The present invention relates to the field of RF test equipment, and more particularly to automated mobility simulators for testing wireless ad hoc networks.
Each reference cited herein is expressly incorporated herein by reference in its entirety. U.S. Pat. No. 7,698,121 (Steenkiste, et al.) relates to a device and method for programmable wideband network emulation. The system emulated a wireless network having a programmable controller for emulating the movements of a plurality of RF nodes. A plurality of signal generation and conversion cards are interposed between a programmable logic core and the RF nodes. The signal generation and conversion cards are responsive to the control signals.
A wireless radio frequency communication network is subject to errors, interference, and limitations of the radio transmitter and receiver. Often, these are analog radio frequency domain issues, and cannot be digitally simulated absent complete characterization, and that characterization is difficult to obtain, or is part of the reason for the analysis. In some cases, testing involves interaction of the RF nodes, and characterization if their interaction is difficult or unavailable based on the known properties of a single RF node. Therefore, a physical network simulation may be used to test the actual hardware for its intended use, in an environment that emulates the environment through analog modifications of the radio signals emitted and/or received by the RF nodes.
Wireless simulators are confronted with the difficult task of recreating the operation of a system at all layers of the network protocol stack as well as the interaction of the system in the physical environment. To make the problem tractable, simplifications are typically made throughout the implementation of the simulator. Even fundamental tasks such as deciding what a received frame looks like diverge greatly from the operation of real hardware. See Takai et al. “Effects of Wireless Physical Layer Modeling in Mobile Ad Hoc Networks”, Proc. of MobiHoc 2001, October 2001.
Efforts have been made to develop RF emulators that accurately emulate down to the physical layer. RAMON uses three programmable attenuators to allow emulation of the signals between a single mobile node and two base stations. E. Hernandez and S. Helal. “RAMON: Rapid mobility network emulator”. Proc. of the 27th IEEE Conference on Local Computer Networks (LCN'02), November 2002.
See, U.S. Pat. Nos. 10,003,985; 10,004,082; 10,009,259; 10,009,783; 10,016,684; 10,028,198; 10,075,893; 10,091,218; 10,116,418; 10,117,111; 4,105,958; 4,464,791; 4,679,248; 4,737,928; 4,977,607; 5,062,148; 5,173,896; 5,191,594; 5,233,628; 5,355,519; 5,465,393; 5,794,128; 5,862,455; 5,973,638; 6,058,261; 6,061,394; 6,134,514; 6,236,363; 6,571,082; 6,600,926; 6,609,002; 6,618,696; 6,665,311; 6,724,730; 6,922,395; 6,990,075; 7,047,176; 7,231,330; 7,310,761; 7,343,094; 7,359,966; 7,376,086; 7,409,217; 7,436,789; 7,457,304; 7,460,532; 7469,143; 7,583,587; 7,590,589; 7,598,766; 7,606,165; 7,613,105; 7,620,368; 7,624,383; 7,626,931; 7,636,309; 7,646,754; 7,660,649; 7,688,847; 7,698,121; 7,719,988; 7,792,138; 7,835,273; 7,860,506; 7,911,962; 7,912,931; 7,961,629; 8,023,423; 8,027,273; 8,050,409; 8,064,377; 8,089,866; 8,107,397; 8,115,622; 8,149,801; 8,169,942; 8,213,957; 8,218,463; 8,315,231; 8,335,207; 8,340,690; 8,355,410; 8,374,352; 8,441,959; 8,483,616; 8,483,652; 8,493,902; 8,509,078; 8,514,865; 8,571,214; 8,571,895; 8,600,830; 8,630,308; 8,665,890; 8,671,176; 8,675,678; 8,682,638; 8,702,506; 8,705,368; 8,712,056; 8,724,508; 8,724,530; 8,744,419; 8,751,159; 8,755,281; 8,777,752; 8,780,693; 8,811,188; 8,821,293; 8,824,328; 8,868,027; 8,874,477; 8,874,776; 8,886,506; 8,902,767; 8,908,516; 8,935,142; 8,935,533; 8,976,802; 8,996,917; 9,009,089; 9,019,643; 9,025,607; 9,037,152; 9,059,927; 9,071,451; 9,111,055; 9,113,371; 9,118,428; 9,137,492; 9,143,274; 9,158,870; 9,160,687; 9,161,158; 9,185,529; 9,191,304; 9,210,589; 9,252,982; 9,253,608; 9,264,863; 9,266,025; 9,271,123; 9,274,912; 9,276,774; 9,294,113; 9,311,670; 9,319,842; 9,326,163; 9,350,670; 9,361,936; 9,369,255; 9,369,295; 9,369,541; 9,380,351; 9,391,869; 9,391,871; 9,495,870; 9,537,759; 9,544,126; 9,544,922; 9,554,348; 9,559,831; 9,590,918; 9,607,003; 9,656,165; 9,660,745; 9,675,882; 9,680,596; 9,698,996; 9,713,061; 9,768,893; 9,788,329; 9,794,860; 9,800,460; 9,802,120; 9,818,136; 9,825,820; 9,832,705; 9,877,265; 9894,559; 9,895,604; 9,906,291; 9,923,714; 9,935,724; 9,936,525; 9,973,881; 9,979,738; 9,985,660; 9,992,048; and 9,998,406; and U.S. Pub. Patent App. Nos. 20010033556; 20030012176; 20030088390; 20030236089; 20040044506; 20040073361; 20040088148; 20040088628; 20040093421; 20040213231; 20050004787; 20050008109; 20050053008; 20050055195; 20050075104; 20050078672; 20050135360; 20050169185; 20050169186; 20050180748; 20050204028; 20050208949; 20050254472; 20050259577; 20050283511; 20060023887; 20060034232; 20060036426; 20060167784; 20060199545; 20060209866; 20060215556; 20060240835; 20060253570; 20070002866; 20070087756; 20070153737; 20070195798; 20070280187; 20080046549; 20080056223; 20080063106; 20080123586; 20080164907; 20080195360; 20080298251; 20090086652; 20090140852; 20090190514; 20090216510; 20090303888; 20100074141; 20100097957; 20100232299; 20100235285; 20100260337; 20100273504; 20100290379; 20100317420; 20110004513; 20110063999; 20110090795; 20110310733; 20120002567; 20120020216; 20120039231; 20120059921; 20120155522; 20120182867; 20120250529; 20120250575; 20120253772; 20120258727; 20120294152; 20130060552; 20130060553; 20130060554; 20130099941; 20130107760; 20130148501; 20130159724; 20130282263; 20130322426; 20140172393; 20140269355; 20140269751; 20140307614; 20140343915; 20150078291; 20150085691; 20150207834; 20150304222; 20150331771; 20160021599; 20160105252; 20160212655; 20170061790; 20170164266; 20170207974; 20170215021; 20170277522; 20180068358; 20180091989; 20180212671; 20180279146; 20180295531; 20180302836; and 20180324609.
