and historical data stored in the database 208 to identify the UEs 116A-N that receive a streaming media content through the unicast mode and the streaming media content to be offloaded. An offload is a process by which certain portions of the streaming media content is shifted from the unicast mode to the broadcast or multicast mode.

Abstract: 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.

Abstract: A system for improving indoor coverage of cellular reception is provided. The system includes an Intelligent receiver and a Pico transmitter. The intelligent receiver demodulates a signal received from a Broadcast radio head (BRH) with a HPHT or a LPLT toplogy through an outdoor high gain rooftop antenna that is externally connected to the intelligent receiver. The intelligent receiver includes an artificial intelligence (AI) or Machine learning (ML) based indoor coverage monitoring unit and a Pico transmitter application. The AI/ML based indoor coverage monitoring unit continuously monitors cellular reception factors of indoor user devices. The AI/ML based indoor coverage monitoring unit predicts an optimal indoor modulation profile and selects a required modulation index required for the indoor user devices. The Pico transmitter application re-broadcasts or relays the demodulated signal, based on an optimal indoor modulation profile required for the indoor user devices.

Abstract: 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.

Abstract: A system for improving indoor coverage of cellular reception is provided. The system includes an Intelligent receiver and a Pico transmitter. The intelligent receiver demodulates a signal received from a Broadcast radio head (BRH) with a HPHT or a LPLT toplogy through an outdoor high gain rooftop antenna that is externally connected to the intelligent receiver. The intelligent receiver includes an artificial intelligence (AI) or Machine learning (ML) based indoor coverage monitoring unit and a Pico transmitter application. The AI/ML based indoor coverage monitoring unit continuously monitors cellular reception factors of indoor user devices. The AI/ML based indoor coverage monitoring unit predicts an optimal indoor modulation profile and selects a required modulation index required for the indoor user devices. The Pico transmitter application re-broadcasts or relays the demodulated signal, based on an optimal indoor modulation profile required for the indoor user devices.

Abstract: A system for dynamically offloading data and video traffic to a broadcast offload core network from a cellular network or to the cellular network from the broadcast offload core network is provided. The system includes an analytics engine, a load manager, and a radio access network (RAN). The analytics engine captures geographical radio frequency (RF) information from a geographical RF information database. The geographical RF information includes an operator infrastructure information, a physical terrain information, a subscriber information, a coverage information, a signal quality information, and telecom traffic patterns. The analytics engine determines whether to offload the data and the video traffic to at least one of a unidirectional downlink network from a unicast network or the unicast network from the unidirectional downlink network by analyzing a hybrid cellular user equipment from a particular geographical location trying to access the data or video content.

Abstract: A system for dynamically offloading data and video traffic to a broadcast offload core network from a cellular network or to the cellular network from the broadcast offload core network is provided. The system includes an analytics engine, a load manager, and a radio access network (RAN). The analytics engine captures geographical radio frequency (RF) information from a geographical RF information database. The geographical RF information includes an operator infrastructure information, a physical terrain information, a subscriber information, a coverage information, a signal quality information, and telecom traffic patterns. The analytics engine determines whether to offload the data and the video traffic to at least one of a unidirectional downlink network from a unicast network or the unicast network from the unidirectional downlink network by analyzing a hybrid cellular user equipment from a particular geographical location trying to access the data or video content.