WO2020185605A1 - Constrained optimization of wireless links in networks with competing objectives - Google Patents
Constrained optimization of wireless links in networks with competing objectives Download PDFInfo
- Publication number
- WO2020185605A1 WO2020185605A1 PCT/US2020/021515 US2020021515W WO2020185605A1 WO 2020185605 A1 WO2020185605 A1 WO 2020185605A1 US 2020021515 W US2020021515 W US 2020021515W WO 2020185605 A1 WO2020185605 A1 WO 2020185605A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- extender
- connection
- access point
- extenders
- throughput
- Prior art date
Links
- 238000005457 optimization Methods 0.000 title description 5
- 239000004606 Fillers/Extenders Substances 0.000 claims abstract description 111
- 238000005259 measurement Methods 0.000 claims abstract description 40
- 238000000034 method Methods 0.000 claims abstract description 22
- 238000004458 analytical method Methods 0.000 claims abstract description 4
- 230000005540 biological transmission Effects 0.000 claims description 4
- 230000006870 function Effects 0.000 description 19
- 238000004891 communication Methods 0.000 description 12
- 238000012545 processing Methods 0.000 description 8
- 230000002093 peripheral effect Effects 0.000 description 4
- 238000013459 approach Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000004044 response Effects 0.000 description 2
- 108010001267 Protein Subunits Proteins 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000003190 augmentative effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 239000010409 thin film Substances 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W76/00—Connection management
- H04W76/10—Connection setup
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P8/00—Arrangements for controlling dynamo-electric motors rotating step by step
- H02P8/32—Reducing overshoot or oscillation, e.g. damping
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
Definitions
- the present disclosure relates generally to the identification of network topologies based not only on discrete channel estimation measurements but also network-level information such as load and inter-channel interference.
- a preferred topology is identified that results in improved network throughput because of a more dynamic analysis of these measurements.
- Home wireless networks are typically made up of a wide mix of devices: routers, access points (APs), consumer communication devices, IoT devices, video distribution boxes, etc.
- APs access points
- IoT devices IoT devices
- video distribution boxes etc.
- each wireless network contained a single AP, to which all wireless clients (“stations” or“STAs”) connected.
- stations wireless clients
- STAs wireless clients
- the limited range of a single AP often places undesirable requirements on its placement inside the home. And, even when these requirements are met, some parts of the home are often still left without strong wireless coverage, typically due to other issues like interference from other nearby APs (e.g., neighbors), or even severe attenuation from obstacles inside the house (e.g., rebar in walls).
- hubs Existing methods for coordinated management of such multi-hub networks leave much to be desired. They are typically simple extensions of the methods available for single APs, and do not take into account the competitive nature of the objectives of different APs and/or extenders (collectively referred to as“hubs”). For example, a station typically connects to the hub with the highest RSSI (Received Signal Strength Indicator). But that hub may already be overloaded with too many other clients, and it may not be able to provide a high throughput or even a stable connection to its new client. A different hub that is located further away but is only lightly loaded with clients may have been a better choice even though it has a lower RSSI, and yet existing systems typically do not even consider this possibility.
- RSSI Receiveived Signal Strength Indicator
- FIG. 1 depicts a prior art star network topology for one or more local area networks.
- FIG. 2 depicts a prior art daisy-chained network topology for one or more local area networks.
- FIG. 3 depicts a first daisy-chained network topology for one or more local area networks according to various embodiments of the invention.
- FIG. 4 depicts a second daisy-chained network topology for one or more local area networks according to various embodiments of the invention.
- FIG. 5 depicts a star topology for one or more local area networks according to various embodiments of the invention.
- FIG. 6 depicts a plurality of extenders associated with an access point in which the load on each extender varies according to various embodiments of the invention.
- FIG. 7 illustrates traffic load between extenders and access point according to various embodiments of the invention.
- FIG. 8 depicts a plot of throughput as a function of RSSI according to embodiments of the present disclosure.
- FIG. 9 is a block diagram of an information handling system (or computing system) according to embodiments of the present disclosure.