See also, U.S. Pat. Nos. 7,672,669, 8,874,776, 8,027,273, 8,521,092, 9,829,870, 9,612,585, and 9,521,219, and U.S. Pub. App. Nos. 20180262388, 20180262597, 20180284743, 20160320759, 20170103103, 20170105265, 20170223037, 20180151008, 20180093291, 20170339769.
The Internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect, collect and exchange data. Communications with nodes may be wired (e.g., Ethernet, serial protocols) or wireless, according to one or more of:
Short-Range Wireless
Bluetooth mesh networking—Specification providing a mesh networking variant to Bluetooth low energy (BLE) with increased number of nodes and standardized application layer (Models).
Light-Fidelity (Li-Fi)—Wireless communication technology similar to the Wi-Fi standard, but using visible light communication for increased bandwidth.
Near-field communication (NFC)—Communication protocols enabling two electronic devices to communicate within a 4 cm range.
QR codes and barcodes—Machine-readable optical tags that store information about the item to which they are attached.
Radio-frequency identification (RFID)—Technology using electromagnetic fields to read data stored in tags embedded in other items.
Transport Layer Security—Network security protocol.
Wi-Fi—technology for local area networking based on the IEEE 802.11 standard, where devices may communicate through a shared access point or directly between individual devices.
ZigBee—Communication protocols for personal area networking based on the IEEE 802.15.4 standard, providing low power consumption, low data rate, low cost, and high throughput.
Medium-Range Wireless
LTE-Advanced—High-speed communication specification for mobile networks. Provides enhancements to the LTE standard with extended coverage, higher throughput, and lower latency.
Long-Range Wireless
Low-power wide-area networking (LPWAN)—Wireless networks designed to allow long-range communication at a low data rate, reducing power and cost for transmission. Available LPWAN technologies and protocols: LoRaWan, Sigfox, NB-IoT, Weightless.
Very small aperture terminal (VSAT)—Satellite communication technology using small dish antennas for narrowband and broadband data.
Wired
Ethernet—General purpose networking standard using twisted pair and fiber optic links in conjunction with hubs or switches.
Power-line communication (PLC)—Communication technology using electrical wiring to carry power and data. Specifications such as HomePlug or G.hn utilize PLC for networking IoT devices.
U.S. 20180246801 discloses various embodiments for controlling a system under test (herein “SUT”), using a cognitive control based test runner by one or more processors, are provided. In one embodiment, by way of example only, a method for controlling an application being tested using cognitive analysis in a virtual computing environment, again by a processor, is provided. Current state data representing a current state of an application may be collected during a test run in a testing environment, such that the current state data is cognitively analyzed in relation to one or more known states. One or more control inputs may be determined for guiding the application to a target state based on the analysis. The testing environment may be a virtualized computing environment that may employ machine learning and may also be part of an Internet of Things (IoT) network.
In order to provide sufficient Quality of Assurance (QA) for a wireless network, it is of paramount importance to test a network of devices. As part of this process, in addition to outdoor testing with representative scenarios, it is customary to create a “testbed” in the “lab”. This is typically done by connecting the wireless devices using wires, or a shared medium such as Ethernet, and then manipulating the connectivity so that the desired network topology is obtained for running tests.
The state of art in such testing uses stationary devices and allows testing of static connectivity, that is, where the connectivity between devices does not change or is changed manually. Due to this, the dynamic connectivity experienced by nodes in a mobile ad hoc network cannot be adequately modeled in a wireless testbed.
The present invention provides a method and apparatus for automatically modeling any given mobility pattern or pattern of connectivity dynamics, while still using a stationary, static testbed. This is done by automatically changing the attenuation on the wires between wireless devices in accordance with the expected attenuation changes that the devices would experience were they to move in that mobility pattern or experience the connectivity dynamics. This may be implemented in both real-time and non-real-time.
A model for real-world connectivity dynamism may be implemented as a standalone process in Computer A. This may be based off of a predefined mobility model (e.g. Random Waypoint model, etc.), or a sequence of link up/downs based on a connectivity dynamism model.
A method is provided to track the path loss matrix between devices at periodic time snapshots in accordance with the mobility or dynamic connectivity model in Computer A and feed it to a Computer B. In other words, mobility/dynamism is captured as a time-varying sequence of path losses between every pair of nodes.
A testbed of devices is provided which is pairwise connected using a stack of attenuators, each aggregate stack settable to a desired attenuation using dedicated Computers Cx,y, (e.g., Raspberry Pi) for each pair of devices (x,y).
The technology also provides a method running, e.g., on Computer B, that takes each entry in the path loss matrix M obtained from Computer A, and sends the value of entry M(x,y) to the Computer Cx,y corresponding to the pair of devices x,y.
A method is also provided for connecting Computer Cx,y to each of the attenuators in the attenuator stack, and a process runs on each Computer Cx,y that sets the attenuation of each individual attenuator in the stack, so that the combined attenuation is equal to the value received from Computer B.
The above steps may be executed in real-time, that is, the path loss matrices are sent from Computer A to B to C as they are generated, or in non-real-time, that is, sent in a batch after the model terminates.
It is therefore an object to provide a radio frequency device, comprising: a packet data interface port; a radio frequency signal input port; a modified radio frequency signal output port; a microcontroller, configured to: control the packet data interface port, receive an input control signal through the packet data interface port, transmit a status report through the packet data interface port, and produce an output control signal in dependence on the input control signal; and a radio frequency signal control device, configured to modify a radio frequency signal received through the radio frequency signal input port according to an analog radio frequency signal modification process, over a range of modification selectively controlled in dependence on the output control signal, and to communicate the modified radio frequency signal through the modified radio frequency signal output port.
The packet data interface port may comprise an IEEE 802 port and the microcontroller may transmit the status report through the IEEE 802 port to a remote server.
The radio frequency signal control device may comprise at least one of a radio frequency attenuator, a radio frequency delay, a radio frequency noise source, a radio frequency filter, a radio frequency equalizer, and a radio frequency amplifier. The output control signal may comprise an analog output signal.
The radio frequency device may further comprise a control processor, communicating through the packet data interface port with the microcontroller, the control processor being configured to: generate a plurality of the input control signals for a plurality of respective radio frequency devices; and coordinate the plurality of respective radio frequency devices to concurrently modify a plurality of radio frequency signals. The control processor may be configured to control the plurality of respective radio frequency devices, to dynamically change the plurality of input control signals over time. The plurality of input control signals may be dynamically changed over time to emulate radio frequency conditions resulting from mobility of nodes in a mobile ad hoc radio frequency communication network, wherein each radio frequency signal control device emulates a radio frequency path within the mobile ad hoc radio frequency communication network.
