Patent 11856414
Derivative works
Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.
Active provider: Google · gemini-2.5-flash
Derivative works
Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.
Defensive Disclosure: US Patent 11856414 - Method and Apparatus for Processing Bandwidth Intensive Data Streams Using Virtual Media Access Control and Physical Layers
This Defensive Disclosure document outlines derivative works and technical disclosures for US Patent 11856414, titled "Method and apparatus for processing bandwidth intensive data streams using virtual media access control and physical layers." The aim is to establish prior art that pre-empts future incremental advancements by competitors, rendering them obvious or non-novel within the scope of wireless networking device performance enhancement through virtualized MAC and PHY layers.
Derivatives Based on Independent Claim 1 of US11856414
Independent Claim 1 describes a method for improving the performance of a wireless networking device by utilizing a processing interface that creates virtual MAC and PHY layers to aggregate bandwidth from multiple wireless transceivers operating in different frequency bands. This aggregation is transparent to higher layers and allows for concurrent use of remaining bandwidth by other devices.
1. Material & Component Substitution: Software-Defined Radio (SDR) and Multi-Protocol Transceivers
Enabling Description:
A wireless networking device incorporates a processing interface comprising a General Purpose Processor (GPP) and a Field-Programmable Gate Array (FPGA) or Digital Signal Processor (DSP) array. Instead of fixed-function wireless transceivers, the device utilizes two or more Software-Defined Radio (SDR) units. Each SDR unit can dynamically reconfigure its physical layer (PHY) characteristics, including modulation schemes, coding rates, and operating frequency bands, through software commands from the processing interface. The actual MAC interfaces are realized as configurable logic modules within the FPGA/DSP, capable of adapting to various protocol specifications (e.g., IEEE 802.11ax, 5G NR-U, LoRa). The virtual MAC and PHY interfaces, implemented as software modules on the GPP, abstract these reconfigurable SDRs. The virtual PHY collects real-time spectrum occupancy and signal-to-noise ratio (SNR) data from the SDRs, feeding it to the virtual MAC for optimized bandwidth allocation across heterogeneous wireless protocols, not just different frequency bands of a single protocol. For example, one SDR could operate in the 5 GHz Wi-Fi band while simultaneously another SDR operates as a dedicated 60 GHz WiGig link, both contributing bandwidth to a single application stream through dynamic multiplexing at the virtual MAC layer. The processing interface includes high-speed interconnects (e.g., PCIe Gen5, CXL) for low-latency data transfer between the GPP, FPGA/DSP, and SDR front-ends.
graph TD
A[Application Interface] --> P{Processing Interface}
P --> VMAC(Virtual MAC Interface)
P --> VPHY1(Virtual PHY 1)
P --> VPHY2(Virtual PHY 2)
VMAC --> BW_ALLOC[Bandwidth Allocator]
VPHY1 -- BW Availability --> BW_ALLOC
VPHY2 -- BW Availability --> BW_ALLOC
BW_ALLOC -- Control Signals --> SDR1[SDR Unit 1 (Reconfigurable Transceiver)]
BW_ALLOC -- Control Signals --> SDR2[SDR Unit 2 (Reconfigurable Transceiver)]
SDR1 -- Data/Control --> AMAC1[Actual MAC 1 (FPGA/DSP Logic)]
SDR2 -- Data/Control --> AMAC2[Actual MAC 2 (FPGA/DSP Logic)]
AMAC1 --> APHY1[Actual PHY 1 (SDR Firmware/Logic)]
AMAC2 --> APHY2[Actual PHY 2 (SDR Firmware/Logic)]
APHY1 -- RF Signal --> Wireless_Link_1[Wireless Link (e.g., 5GHz)]
APHY2 -- RF Signal --> Wireless_Link_2[Wireless Link (e.g., 60GHz)]
Wireless_Link_1 -- Data Stream --> Recipient
Wireless_Link_2 -- Data Stream --> Recipient
style SDR1 fill:#f9f,stroke:#333,stroke-width:2px
style SDR2 fill:#f9f,stroke:#333,stroke-width:2px
style AMAC1 fill:#ccf,stroke:#333,stroke-width:2px
style AMAC2 fill:#ccf,stroke:#333,stroke-width:2px