- connections between components or systems within the figures are not intended to be limited to direct connections. Rather, data between these components may be modified, re-formatted, or otherwise changed by intermediary components. Also, additional or fewer connections may be used. It shall also be noted that the terms“coupled,”“connected,” or“communicatively coupled” shall be understood to include direct connections, indirect connections through one or more intermediary devices, and wireless connections.
- a service, function, or resource is not limited to a single service, function, or resource; usage of these terms may refer to a grouping of related services, functions, or resources, which may be distributed or aggregated.
- the use of memory, database, information base, data store, tables, hardware, and the like may be used herein to refer to system component or components into which information may be entered or otherwise recorded.
- the terms“data,” “information,” along with similar terms may be replaced by other terminologies referring to a group of bits, and may be used interchangeably.
- FIG. 1 depicts a star network topology deploying two extenders 112 connected to a wireless access point 102.
- the deployed star topology is created based on discrete RSSI measurements between the access point 102 and each of the extenders 112a, 112b.
- This prior art configuration is oftentimes not an optimal deployment because the measurements (e.g., RSSI) fail to take into account the load on each of the extenders as well as how each connection may negatively affect other connections within the topology such as inter channel interference and/or cross-talk caused by the wireless connections operating within a shared or overlapping frequency band(s).
- FIG. 2 depicts a daisy-chained network topology once again based on discrete and independent measurements of connectivity between the extenders 212a, 212b and the access point 202.
- This particular daisy-chained topology may not be optimized because of the deficiencies within prior art procedures in defining optimal network topologies.
- the stations 114a-l - 114a-3, 114b-l - 114b-2, 214a-l - 214a- 3, 214b-l - 214b-2 may be user devices and include a wide variety of applications, ranging from tasks that require low speed with low latency and very high reliability (e.g., remote lighting solutions) to tasks that demand continuous high-speed connectivity with high reliability, but where low latency (in the millisecond range) is not that important (e.g., constantly-streaming high-definition security cameras).
- these new applications may communicate the network via the AP and extender(s).
- the station 114a-l may communicate data to the network 101 through one extender 112a and one AP 102, i.e., the data flows 114a-l -> 112a -> 102 ->101 or vice versa.
- the station 214b-l may communicate data to the network 201 through the two extenders and one AP: 214b-l -> 212b -> 212a -> 202 -> 201 or vice versa.
- each of the extenders 112a and 112b may be directly coupled to the AP 102 to form a star topology.
- the extenders 212a and 212b may be communicatively coupled to the AP 202 in a daisy chain topology, i.e., the extender 212b may communicate data with the AP 202 via the extender 212a.
- each extender (“hub”) may connect directly to an AP and extend the communication range to problematic areas.
- the extender 112a in the system 100 may provide wireless communications for the STAs 114a-2 - 114a-3 that may be located in the area 130a, where the AP 102 may not be able to communicate directly with the devices in the area 130a.
- the extender 112b may cover the area 103b, where the AP 102 is not able to directly communicate data with the devices in the area 103b.
- each of the AP 102 (202) and/or extenders 112a - 112b (212a - 212b) has its own radio(s), its own connectivity rules, and its own performance objectives.
- the connections between the APs and extenders are configured without taking into account these characteristics of the AP and extenders.
- different hubs often end up with competing objectives, with unwanted results such as multiple devices vying for the same frequency channels, or a net reduction of usable spectrum available to stations due to the need for hubs to communicate wirelessly with each other.
- the following example illustrates methods in which throughput is measured instead of a discrete RSSI measurement in defining a network topology for the one access point and two extenders that share a single band or have overlapping bands.
- Example 1 one AP and two extenders that share one frequency band
- Both extenders are connected directly to the AP, as depicted in FIG. 1
- the first extender, El is connected to the AP, and the second extender, E2, is connected to El (daisy chain), as depicted in FIG. 2;
- E2 is connected to the AP, and El is connected to E2 (similar to FIG. 2, with El and E2 roles reversed).