It is a further object to provide a method, comprising: receiving an input control signal through a packet data interface port of a radio frequency device comprising a microcontroller having a packet data interface port; transmitting a status report from the microcontroller through the associated packet data interface port; producing an output control signal from the microcontroller in dependence on the input control signal; and modifying a received radio frequency signal with an analog radio frequency signal modification device, over a range of analog signal modification, selectively in dependence on the output control signal.
The packet data interface port may comprise an IEEE 802 port, and the method may further comprise transmitting the status report through the IEEE 802 port to a remote server.
The radio frequency signal modification device may comprise at least one of a radio frequency attenuator, a radio frequency delay, a radio frequency noise source, a radio frequency filter, a radio frequency equalizer, and a radio frequency amplifier. The radio frequency signal control device may comprise a radio frequency signal generator. The radio frequency signal control device may comprise a radio frequency switch matrix. The output control signal may comprise an analog output signal.
The method may further comprise communicating through the packet data interface port between a remote control processor and the microcontroller, the remote control processor generating a plurality of the input control signals for a plurality of respective radio frequency devices comprising the microcontroller and the analog radio frequency signal modification device.
The control processor may coordinate the plurality of respective radio frequency devices comprising the microcontroller and the analog radio frequency signal modification device to concurrently dynamically modify a plurality of radio frequency signals over time.
The method may further comprise modelling mobility of a node in an ad hoc network comprising a plurality of nodes; defining a path loss matrix selectively dependent on the modelled mobility of the plurality of nodes in the ad hoc network; and said modifying the received radio frequency signal comprises emulating the modelled mobility of the plurality of nodes with respect to modifications of respective received radio frequency signals from a plurality of other nodes.
The method may further comprise dynamically changing the plurality of input control signals are over time to emulate radio frequency conditions resulting from mobility of nodes in a mobile ad hoc radio frequency communication network, wherein each radio frequency signal modification device emulates a radio frequency path within the mobile ad hoc radio frequency communication network.
It is a still further object to provide a testing system, comprising: a plurality of radio frequency devices, each radio frequency device comprising:
a packet data interface port,
a microcontroller configured to:
a control processor, communicating through the packet data interface port of each respective radio frequency device with the respective microcontroller of the respective radio frequency device, the control processor being configured to generate a plurality of the input control signals for the plurality of respective radio frequency devices; and
a mobility simulator, configured to generate a dynamically changing model of a multi-node communication network subject to changing communication channels, wherein the mobility simulator is configured to provide the dynamically changing model to the control processor.
Each respective radio frequency signal control device may be controlled according to the respective input control signal to vary a path loss over time and the path loss varies over time to emulate mobility according to at least one of a free space algorithm and a two-ray algorithm.
The mobility simulator may be configured to generate a matrix representing mobility model-consistent changes of the modification of the received radio frequency signals by the plurality of radio frequency devices, and the input control signals generated by the control processor comprise cell values of the matrix, sent to respective radio frequency devices.
It is also an object to provide a device, comprising a microcontroller having a packet data interface port, configured to control the packet data interface port, receive an input control signal through the packet data interface port, transmit a status report through the packet data interface port, and in dependence on the input control signal, produce an output control signal; and a radio frequency signal control device, configured to modify a received radio frequency signal over a range selectively in dependence on the output control signal.
It is a further object to provide a method, comprising: receiving a input control signal through a packet data interface port of a device comprising a microcontroller having a packet data interface port; transmitting a status report through the packet data interface port; producing an output control signal in dependence on the input control signal; and modifying a received radio frequency signal with a radio frequency signal control device, over a range of modification, selectively in dependence on the output control signal.
It is a still further object to provide a device, comprising: a packet data interface port; a microcontroller, configured to control the packet data interface port, receive a input control signal through the packet data interface port, transmit a status report through the packet data interface port, and in dependence on the input control signal, produce an output control signal; and a radio frequency modification device, configured to modify a received radio frequency signal over a range selectively in dependence on the output control signal.
It is also an object to provide a testing system, comprising: a device, comprising a packet data interface port, a microcontroller configured to control the packet data interface port, receive a input control signal through the packet data interface port, transmit a status report through the packet data interface port, and in dependence on the input control signal, and produce an output control signal to control a radio frequency signal control device for modifying a received radio frequency signal over a range selectively in dependence on the output control signal; a control processor, communicating through the packet data interface port with the microcontroller, configured to generate a plurality of the input control signals for a plurality of respective devices comprising the microcontroller and the radio frequency signal control device; and a mobility simulator, configured to generate a dynamically changing model of a multi-node communication network subject to changing communication channels, wherein the mobility simulator is configured to provide the dynamically changing model to the control processor.
The report may be, for example, an acknowledgement message or flag within a message, that verifies that indicates a status of the device, of the radio frequency signal modified by the device, or a response to the radio frequency signal, for example. The report may be broadcast to all nodes, to selected nodes, e.g., adjacent or nearby nodes, or communicated to specific nodes and/or a centralized controller. In a complex environment, where signal communication is not guaranteed, acknowledgements and reports may help distinguish between different types of communication issues, especially within a testbed environment, where multiple variables may be at play. In addition, in some cases, the testbed is used outside of a laboratory environment, or portions reside outside the environment, and reports are useful even where reliable performance of most nodes in accordance with commands issued for them is assured.
The packet data interface port comprises at least one of an Ethernet port, a wireless Ethernet port, and an IEEE 802.11 wireless Ethernet port.
The radio frequency signal control device may comprise at least one of a radio frequency attenuator, a radio frequency delay, a radio frequency noise source, a radio frequency filter, a radio frequency equalizer, a radio frequency signal generator, a radio frequency switch matrix, and a radio frequency amplifier.
The output control signal may comprise at least one of an analog output signal, a serial data digital output signal, a parallel data digital multibit output signal, and a parallel binary-weighted multibit digital output signal.
The system may further comprise a control processor, communicating through the packet data interface port with the microcontroller, the control processor being configured to generate a plurality of the input control signals for a plurality of respective devices comprising the microcontroller and the radio frequency signal control device. The control processor may be configured to coordinate the plurality of respective devices comprising the microcontroller and the radio frequency signal control device to concurrently modify a plurality of radio frequency signals. The control processor may be configured to dynamically change the plurality of input control signals over time.
The plurality of input control signals may be dynamically changed over time to emulate radio frequency conditions resulting from mobility of nodes in a mobile ad hoc radio frequency communication network.
It is a further object to provide a method of testing radio frequency ad hoc network communication devices, comprising: providing a plurality of node device, each node device comprising a microcontroller configured to interface to a digital communication network, to receive control parameters, a radio frequency signal modification device, configured to modify a received radio frequency signal selectively dependent on the control parameters, an RF input port configured to receive the radio frequency signal, and an RF output port configured to transmit a modified radio frequency signal; receiving the control parameters through the digital communication network; and modifying the received radio frequency signal according to the received control parameters.