2. Operational Parameter Expansion: Terabit-Scale Distributed Wireless Fabric
Enabling Description:
A wireless networking device, conceptualized as a distributed wireless fabric controller, manages hundreds of spatially distributed, ultra-high-bandwidth optical wireless transceivers (e.g., free-space optics, LiFi) and millimeter-wave (mmWave) transceivers (e.g., 28GHz, 39GHz). Each optical transceiver offers multi-gigabit per second (Gbps) to terabit per second (Tbps) links within a tightly controlled line-of-sight (LoS) area, while mmWave transceivers provide robust Gbps links over wider areas. The processing interface, implemented as a massively parallel computing cluster (e.g., NVIDIA DGX-like systems with multiple GPUs and NPUs), handles real-time pathfinding and load balancing across this heterogeneous pool. The virtual MAC layer uses a graph-based optimization algorithm to model network topology, interference patterns, and dynamic bandwidth demands from extreme applications (e.g., uncompressed 8K VR streaming, real-time quantum data transfer). It allocates specific sub-THz frequency blocks or laser channels from multiple transceivers to achieve multi-Tbps aggregated bandwidth for a single recipient, dynamically adjusting power levels and beamforming vectors. This system operates across varying atmospheric conditions (fog, rain for optical links) and electromagnetic interference, using predictive analytics to switch between optical and mmWave PHY layers seamlessly at sub-millisecond latencies. The scale extends to building-wide or campus-wide deployments with hundreds to thousands of such transceivers.
graph TD
A[Application Layer (Tbps Req)] --> PC{Processing Cluster (Virtual MAC/PHY)}
PC --> VMAC(Virtual MAC Layer - Graph Optimizer)
PC --> VPHY_OPT(Virtual PHY - Optical Links Manager)
PC --> VPHY_MMW(Virtual PHY - Millimeter Wave Manager)
VMAC -- Control & Data Streams --> VPHY_OPT
VMAC -- Control & Data Streams --> VPHY_MMW
VPHY_OPT -- Resource Assignment --> T_OPT1[Optical Transceiver Array 1]
VPHY_OPT -- Resource Assignment --> T_OPTN[Optical Transceiver Array N]
VPHY_MMW -- Resource Assignment --> T_MMW1[mmWave Transceiver Cluster 1]
VPHY_MMW -- Resource Assignment --> T_MMWN[mmWave Transceiver Cluster N]
T_OPT1 -- Gbps/Tbps Optical Link --> R[Recipient Device]
T_OPTN -- Gbps/Tbps Optical Link --> R
T_MMW1 -- Gbps mmWave Link --> R
T_MMWN -- Gbps mmWave Link --> R
subgraph Distributed Wireless Fabric
T_OPT1
T_OPTN
T_MMW1
T_MMWN
end
style PC fill:#bbf,stroke:#333,stroke-width:2px
style VMAC fill:#cfc,stroke:#333,stroke-width:2px
style VPHY_OPT fill:#ccf,stroke:#333,stroke-width:2px
style VPHY_MMW fill:#ccf,stroke:#333,stroke-width:2px
3. Cross-Domain Application 1: Industrial Robotics and Autonomous Manufacturing
Enabling Description:
In an advanced industrial automation setting, the wireless networking device is integrated into a central Robot Control Unit (RCU) that manages a fleet of collaborative robots (cobots) and autonomous guided vehicles (AGVs) on a manufacturing floor. The RCU's processing interface dynamically allocates wireless bandwidth for real-time sensor data (Lidar, vision systems, haptic feedback) and control commands. The actual MAC/PHY layers correspond to industrial-grade Wi-Fi 6E (6 GHz band), Ultra-Wideband (UWB) for precise localization, and dedicated 5G private network radio units (e.g., 3.5 GHz CBRS band). The virtual MAC/PHY layers within the RCU aggregate bandwidth from these disparate radio technologies to ensure ultra-low-latency, high-reliability communication for mission-critical tasks like object manipulation, precision assembly, and collision avoidance. For example, an AGV's high-definition camera stream might be aggregated over Wi-Fi 6E and a 5G link, while its UWB module concurrently provides sub-centimeter positioning data to the RCU, all managed as a single logical data stream by the virtual MAC. This ensures robotic cells can operate without traditional wired connections, facilitating flexible manufacturing layouts.