- one of the three topologies that maximizes the minimum of connection received-signal-strength-indicator (RSSI) values in the resulting network may be selected, i.e., the topology that defines the selected cost function of this optimization approach as max ⁇ min(RSSI) ⁇ .
- the solution may be described as follows: If both El and E2 measure a higher RSSI from the AP than from the other extender (E2 or El, respectively), they connect directly to the AP, resulting in the star topology, as shown in FIG. 1.
- the extender e.g.
- the direct throughput measurements between the extenders may be used instead of the RSSI to improve this method.
- the cost function of maximizing the minimum RSSI value between hubs may be practical and easy to optimize.
- This method does not consider the fact that, if the path between the AP and one of the extenders (say E2) is a multi hop (daisy chain topology, i.e., AP ⁇ — >E1 ⁇ — >E2), and if both connections operate in the same frequency band (for example, because of heavy interference in the other bands), the end-to-end throughput between the AP and E2 may be TlA * T21 / (TlA + T21), where T1A and T21 are the throughput values for connections from El to the AP and from E2 to El, respectively).
- the direct throughput measurements between the extenders may be used instead of RSSI, to thereby modify the method for selecting a topology.
- max ⁇ min(Tput) ⁇ where Tput is the throughput from the AP to each extender, is a better cost function than max ⁇ min(RSSI) ⁇ , because it maximizes the minimum throughput from the AP to the extenders.
- Figure 3 depicts a first daisy-chained topology in which an access point 302 is coupled to a first extender 312a, which is coupled to a second extender 312b.
- the topologies in Figs. 3 - 5 result from a more dynamic modeling of the network where other factors are also considered, including load and inter-channel interference.
- the channel responses between the access point 302 and the extenders 312 are measured.
- measurements taken across the network such that inter-channel interference and network load, are also included in defining a preferred network configuration.
- band allocation may be adjusted across these connections to further increase throughput as a result of further improvements of inter-channel interference.
- Figure 4 depicts a second daisy-chained topology in which an access point 402 is coupled to a second extender 412b, which is coupled to the first extender 412a.
- measurements are taken that not only account for discrete channel response measurements but also inter-channel interference and load are measured across the entire network. This resulting topology may also allocate different bands between the extenders and the access point to further increase overall throughput.
- Figure 5 depicts a star topology in which an access point 502 is coupled directly to a first extender 512a and second extender 512b.
- This topology may be identified as a result of channel measurements, network inter-channel interference and load.
- the result of this more dynamic modeling of network performance provides a more accurate depiction of the network and identifies a preferred topology that improves overall throughput. Exemplary network scenarios and corresponding channel measurements, inter-channel infringement and load are described later in this application to highlight the improved overall throughput of the network when a more dynamic model is used in deployment of network topologies.
- Figure 6 illustrates a possible scenario in which load across a first extender 612a and a second extender 612b is asymmetric.
- the load across the two extenders is highly disproportionate which will result in traffic to/from the first extender being significantly larger than the traffic to/from the second extender.
- This asymmetric traffic may result in heavy cross-talk between channels if they are shared between components.
- the unequal load may be disproportionately balanced if a selected network topology does not take this into account.
- Figure 7 illustrates the effect of asymmetric load and inter-channel interference across channels within a network.
- the channel between the first extender 712a and access point 702 is significantly more congested than the channel between the second extender 712b and the access point 702.
- the traffic stream from the first extender 712a contains only a single unused window for transmission of traffic while the traffic stream from the second extender 712b contains many unused windows.
- This unbalanced traffic load may not only bog down a single node within a network topology but may also result in significant inter-channel interference. Accordingly, various procedures are described below in which this type of information is analyzed to define a particular topology and frequency band allocation to enhance overall network throughput.
- Example 2 one AP and two extenders and two frequency bands
- Systems 300, 400, 500 may use two frequency bands for communication.
- the system may operate under the following conditions:
- the daisy-chain topologies in FIGS. 3 and 4 may result in a throughput from E2 to AP of 143 (since El connects to both the AP and E2 in the 5G band), while the star topology in FIG. 5 may result in a throughput of only 50.