The method may further comprise communicating a report from the microcontroller through the digital communication network.
The method may further comprise interfacing a radio frequency transceiver to the RF output port, wherein a modification of a transmitted signal from the radio frequency transceiver is asymmetric with a modification of a received signal to the radio frequency transceiver.
The method may further comprise interfacing a radio frequency transceiver to the RF output port, wherein the transmitted signal from the radio frequency transceiver is not modified and the received signal to the radio frequency transceiver is modified.
The method may further comprise interfacing a radio frequency transceiver to the RF output port, wherein a modification of a transmitted signal from the radio frequency transceiver is symmetric with a modification of a received signal to the radio frequency transceiver.
The radio frequency signal modification device may comprise a programmable attenuator and/or a programmable delay configured to emulate multipath signal distortion.
The microcontroller may communicate though the digital communication network with a coordination server configured to communicate with a plurality of microcontrollers, wherein the RF output of a plurality of a first node interface device is connected to the RF input of a second node interface device and a third node interface device, the RF output of a plurality of the second node interface device is connected to the RF input of the first second node interface device and the third node interface device, and the RF output of the third node interface device is connected to the RF input of the first node interface device and the second node interface device.
The control parameters may comprise parameters describing a change in radio frequency modification over time. The control parameters comprise parameters are derived from a mobility model.
The method may further comprise modelling mobility of the node interface device; defining a path loss matrix selectively dependent on the modelled mobility of the node interface device; and said modifying the received radio frequency signal according to the received control parameters comprises emulating the modelled mobility with respect to modifications of the received radio frequency signal.
The method may further comprise modelling mobility of the node interface device in an ad hoc network comprising a plurality of node interface devices; defining a path loss matrix selectively dependent on the modelled mobility of the node interface device in the ad hoc network comprising the plurality of node interface devices; and said modifying the received radio frequency signal according to the received control parameters comprises emulating the modelled mobility of the plurality of node interface devices with respect to modifications of respective received radio frequency signals from a plurality of other node interface devices.
The path loss matrix may define a change of network state over time.
The RF output of a first node interface device may be conveyed to serve as an RF input to a second node interface device, substantially without an intervening active RF signal modification device, such that the RF output of the second node interface device is a composite of the modification by the received radio frequency signal by the first node interface device and the second node interface device.
A plurality of node interface devices may be provided, and configured to form an ad hoc network test bed. The control parameters may be received from a computational network simulator.
The method may further comprise interfacing a radio frequency receiver to the RF output, analyzing the modified radio frequency signal with the radio frequency receiver, and comparing the analyzing modified radio frequency signal with a result from the computational network simulator.
The method may further comprise updating a network model employed by the computational network simulator based on the analyzed modified radio frequency signal and/or updating a radio frequency receiver model employed by the computational network simulator based on the analyzed modified radio frequency signal.
Yet another aspect of the disclosure is directed to a non-transitory computer readable medium having a plurality of computer executable instructions for causing the systems as described above to operate.
A schematic of the invention is shown in
As a result of the apparatus and methods mentioned above, any given mobility pattern can be modeled on a stationary testbed. That is, the system takes as input a predefined mobility pattern over a specified number of nodes, and the protocol software is executed as though the devices are moving in that pattern, but in reality they are stationary. This allows substantially more comprehensive Quality Assurance, especially when the product in question is applicable primarily to mobile contexts.
A mobility model consists of a) a certain number nodes representing wireless devices, and a representative transmission range; (b) an area of operation; and b) a trajectory of movement for each node in (a), including the average velocity. Several models of mobility have been proposed in the literature, for example, Random Waypoint, Gauss-Markov, Truncated Levy Walk, etc. See:
For example, in the Random Waypoint model each node picks a random location within the area of operation and moves towards that with constant specified velocity. When it reaches that location, it is stationary for a predefined amount of time and then repeats the process. This is done by each node of the network.
Any appropriate mobility model could be used, and in some cases, a mobility model may be defined by performance constraints (e.g., empirically based on performance of the system). One may define and implement one's own model. In the exemplary implementation, a model in github.com/panisson/pymobility has been used; however, this is only an example.
Instead of a mobility model, one could have a model for when links go down or come up: a connectivity dynamism model. In both cases, there is a connectivity snapshot at every time instant t. Similarly, the model may include dynamic interference, latency, error rate, etc.
A traditional mobility or dynamic connectivity model as described above outputs a vector of locations for each time snapshot. That is, at a given time snapshot, it outputs the (lat,long) or (x,y) coordinate of each node in the model.
The present method takes this time-varying vector and converts it into a time varying matrix, one matrix for each time snapshot. In each (square) matrix, the rows and columns are the node identifiers, and the entry (r, c) denotes the path loss between the locations of the two nodes.
The path loss between two locations L1 and L2 is calculated as a function of the Euclidean distance between L1 and L2. There are several functions that are available to do this. As an example, the Free Space, Two-ray path loss or other models may be employed.
Therefore, according to the present invention, a mobility model may be used to control a time-varying path loss matrix over time, to emulate the environmental path of each node. The matrix may include not only attenuation, but also time delay and frequency-dependent effects, and perhaps Doppler shifts, as may be relevant to the circumstances of the network. For example, some systems analyze signals not only for modulation sequence, but also attenuation, timing, Doppler shift, multipath, frequency-dependent channel characteristics, and the like. Each of these may be simulated in a radio frequency signal control device, though emulation of a Doppler shift in a static environment may require a frequency controllable signal generation/regeneration device. The mobility trace may be converted using Free space model, Two-ray ground reflection model, probabilistic Shadowing Model, etc.
In this scheme, the parameters of elements of the matrix are communicated to the distributed microcontrollers, which then physically implement the channel condition using their respective controlled radio frequency signal control device(s). If these change over time, a vector of representing the states and their transitions may be communicated, and the microcontrollers synchronized with a common source of consensus reference to synchronize the transitions. In a shared band, a collision may occur from an out-of-network device without a direct mode of communication to the network to be simulated, and therefore the model may inferentially and statistically model the likely behavior of this other network and its effect on, and interaction with, the network under test. For example, the simulation of this competing interfering network may be modelled within a respective node microcontroller, or externally to the microcontrollers, within a “master” microcontroller for the respective interference, or as a distributed task among the various microcontrollers. In some cases, one or more interfering networks may be physically modelled, but in others, the interference may be simulated or digitally emulated. The time varying matrices are sent from Computer A to Computer B either in real-time or after collecting all the matrices for the duration of the run.