graph TD
A[Robot Application (e.g., Vision, Control)] --> RCU{Robot Control Unit (Processing Interface)}
RCU --> VMAC(Virtual MAC - Robotics)
RCU --> VPHY_WIFI(Virtual PHY - WiFi 6E)
RCU --> VPHY_UWB(Virtual PHY - UWB)
RCU --> VPHY_5G(Virtual PHY - 5G Private)
VMAC -- Bandwidth & QoS Requests --> VPHY_WIFI
VMAC -- Bandwidth & QoS Requests --> VPHY_UWB
VMAC -- Bandwidth & QoS Requests --> VPHY_5G
VPHY_WIFI -- Allocates Resources --> T_WIFI[WiFi 6E Transceiver]
VPHY_UWB -- Allocates Resources --> T_UWB[UWB Transceiver]
VPHY_5G -- Allocates Resources --> T_5G[5G NR-U Transceiver]
T_WIFI -- Data Link (6GHz) --> AGV[Autonomous Guided Vehicle / Cobot]
T_UWB -- Data Link (UWB) --> AGV
T_5G -- Data Link (CBRS) --> AGV
style RCU fill:#ace,stroke:#333,stroke-width:2px
style VMAC fill:#fcc,stroke:#333,stroke-width:2px
style VPHY_WIFI fill:#cfc,stroke:#333,stroke-width:2px
style VPHY_UWB fill:#cfc,stroke:#333,stroke-width:2px
style VPHY_5G fill:#cfc,stroke:#333,stroke-width:2px
3. Cross-Domain Application 2: Smart City Infrastructure for Public Safety
Enabling Description:
A smart city node (e.g., integrated into streetlights or traffic signals) functions as the wireless networking device, providing ubiquitous high-bandwidth connectivity for public safety applications. The processing interface manages multiple actual MAC/PHY layers, including dedicated public safety LTE/5G (e.g., FirstNet B14), municipal Wi-Fi mesh (e.g., 2.4/5 GHz), and directional mmWave backhaul links (e.g., 60 GHz). The virtual MAC and PHY layers dynamically aggregate these resources to support real-time streaming from high-resolution surveillance cameras, rapid deployment of emergency drone footage, and resilient communication for first responders. For example, during a public event, live video feeds from multiple points might be aggregated over both municipal Wi-Fi and public safety 5G links, with the mmWave link providing dedicated high-capacity backhaul to a command center. The system prioritizes public safety traffic, ensuring that available bandwidth is reallocated to critical applications even if commercial Wi-Fi usage is high, without interrupting essential services.
graph TD
A[Public Safety App (e.g., Live Video, Drone Feed)] --> SCN{Smart City Node (Processing Interface)}
SCN --> VMAC(Virtual MAC - Public Safety)
SCN --> VPHY_LTE(Virtual PHY - Public Safety LTE/5G)
SCN --> VPHY_WIFI_MESH(Virtual PHY - Municipal WiFi Mesh)
SCN --> VPHY_MMW_BHL(Virtual PHY - mmWave Backhaul)
VMAC -- Priority & BW Allocation --> VPHY_LTE
VMAC -- Priority & BW Allocation --> VPHY_WIFI_MESH
VMAC -- Priority & BW Allocation --> VPHY_MMW_BHL
VPHY_LTE -- Resource Control --> T_LTE[PS LTE/5G Transceiver]
VPHY_WIFI_MESH -- Resource Control --> T_WIFI_MESH[WiFi Mesh Transceiver]
VPHY_MMW_BHL -- Resource Control --> T_MMW_BHL[mmWave Backhaul Transceiver]
T_LTE -- Data Link --> First_Responder[First Responder Devices]
T_WIFI_MESH -- Data Link --> Surveillance_Cam[Surveillance Cameras]
T_MMW_BHL -- High-Cap Backhaul --> Command_Center[Command Center]
style SCN fill:#add8e6,stroke:#333,stroke-width:2px
style VMAC fill:#ffc,stroke:#333,stroke-width:2px
style VPHY_LTE fill:#e0b0ff,stroke:#333,stroke-width:2px
style VPHY_WIFI_MESH fill:#e0b0ff,stroke:#333,stroke-width:2px
style VPHY_MMW_BHL fill:#e0b0ff,stroke:#333,stroke-width:2px
3. Cross-Domain Application 3: Deep Space Communication for Planetary Rovers
Enabling Description:
For deep space communication, a planetary rover (the wireless networking device) employs a processing interface to manage its highly constrained and heterogeneous communication links back to Earth or an orbiter. The actual MAC/PHY layers comprise multiple transceivers: a high-gain X-band antenna for direct-to-Earth (DTE) communication, a low-gain UHF antenna for communication with a Mars orbiter, and a short-range Wi-Fi link for local data transfer to a lander. The virtual MAC/PHY layers dynamically prioritize data types (e.g., scientific telemetry, high-resolution imagery, software updates) and aggregate available bandwidth across these links, which exhibit vastly different data rates, latencies, and availability windows due to orbital mechanics and power constraints. For example, during a DTE window, high-priority scientific data might be aggregated across both X-band and UHF links (if an orbiter is also in range and acting as a relay), with the virtual MAC managing fragmentation and reassembly to maximize throughput despite intermittent link quality. The system must account for relativistic effects on timing and employ advanced error correction.
graph TD
A[Rover Applications (e.g., Scientific Data, Imagery)] --> PR{Planetary Rover (Processing Interface)}
PR --> VMAC(Virtual MAC - Deep Space Comms)
PR --> VPHY_XBAND(Virtual PHY - X-Band DTE)
PR --> VPHY_UHF(Virtual PHY - UHF Orbiter Link)
PR --> VPHY_WIFI(Virtual PHY - Local WiFi)
VMAC -- Data Prioritization & Aggregation --> VPHY_XBAND
VMAC -- Data Prioritization & Aggregation --> VPHY_UHF
VMAC -- Data Prioritization & Aggregation --> VPHY_WIFI
VPHY_XBAND -- Control & Data --> T_XBAND[X-Band Antenna]
VPHY_UHF -- Control & Data --> T_UHF[UHF Antenna]
VPHY_WIFI -- Control & Data --> T_WIFI[Local WiFi Transceiver]
T_XBAND -- Long-Range Link --> Earth_Station[Earth Station]
T_UHF -- Relay Link --> Orbiter[Orbiter]
T_WIFI -- Short-Range Link --> Lander[Lander]
style PR fill:#cce,stroke:#333,stroke-width:2px
style VMAC fill:#fbe,stroke:#333,stroke-width:2px
style VPHY_XBAND fill:#d4e6ff,stroke:#333,stroke-width:2px
style VPHY_UHF fill:#d4e6ff,stroke:#333,stroke-width:2px
style VPHY_WIFI fill:#d4e6ff,stroke:#333,stroke-width:2px
4. Integration with Emerging Tech: AI-Driven Multi-Layer Optimization with IoT and Blockchain for Resource Trust
Enabling Description:
A wireless networking device integrates an AI inference engine (e.g., edge TPU, specialized NPU) into its processing interface. This AI engine continuously analyzes real-time network conditions (traffic patterns, interference, signal strength, latency), application demands, and historical performance data from local IoT sensors (e.g., environmental sensors, localized spectrum analyzers). The virtual MAC layer incorporates an AI-driven optimization algorithm (e.g., Reinforcement Learning agent) that predicts future bandwidth requirements and dynamically reallocates portions of available bandwidth from multiple transceivers (e.g., Wi-Fi 6E, mmWave, Sub-6GHz 5G, LoRaWAN) across various frequency bands. This includes proactive channel switching, adaptive beamforming adjustments, and power control to maximize aggregated throughput and minimize latency for critical applications. Furthermore, the resource allocation decisions and bandwidth usage logs are cryptographically signed and recorded on a localized blockchain ledger (e.g., a permissioned sidechain). This provides an immutable, transparent, and auditable record of resource utilization, enhancing trust in multi-operator or shared-spectrum environments and enabling micro-transactions for dynamic bandwidth trading. IoT sensors feed validated environmental data directly into the AI model and the blockchain for contextual awareness and verifiable operating conditions.
graph TD
A[Application Layer] --> PI{Processing Interface}
PI --> VMAC(Virtual MAC - AI Opt.)