- a topology with higher throughput than the star topology in FIG. 5 may be selected for communication.
- the total load on El may be also considered to select the topology. If El has many devices already connected to it, the airtime of El that is available for E2 may be low, let’s say 20%. Therefore, the effective throughput from E2 to AP in the daisy-chain topology in FIGS. 3 and 4 may end up being only 29 (20% of 143), which is again lower than the throughput achieved with the star configuration.
- the cost function may need to be modified to incorporate the load of individual extenders in addition to the nominal throughput in the determination of the optimal topology.
- such an approach may be achieved by considering the load on each extender in the computation of the corresponding effective throughput.
- This approach may modify the cost function indirectly, by modifying the throughput function that is used in the cost function.
- Example 3 one AP and two frequency bands
- a communication system may include a single AP and support wireless links to multiple stations, in two frequency bands, such as the 2G and the 5G bands, and use band steering.
- Band steering is the process by which an AP encourages a station to connect using a particular band (in this case 2G or 5G) in order to improve overall performance.
- one method for band steering is to minimize interference, which is defined as the number of timeslots that are already occupied in a particular band.
- the AP may see that the interference in the 2G band is at 70% (for instance, because several devices are already connected that are only capable of operating in the 2G band), while in the 5G band the interference is only 30%.
- the AP may instruct a dual-band station (i.e., one capable of operating in both the 2G and 5G bands) that is connected in the 2G band to switch to the 5G band.
- the station in question may, in fact, be unable to connect to the AP in the 5G band under the particular conditions it is experiencing.
- the station may be located just outside the range of the 5G band of the AP.
- the station may be experiencing heavy interference in the 5G band from a neighbor’s 5G AP, which is located just far enough away to be invisible to the station’s own AP (and therefore not be correctly accounted for in the interference calculations).
- the station may drop its connection, which is a highly undesirable result.
- the interference minimization cost function may be modified by adding the constraint that connection drops may be kept below an acceptable threshold. Then, the AP may keep a history of past connection drops for each station and disable band steering for stations that are in danger of dropping their connections to the AP.
- Example 4 one AP and two channels
- the communication system may include one AP that communicates with multiple stations through two channels. For the purpose of illustration, it is assumed that the AP is connected to multiple stations in the 5G band, for instance.
- FIG. 8 shows a plot 800 of throughput as a function of RSSI.
- station STA may be located at a point where it is using channel 149.
- the AP transmission power is 23 dBm and the RSSI is -54 dBm, but the interference is high (e.g., 60%).
- the point A 810 in the plot 800 represents the (hypothetical) channel condition where the station STA has no interference and uses channel 149. But when the interference is taken into account, station STA is actually represented by point A 812, so its actual throughput is significantly lower.
- station STA may move to a point B 816, where the interference of the channel is low (e.g., 20%).
- the transmit power of the AP on channel 36 is 6 dB lower at 17 dBm, but the RSSI is still very high at -60 dBm, and the significantly lower interference means that the throughput of station STA may approximately double by moving from channel 149 to channel 36.
- the point B 814 represents the (hypothetical) channel condition where the station STA uses channel 36 and has no interference.
- Station STA may be located further away from the AP. It is assumed that station STA is using channel 149 and the point C 820 corresponds to the channel condition of station STA where the interference is still 60%. As depicted, the RSSI is significantly lower at -74 dBm, and so is its throughput, compared to the condition at the point A 812. In the plot 800, the point C 818 represents the (hypothetical) channel condition where station STA uses channel 149 and does not have any interference. If the AP re-assigns station STA to channel 36, the channel condition moves from the point C 820 to the point D 822.
- the interference is reduced to 20%, but the lower AP transmit power (by 6 dB) may push the RSSI of station STA to a low enough level (-80 dBm) that station STA may lose connectivity and its throughput may go down to zero.