The attenuation-controllable testbed consists of a set of wireless devices. Each wireless device is connected to an attenuator stack. An attenuator stack is a set of serially connected hardware attenuators. An example is the PE4312 attenuator from Peregrine Semiconductors, www.psemi.com/pdf/datasheets/pe4312ds.pdf. Alternates include: Analog Devices ADRF57XX, HMC8073, HMC425A, HMC291S, HMC1019A, HMC1018A, HMC941, HMC939, HMC1119, HMC629A, HMC470A, HMC802A, HMC539A, HMC273A, HMC1122, HMC305S, HMC540S, HMC306A, HMC792A, HMC1095, HMC468A, HMC624A, HMC542B, HMC472A, ADRF6801, HMC759, HMC424; IDT PDFIMGF1912, PDFIMGF1950, PDFIMGF1951, PDFIMGF1953, PDFIMGF1956, PDFIMGF1958, PDFIMGF1975, PDFIMGF1977, PDFIMGF1978, PDFIMGF2250, PDFIMGF2255, PDFIMGF2258, PDFIMGF2270; Minicircuits DAT family, EVA family, ZFAT family. ZSAT-21R5+, ZX76 family, RC4DAT family, RUDAT family, ZVVA-3000, ZX73-2500+, TAOT family, etc. Therefore, any equivalent could be used. Each device is connected to the attenuator stack via a GPIOS (General Purpose Input Output) or other appropriate interface. An alternate manifestation is using WiFi or Bluetooth to connect between the devices and the attenuator stack, by configuring separate IP addresses for each attenuator.
An attenuator stack is provided between each pair of devices. Thus, if there are 6 devices, there would be 15 attenuator stacks. Each attenuator stack can be in aggregate set to a desired value to effect a particular path loss between the corresponding devices. To control the attenuation of the stack, a dedicated Computer may be employed, called Computers Cx,y. Thus, if there are 6 devices, there are 15 Computers. Each Computer is connected to each attenuator in the stack via three pins (so a total of 9).
A reasonably small and cheap computer can be used for this purpose. For example, a Raspberry Pi or Arduino controller may be used for each Computer Cx,y.
The Computer B may be connected to each Computer Cx,y over the Internet. After the Computer B receives a matrix from Computer A, it takes an entry Mr,c where r is the row and c is the column number, and sends the value of that entry to Computer Cx,y such that x=r and y=c. That is, for example, M2,1 which represents the path loss P between node 1 and node 2 in the model, is sent to Computer C1,2. We assume that the path-loss is symmetric, therefore C1,2=C2,1.
The receiving computer Cx,y takes the value P and divides it up into values P1, P2 and P3 such that P1+P2+P3=P and sets attenuator 1 in the stack to P1, attenuator 2 in the stack to P2 and attenuator 3 in the stack to P3. Thus, the attenuation between devices x and y, controlled by Computer Cx,y is set to P.
Thus, there is an end-to-end connection between the mobile network model in Computer A and the path loss between real devices on the stationary testbed. As the model executes in Computer A, the changing path loss between nodes as they move around is reflected in the attenuation between the corresponding devices by virtue of the path loss matrix entry being written in by Computers C. Such a connection and control can be effected in real-time if necessary, or by collecting the matrices up front and “re-playing” it on Computer B at a convenient time.
Many modifications and other embodiments of the invention will come to the mind of one skilled in the art having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is understood that the invention is not to be limited to the specific embodiments disclosed, and that modifications and embodiments are intended to be included within the scope of the foregoing description.
It should be noted that, one or more aspects of the various embodiments of the present disclosure may be included in an article of manufacture (e.g., one or more computer program products) having, for instance, computer usable media. The media has embodied therein, for instance, computer readable program code for providing and facilitating the capabilities of the various embodiments of the present disclosure. The article of manufacture can be included as a part of a computer system or sold separately.
Additionally, one or more aspects of the various embodiments of the present disclosure may be designed using computer readable program code for providing and/or facilitating the capabilities of the various embodiments or configurations of embodiments of the present disclosure.
Additionally, one or more aspects of the various embodiments of the present disclosure may use computer readable program code embodied on a non-transitory computer readable medium for providing and facilitating the capabilities of the various embodiments or configurations of embodiments of the present disclosure and that may be included as a part of a computer system and/or memory system and/or sold separately.
Additionally, at least one program storage device readable by a machine, tangibly embodying at least one program of instructions executable by the machine to perform the capabilities of the various embodiments of the present disclosure can be provided.
The diagrams depicted herein are just examples. There may be many variations to these diagrams or the steps (or operations) described therein without departing from the spirit of the various embodiments of the disclosure. For instance, the steps may be performed in a differing order, or steps may be added, deleted or modified.
In various optional embodiments, the features, capabilities, techniques, and/or technology, etc. of the memory and/or storage devices, networks, mobile devices, peripherals, hardware, and/or software, etc. disclosed in the following applications may or may not be incorporated into any of the embodiments disclosed herein.
References in this specification and/or references in specifications incorporated by reference to “one embodiment” may mean that particular aspects, architectures, functions, features, structures, characteristics, etc. of an embodiment that may be described in connection with the embodiment may be included in at least one implementation. Thus, references to “in one embodiment” may not necessarily refer to the same embodiment. The particular aspects, etc. may be included in forms other than the particular embodiment described and/or illustrated and all such forms may be encompassed within the scope and claims of the present application.