PI --> VPHY1(Virtual PHY 1)
PI --> VPHY2(Virtual PHY 2)
VMAC -- Policy/Commands --> AI_ENGINE[AI Inference Engine (RL Agent)]
AI_ENGINE -- BW Allocation --> BW_ALLOC[Dynamic Bandwidth Allocator]
VPHY1 -- BW Info --> BW_ALLOC
VPHY2 -- BW Info --> BW_ALLOC
BW_ALLOC -- Control Signals --> T1[Transceiver 1 (Actual MAC/PHY)]
BW_ALLOC -- Control Signals --> T2[Transceiver 2 (Actual MAC/PHY)]
T1 -- Data --> Recipient
T2 -- Data --> Recipient
IoT_SENSORS[IoT Sensors (Env. Data)] --> AI_ENGINE
IoT_SENSORS --> BLOCKCHAIN[Blockchain Ledger (Resource Use)]
BW_ALLOC -- Logged Decisions --> BLOCKCHAIN
style PI fill:#e0ffff,stroke:#333,stroke-width:2px
style VMAC fill:#fcc,stroke:#333,stroke-width:2px
style AI_ENGINE fill:#aaffaa,stroke:#333,stroke-width:2px
style BLOCKCHAIN fill:#ccccff,stroke:#333,stroke-width:2px
style IoT_SENSORS fill:#e6ffe6,stroke:#333,stroke-width:2px
5. The "Inverse" or Failure Mode: Resilient, Low-Power, Limited-Functionality Operation
Enabling Description:
A wireless networking device is designed with a hierarchical power management system and a fault-tolerant processing interface. In the event of primary power failure, severe component degradation, or extreme environmental conditions (e.g., high radiation, intense heat leading to thermal throttling), the device transitions into a "limited-functionality" or "low-power" mode. The processing interface, upon detecting such an event (e.g., via power monitors, temperature sensors, watchdog timers), invokes a failsafe virtual MAC policy. This policy de-prioritizes non-essential applications, migrates critical data streams to the most robust and power-efficient wireless transceiver available (e.g., switching from high-bandwidth mmWave to lower-bandwidth, longer-range Sub-1GHz LoRa or narrowband IoT). If multiple transceivers exist, the virtual MAC dynamically re-allocates a minimal, guaranteed bandwidth portion to critical applications using only a single, most resilient frequency band, even if it means sacrificing aggregation. The virtual PHY layers report degraded capabilities (e.g., reduced transmit power, limited frequency hopping options), allowing the virtual MAC to operate within these constraints, ensuring continuous, albeit reduced, service for essential functions like emergency alerts or basic telemetry. Non-critical applications are suspended or buffered locally until normal operation resumes.
stateDiagram-v2
[*] --> Normal_Operation
Normal_Operation --> Power_Failure: Power Loss/Degradation
Normal_Operation --> Component_Degradation: Hardware Faults
Normal_Operation --> Extreme_Environment: High Temp/Radiation
Power_Failure --> Low_Power_Mode
Component_Degradation --> Limited_Functionality_Mode
Extreme_Environment --> Limited_Functionality_Mode
Low_Power_Mode --> Normal_Operation: Power Restored
Limited_Functionality_Mode --> Normal_Operation: Fault Remedied
state Normal_Operation {
VMAC_Normal: Full BW Aggregation
VPHY_Normal: Multi-Transceiver
}
state Low_Power_Mode {
VMAC_LP: Critical Apps Only
VPHY_LP: Single, Efficient Transceiver
}
state Limited_Functionality_Mode {
VMAC_LF: Failsafe Policy
VPHY_LF: Reduced Capability Transceiver
}
VMAC_LP --> VPHY_LP: Reduced BW
VMAC_LF --> VPHY_LF: Min BW
note right of Limited_Functionality_Mode: Prioritize emergency comms, suspend non-critical
note right of Low_Power_Mode: Minimal power draw, essential services only
Combination Prior Art Scenarios
These scenarios combine the teachings of US11856414 with existing open-source standards, demonstrating how the patent's core concepts could be implemented and extended using publicly available technologies.