It may thus be seen from the examples provided above that the improvements to devices (e.g., as shown in the contexts of the figures included in this specification, for example) may be used in various applications, contexts, environments, etc. The applications, uses, etc. of these improvements, etc. may not be limited to those described above, but may be used, for example, in combination. For example, one or more applications, etc. used in the contexts, for example, in one or more figures may be used in combination with one or more applications, etc. used in the contexts of, for example, one or more other figures and/or one or more applications, etc. described in any specifications incorporated by reference. Further, while various embodiments have been described above, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of a preferred embodiment should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
The present application is a non-provisional of, and claims benefit of priority under 35 U.S.C. § 119(e) from U.S. Provisional Patent Application No. 62/788,447, filed Jan. 4, 2019, the entirety of which is expressly incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
4105958 | Pierce et al. | Aug 1978 | A |
4464791 | Eness | Aug 1984 | A |
4679248 | McKeown | Jul 1987 | A |
4737928 | Parl et al. | Apr 1988 | A |
4977607 | Maucksch et al. | Dec 1990 | A |
5062148 | Edwards | Oct 1991 | A |
5173896 | Dariano | Dec 1992 | A |
5191594 | Argo et al. | Mar 1993 | A |
5233628 | Rappaport et al. | Aug 1993 | A |
5355519 | Hasegawa | Oct 1994 | A |
5465393 | Frostrom et al. | Nov 1995 | A |
5486509 | Jimenez et al. | Jan 1996 | A |
5579543 | Crawford et al. | Dec 1996 | A |
5794128 | Brockel et al. | Aug 1998 | A |
5862455 | Martin et al. | Jan 1999 | A |
5973638 | Robbins et al. | Oct 1999 | A |
6058261 | Rapeli | May 2000 | A |
6061394 | Itahara | May 2000 | A |
6091302 | Arevalo | Jul 2000 | A |
6134514 | Liu et al. | Oct 2000 | A |
6236363 | Robbins et al. | May 2001 | B1 |
6571082 | Rahman et al. | May 2003 | B1 |
6600926 | Widell et al. | Jul 2003 | B1 |
6609002 | Krishnamurthy et al. | Aug 2003 | B1 |
6618696 | Dean et al. | Sep 2003 | B1 |
6665311 | Kondylis et al. | Dec 2003 | B2 |
6724730 | Mlinarsky et al. | Apr 2004 | B1 |
6922395 | Elliott et al. | Jul 2005 | B1 |
6990075 | Krishnamurthy et al. | Jan 2006 | B2 |
7047176 | Klevans et al. | May 2006 | B2 |
7231330 | Hernandez-Mondragon et al. | Jun 2007 | B2 |
7310761 | Cho et al. | Dec 2007 | B2 |
7343094 | Kawahata | Mar 2008 | B2 |
7359966 | Saxena et al. | Apr 2008 | B2 |
7376086 | Paraschiv | May 2008 | B1 |
7396875 | Lockhart et al. | Jul 2008 | B2 |
7409217 | Jain et al. | Aug 2008 | B2 |
7436789 | Caliskan et al. | Oct 2008 | B2 |
7457304 | Roh et al. | Nov 2008 | B2 |
7460532 | Shin et al. | Dec 2008 | B2 |
7462435 | Hagino | Dec 2008 | B2 |
7469143 | Jain et al. | Dec 2008 | B2 |
7583587 | Qiu et al. | Sep 2009 | B2 |
7590589 | Hoffberg | Sep 2009 | B2 |
7598766 | Mercaldi-Kim et al. | Oct 2009 | B2 |
7606165 | Qiu et al. | Oct 2009 | B2 |
7613105 | Bahl et al. | Nov 2009 | B2 |
7620368 | Wang et al. | Nov 2009 | B2 |
7624383 | Barr et al. | Nov 2009 | B2 |
7626931 | Wu et al. | Dec 2009 | B2 |
7636309 | Alicherry et al. | Dec 2009 | B2 |
7646754 | McLaughlin et al. | Jan 2010 | B2 |
7660649 | Hope et al. | Feb 2010 | B1 |
7672669 | Alexander et al. | Mar 2010 | B2 |
7688847 | Kim et al. | Mar 2010 | B2 |
7698121 | Steenkiste et al. | Apr 2010 | B2 |
7719988 | Ruiz et al. | May 2010 | B1 |
7792138 | Hahm et al. | Sep 2010 | B2 |
7819322 | Hammad et al. | Oct 2010 | B2 |
7835273 | Sin | Nov 2010 | B2 |
7860506 | Jain et al. | Dec 2010 | B2 |
7911962 | Khuu et al. | Mar 2011 | B2 |
7912931 | Ahmed et al. | Mar 2011 | B2 |
7961629 | Ueda | Jun 2011 | B2 |
8023423 | Chiang et al. | Sep 2011 | B2 |
8027273 | Nguyen | Sep 2011 | B2 |
8050409 | Agrawal et al. | Nov 2011 | B2 |
8064377 | Yi et al. | Nov 2011 | B2 |
8089866 | Smith et al. | Jan 2012 | B2 |
8107397 | Bagchi et al. | Jan 2012 | B1 |
8115622 | Stolarczyk et al. | Feb 2012 | B2 |
8149801 | Hall | Apr 2012 | B2 |
8169942 | Bahk et al. | May 2012 | B2 |
8213957 | Bull et al. | Jul 2012 | B2 |
8218463 | Hall | Jul 2012 | B2 |
8315231 | Pirzada et al. | Nov 2012 | B2 |
8335207 | Singh et al. | Dec 2012 | B2 |
8340690 | Wong et al. | Dec 2012 | B2 |
8355410 | Hall | Jan 2013 | B2 |
8374352 | Song et al. | Feb 2013 | B2 |
8441959 | Erdmann et al. | May 2013 | B2 |
8483616 | Hall | Jul 2013 | B1 |
8483652 | Hall | Jul 2013 | B2 |
8493902 | Suri et al. | Jul 2013 | B2 |
8509078 | Moscibroda et al. | Aug 2013 | B2 |
8514865 | Sharma et al. | Aug 2013 | B2 |
8521092 | Kennedy et al. | Aug 2013 | B2 |
8571214 | Lima et al. | Oct 2013 | B2 |
8571895 | Medina, III et al. | Oct 2013 | B1 |
8600830 | Hoffberg | Dec 2013 | B2 |
8630308 | Wang et al. | Jan 2014 | B2 |
8665890 | Yousefi'zadeh et al. | Mar 2014 | B2 |
8671176 | Kharitonov et al. | Mar 2014 | B1 |
8675678 | Farrag et al. | Mar 2014 | B2 |