1. Combination with OpenFlow/SDN for Dynamic Wireless Resource Orchestration
- Description: The processing interface described in US11856414, particularly the virtual MAC and virtual PHY layers (e.g., elements 111 and 112 in FIG. 1, or 621 and 722 in FIG. 8), can be extended to operate within a Software-Defined Networking (SDN) framework, leveraging the OpenFlow protocol. In this scenario, the virtual MAC acts as an SDN controller, abstracting the underlying actual MAC and PHY layers (transceivers 118, 728) as programmable network elements. The "bandwidth allocator" (part of the processing layer 104) is implemented as an application running on the SDN controller. This application uses OpenFlow rules to dynamically program the flow tables of the virtual PHY interfaces (which now act as OpenFlow-enabled switches/forwarders) to steer specific data streams across identified portions of different frequency bands provided by multiple physical transceivers. For example, a high-bandwidth video stream (Application A, 450 Mbps) could be split and routed over both a 5 GHz Wi-Fi transceiver and a 60 GHz mmWave transceiver by injecting appropriate OpenFlow
MATCHandACTIONrules into the virtual PHY, allowing granular control of bandwidth aggregation and traffic steering based on application requirements and real-time network conditions. The monitoring function of the ultra-streaming block (110, 720) feeds transceiver availability and performance metrics back to the SDN controller for adaptive rule updates.
2. Combination with Open vSwitch (OVS) for Virtualized Multi-Radio Bonding
- Description: The wireless networking device's processing interface (104, 714) leverages Open vSwitch (OVS) to virtualize and bond multiple wireless network interfaces at Layer 2 (MAC layer). Each actual MAC/PHY transceiver (118, 728) is represented as a virtual port within an OVS bridge. The virtual MAC layer (111, 621), acting as an OVS controller or interacting with one, dynamically configures OVS bonding modes (e.g., balance-xor, active-backup, 802.3ad LACP-like aggregation) across these virtual wireless ports. This allows the aggregation of bandwidth from transceivers operating in different frequency bands (e.g., a 2.4 GHz Wi-Fi radio and a 5 GHz Wi-Fi radio, or even a cellular modem if represented as an OVS port) for a single application stream. The virtual PHY layers (112, 722) provide real-time link quality metrics (e.g., RSSI, packet loss, latency) to the OVS controller, enabling it to adjust bonding parameters or re-prioritize links dynamically. The transparency to higher layers is maintained as the operating system or application simply sees a single, aggregated virtual network interface.
3. Combination with LoRaWAN and MQTT for Heterogeneous IoT Backhaul Aggregation
- Description: In an IoT gateway acting as the wireless networking device, the principles of US11856414 are applied to aggregate heterogeneous low-power, wide-area network (LPWAN) and local area network (LAN) technologies for IoT device backhaul. The actual MAC/PHY layers include a LoRaWAN concentrator (for long-range, low-data rate devices in the sub-GHz ISM band), a Wi-Fi 6 transceiver (for higher-bandwidth local IoT devices in 2.4/5/6 GHz bands), and an LTE-M/NB-IoT cellular module (for wide-area, low-power cellular connectivity). The processing interface defines virtual MAC and PHY layers that dynamically allocate and aggregate bandwidth for IoT data streams, which are then published to an MQTT broker. For instance, critical sensor alerts (low bandwidth) might be routed over LoRaWAN, while firmware updates for a cluster of local IoT devices (higher bandwidth) are aggregated over Wi-Fi 6 and LTE-M simultaneously. The virtual MAC analyzes the incoming MQTT topic data to determine bandwidth requirements and prioritizes uplink traffic. The unique aspect is applying the virtual MAC/PHY abstraction to aggregate extremely diverse physical layers, from narrow-band LPWANs to broadband Wi-Fi, using the common application-layer protocol (MQTT) as the driver for bandwidth demand. The "remaining portion of bandwidth availability" concept means LoRaWAN could still serve other low-priority sensors while Wi-Fi handles a bulk data transfer for another application.
Generated 5/19/2026, 12:49:01 AM