8682638 | Mlinarsky et al. | Mar 2014 | B2 |
8702506 | Hall | Apr 2014 | B2 |
8705368 | Abts et al. | Apr 2014 | B1 |
8712056 | Hall | Apr 2014 | B2 |
8724508 | Chiang et al. | May 2014 | B2 |
8724530 | Ho et al. | May 2014 | B2 |
8744419 | Hall et al. | Jun 2014 | B2 |
8751159 | Hall | Jun 2014 | B2 |
8755281 | He et al. | Jun 2014 | B2 |
8777752 | Hall | Jul 2014 | B2 |
8780693 | Kim et al. | Jul 2014 | B2 |
8811188 | Bagchi et al. | Aug 2014 | B1 |
8821293 | Hall | Sep 2014 | B2 |
8824328 | Dhanapal | Sep 2014 | B2 |
8868027 | Hall | Oct 2014 | B2 |
8874477 | Hoffberg | Oct 2014 | B2 |
8874776 | Serban et al. | Oct 2014 | B2 |
8886506 | Conway | Nov 2014 | B2 |
8902767 | Custer et al. | Dec 2014 | B2 |
8908516 | Tzamaloukas et al. | Dec 2014 | B2 |
8935142 | Conway | Jan 2015 | B2 |
8935533 | Kim et al. | Jan 2015 | B2 |
8976802 | Koka et al. | Mar 2015 | B2 |
8996917 | Chandramohan et al. | Mar 2015 | B1 |
9009089 | El Defrawy et al. | Apr 2015 | B1 |
9019643 | Medard et al. | Apr 2015 | B2 |
9025607 | Zeger et al. | May 2015 | B2 |
9037152 | Herrera et al. | May 2015 | B1 |
9059927 | Aparicio et al. | Jun 2015 | B2 |
9071451 | Hall | Jun 2015 | B2 |
9111055 | Kayton et al. | Aug 2015 | B2 |
9113371 | Sun et al. | Aug 2015 | B2 |
9118428 | Hall | Aug 2015 | B2 |
9137492 | Lima et al. | Sep 2015 | B2 |
9143274 | Zeger et al. | Sep 2015 | B2 |
9158870 | Aparicio et al. | Oct 2015 | B2 |
9160687 | Haeupler et al. | Oct 2015 | B2 |
9161158 | Hall | Oct 2015 | B2 |
9185529 | Medard et al. | Nov 2015 | B2 |
9191304 | Plate et al. | Nov 2015 | B1 |
9210589 | Panta et al. | Dec 2015 | B2 |
9252982 | Jobe et al. | Feb 2016 | B2 |
9253608 | Medard et al. | Feb 2016 | B2 |
9264863 | Hall et al. | Feb 2016 | B2 |
9266025 | Hall | Feb 2016 | B2 |
9271123 | Medard et al. | Feb 2016 | B2 |
9274912 | Conway | Mar 2016 | B2 |
9276774 | Manser | Mar 2016 | B2 |
9294113 | Feizi-Khankandi et al. | Mar 2016 | B2 |
9311670 | Hoffberg | Apr 2016 | B2 |
9319842 | Hall | Apr 2016 | B2 |
9326163 | Monogioudis et al. | Apr 2016 | B2 |
9350670 | Ko et al. | May 2016 | B2 |
9361936 | Medard et al. | Jun 2016 | B2 |
9369255 | Medard et al. | Jun 2016 | B2 |
9369295 | Hall | Jun 2016 | B2 |
9369541 | Medard et al. | Jun 2016 | B2 |
9380351 | Zhao et al. | Jun 2016 | B2 |
9391869 | Kharitonov et al. | Jul 2016 | B2 |
9391871 | Abts et al. | Jul 2016 | B1 |
9495870 | Jana et al. | Nov 2016 | B2 |
9521219 | Walker et al. | Dec 2016 | B2 |
9537759 | Calmon et al. | Jan 2017 | B2 |
9544126 | Zeger et al. | Jan 2017 | B2 |
9544922 | Hall | Jan 2017 | B2 |
9554348 | Niranjayan et al. | Jan 2017 | B2 |
9559831 | Zeger et al. | Jan 2017 | B2 |
9590918 | Lutz et al. | Mar 2017 | B2 |
9607003 | Medard et al. | Mar 2017 | B2 |
9612585 | Aggarwal et al. | Apr 2017 | B2 |
9656165 | Hall | May 2017 | B2 |
9660745 | Hall | May 2017 | B2 |
9675882 | Hall | Jun 2017 | B2 |
9680596 | Bouda et al. | Jun 2017 | B2 |
9698996 | Hall | Jul 2017 | B2 |
9713061 | Ruiz et al. | Jul 2017 | B2 |
9768893 | Wank et al. | Sep 2017 | B1 |
9788329 | Hall | Oct 2017 | B2 |
9794860 | Hall | Oct 2017 | B2 |
9800460 | Roy et al. | Oct 2017 | B2 |
9802120 | Hall | Oct 2017 | B2 |
9818136 | Hoffberg | Nov 2017 | B1 |
9825820 | Custer et al. | Nov 2017 | B2 |
9829870 | Aggarwal et al. | Nov 2017 | B2 |
9832705 | Newton et al. | Nov 2017 | B1 |
9877265 | Kim et al. | Jan 2018 | B2 |
9894559 | Ko et al. | Feb 2018 | B2 |
9895604 | Hall | Feb 2018 | B2 |
9906291 | Nakamura et al. | Feb 2018 | B1 |
9923714 | Lima et al. | Mar 2018 | B2 |
9935724 | Cooper et al. | Apr 2018 | B1 |
9936525 | Guner | Apr 2018 | B2 |
9973881 | Hall | May 2018 | B2 |
9979738 | Holland et al. | May 2018 | B2 |
9985660 | Mani et al. | May 2018 | B2 |
9992048 | Hu et al. | Jun 2018 | B2 |
9998406 | Haeupler et al. | Jun 2018 | B2 |
20010033556 | Krishnamurthy et al. | Oct 2001 | A1 |
20030012176 | Kondylis et al. | Jan 2003 | A1 |
20030088390 | Jamsa et al. | May 2003 | A1 |
20030236089 | Beyme et al. | Dec 2003 | A1 |
20040044506 | Meinila et al. | Mar 2004 | A1 |
20040073361 | Tzamaloukas et al. | Apr 2004 | A1 |
20040088148 | Szymanski et al. | May 2004 | A1 |
20040088628 | Poutanen | May 2004 | A1 |
20040093421 | Peng et al. | May 2004 | A1 |
20040213231 | Cho et al. | Oct 2004 | A1 |
20050004787 | Kubischta et al. | Jan 2005 | A1 |
20050008109 | Kemppainen et al. | Jan 2005 | A1 |
20050053008 | Griesing et al. | Mar 2005 | A1 |
20050055195 | Hernandez-Mondragon et al. | Mar 2005 | A1 |
20050075104 | Jain et al. | Apr 2005 | A1 |
20050078672 | Caliskan et al. | Apr 2005 | A1 |
20050135360 | Shin et al. | Jun 2005 | A1 |
20050169185 | Qiu et al. | Aug 2005 | A1 |
20050169186 | Qiu et al. | Aug 2005 | A1 |
20050180748 | Kawahata | Aug 2005 | A1 |
20050204028 | Bahl et al. | Sep 2005 | A1 |
20050208949 | Chiueh | Sep 2005 | A1 |
20050254472 | Roh et al. | Nov 2005 | A1 |
20050259577 | Sin | Nov 2005 | A1 |
20050283511 | Fan et al. | Dec 2005 | A1 |
20060023887 | Agrawal et al. | Feb 2006 | A1 |
20060034232 | McLaughlin et al. | Feb 2006 | A1 |
20060036426 | Barr et al. | Feb 2006 | A1 |
20060167784 | Hoffberg | Jul 2006 | A1 |
20060199545 | Abusch-Magder et al. | Sep 2006 | A1 |
20060209866 | Steenkiste et al. | Sep 2006 | A1 |
20060215556 | Wu et al. | Sep 2006 | A1 |
20060240835 | Jain et al. | Oct 2006 | A1 |
20060253570 | Biswas et al. | Nov 2006 | A1 |
20070002866 | Belstner et al. | Jan 2007 | A1 |
20070087756 | Hoffberg | Apr 2007 | A1 |
20070153737 | Singh et al. | Jul 2007 | A1 |
20070195798 | Peng et al. | Aug 2007 | A1 |
20070280187 | Wang et al. | Dec 2007 | A1 |
20080046549 | Saxena et al. | Feb 2008 | A1 |
20080056223 | Manser | Mar 2008 | A1 |
20080063106 | Hahm et al. | Mar 2008 | A1 |
20080123586 | Manser | May 2008 | A1 |
20080164907 | Mercaldi-Kim et al. | Jul 2008 | A1 |
20080195360 | Chiang et al. | Aug 2008 | A1 |
20080298251 | Khuu et al. | Dec 2008 | A1 |
20090086652 | Jain et al. | Apr 2009 | A1 |
20090140852 | Stolarczyk et al. | Jun 2009 | A1 |
20090190514 | Yi et al. | Jul 2009 | A1 |
20090216510 | Higashino et al. | Aug 2009 | A1 |
20090303888 | Ariyur et al. | Dec 2009 | A1 |
20100074141 | Nguyen | Mar 2010 | A1 |
20100097957 | Pirzada et al. | Apr 2010 | A1 |
20100227607 | Lorion | Sep 2010 | A1 |
20100232299 | Conway | Sep 2010 | A1 |
20100235285 | Hoffberg | Sep 2010 | A1 |
20100260337 | Song et al. | Oct 2010 | A1 |
20100273504 | Bull et al. | Oct 2010 | A1 |
20100290379 | Bahk et al. | Nov 2010 | A1 |
20100317420 | Hoffberg | Dec 2010 | A1 |
20110004513 | Hoffberg | Jan 2011 | A1 |
20110063999 | Erdmann et al. | Mar 2011 | A1 |
20110090795 | Li et al. | Apr 2011 | A1 |
20110310733 | Tzamaloukas et al. | Dec 2011 | A1 |
20120002567 | Sun et al. | Jan 2012 | A1 |
20120020216 | Vashist et al. | Jan 2012 | A1 |
20120039231 | Suri et al. | Feb 2012 | A1 |
20120059921 | Serban et al. | Mar 2012 | A1 |
20120155522 | Custer et al. | Jun 2012 | A1 |
20120182867 | Farrag et al. | Jul 2012 | A1 |
20120250529 | Lee et al. | Oct 2012 | A1 |
20120250575 | Chiang et al. | Oct 2012 | A1 |
20120253772 | Conway | Oct 2012 | A1 |
20120258727 | Wong et al. | Oct 2012 | A1 |
20120264377 | Seelenfreund | Oct 2012 | A1 |
20120294152 | Yousefi'zadeh et al. | Nov 2012 | A1 |
20130060552 | Aparicio et al. | Mar 2013 | A1 |
20130060553 | Patel et al. | Mar 2013 | A1 |
20130060554 | Aparicio et al. | Mar 2013 | A1 |
20130099941 | Jana et al. | Apr 2013 | A1 |
20130107760 | Ho et al. | May 2013 | A1 |
20130148501 | He et al. | Jun 2013 | A1 |
20130159724 | Kim et al. | Jun 2013 | A1 |
20130282263 | Tee | Oct 2013 | A1 |
20130322426 | Niranjayan et al. | Dec 2013 | A1 |
20140172393 | Kang et al. | Jun 2014 | A1 |
20140269355 | Monogioudis et al. | Sep 2014 | A1 |
20140269751 | Koka et al. | Sep 2014 | A1 |
20140307614 | Ruiz et al. | Oct 2014 | A1 |
20140343915 | Song | Nov 2014 | A1 |
20150078291 | Guner | Mar 2015 | A1 |
20150085691 | Custer et al. | Mar 2015 | A1 |
20150207834 | Zhao et al. | Jul 2015 | A1 |
20150304222 | Ko et al. | Oct 2015 | A1 |
20150331771 | Conway | Nov 2015 | A1 |
20160021599 | Fitzek et al. | Jan 2016 | A1 |
20160105252 | Bouda et al. | Apr 2016 | A1 |
20160212655 | Ko et al. | Jul 2016 | A1 |
20160320759 | Macha et al. | Nov 2016 | A1 |
20170061790 | Jana et al. | Mar 2017 | A1 |
20170103103 | Nixon et al. | Apr 2017 | A1 |
20170105265 | Sadwick | Apr 2017 | A1 |
20170164266 | Domaratsky | Jun 2017 | A1 |
20170207974 | Shailendra et al. | Jul 2017 | A1 |
20170215021 | de Azevedo et al. | Jul 2017 | A1 |
20170223037 | Singh et al. | Aug 2017 | A1 |
20170277522 | Conway | Sep 2017 | A1 |
20170339769 | Wennemyr et al. | Nov 2017 | A1 |
20180068358 | Hoffberg | Mar 2018 | A1 |
20180091989 | Baroudi et al. | Mar 2018 | A1 |
20180093291 | Benjamin | Apr 2018 | A1 |
20180151008 | Dehnert et al. | May 2018 | A1 |
20180212671 | Wu et al. | Jul 2018 | A1 |
20180246801 | Krauss | Aug 2018 | A1 |
20180259473 | Mohseni | Sep 2018 | A1 |
20180262388 | Johnson et al. | Sep 2018 | A1 |
20180262597 | Matthieu et al. | Sep 2018 | A1 |
20180279146 | Baroudi et al. | Sep 2018 | A1 |
20180284743 | Cella et al. | Oct 2018 | A1 |
20180295531 | Baroudi et al. | Oct 2018 | A1 |
20180302836 | Fitzek et al. | Oct 2018 | A1 |
20180324609 | Diancin | Nov 2018 | A1 |
Entry |
---|
U.S. Appl. No. 10/003,985, filed Jun. 19, 2018, Holland et al. |
U.S. Appl. No. 10/004,082, filed Jun. 19, 2018, Bane et al. |
U.S. Appl. No. 10/009,259, filed Jun. 26, 2018, Calmon et al. |
U.S. Appl. No. 10/009,783, filed Jun. 26, 2018, Baroudi et al. |
U.S. Appl. No. 10/016,684, filed Jul. 10, 2018, Hall. |
U.S. Appl. No. 10/028,198, filed Jul. 17, 2018, Fitzek et al. |
U.S. Appl. No. 10/075,893, filed Sep. 11, 2018, Hall et al. |
U.S. Appl. No. 10/091,218, filed Oct. 2, 2018, Holland et al. |
U.S. Appl. No. 10/116,418, filed Oct. 30, 2018, Wu et al. |
U.S. Appl. No. 10/117,111, filed Oct. 30, 2018, Jobe et al. |
Number | Date | Country | |
---|---|---|---|
20200220788 A1 | Jul 2020 | US |
Number | Date | Country | |
---|---|---|---|
62788447 | Jan 2019 | US |