- the cost function of minimizing the interference may result in an undesirable disconnect event. Therefore, in embodiments of the present invention, the cost function may be augmented by taking into account the uplink RSSI (to determine whether the station is in a high RSSI or low RSSI location) and the AP transmit power (which acts as a proxy for the downlink RSSI).
- aspects of the present patent document may be directed to, may include, or may be implemented on one or more information handling systems (or computing systems).
- An information handling system/computing system may include any instrumentality or aggregate of instrumentalities operable to compute, calculate, determine, classify, process, transmit, receive, retrieve, originate, route, switch, store, display, communicate, manifest, detect, record, reproduce, handle, or utilize any form of information, intelligence, or data.
- a computing system may be or may include a personal computer (e.g., laptop), tablet computer, mobile device (e.g., personal digital assistant (PDA), smart phone, etc.) smart watch, server (e.g., blade server or rack server), a network storage device, camera, or any other suitable device and may vary in size, shape, performance, functionality, and price.
- the computing system may include random access memory (RAM), one or more processing resources such as a central processing unit (CPU) or hardware or software control logic, ROM, and/or other types of memory.
- RAM random access memory
- processing resources such as a central processing unit (CPU) or hardware or software control logic, ROM, and/or other types of memory.
- Additional components of the computing system may include one or more disk drives, one or more network ports for communicating with external devices as well as various input and output (I/O) devices, such as a keyboard, a mouse, touchscreen and/or a video display.
- the computing system may also include one or more buses operable to transmit communications between the various hardware components.
- FIG. 9 depicts a block diagram of an information handling system (or computing system) according to embodiments of the present disclosure. It will be understood that the functionalities shown for system 900 may operate to support various embodiments of a computing system— although it shall be understood that a computing system may be differently configured and include different components, including having fewer or more components as depicted in FIG. 6.
- the computing system 900 includes one or more central processing units (CPU) 901 that provides computing resources and controls the computer.
- CPU 901 may be implemented with a microprocessor or the like, and may also include one or more graphics processing units (GPU) 919 and/or a floating-point coprocessor for mathematical computations.
- System 600 may also include a system memory 902, which may be in the form of random-access memory (RAM), read-only memory (ROM), or both.
- RAM random-access memory
- ROM read-only memory
- An input controller 903 represents an interface to various input device(s) 904, such as a keyboard, mouse, touchscreen, and/or stylus.
- the computing system 900 may also include a storage controller 907 for interfacing with one or more storage devices 908 each of which includes a storage medium such as magnetic tape or disk, or an optical medium that might be used to record programs of instructions for operating systems, utilities, and applications, which may include embodiments of programs that implement various aspects of the present disclosure.
- Storage device(s) 908 may also be used to store processed data or data to be processed in accordance with the disclosure.
- the system 900 may also include a display controller 909 for providing an interface to a display device 911, which may be a cathode ray tube (CRT), a thin film transistor (TFT) display, organic light-emitting diode, electroluminescent panel, plasma panel, or other type of display.
- a display device 911 which may be a cathode ray tube (CRT), a thin film transistor (TFT) display, organic light-emitting diode, electroluminescent panel, plasma panel, or other type of display.
- the computing system 900 may also include one or more peripheral controllers or interfaces 905 for one or more peripherals 906. Examples of peripherals may include one or more printers, scanners, input devices, output devices, sensors, and the like.
- a communications controller 914 may interface with one or more communication devices 915, which enables the system 900 to connect to remote devices through any of a variety of networks including the Internet, a cloud resource (e.g., an Ethernet cloud, a Fiber Channel over Ethernet (FCoE)/Data Center Bridging (DCB) cloud, etc.), a local area network (LAN), a wide area network (WAN), a storage area network (SAN) or through any suitable electromagnetic carrier signals including infrared signals.
- a cloud resource e.g., an Ethernet cloud, a Fiber Channel over Ethernet (FCoE)/Data Center Bridging (DCB) cloud, etc.
- FCoE Fiber Channel over Ethernet
- DCB Data Center Bridging
- LAN local area network
- WAN wide area network
- SAN storage area network
- electromagnetic carrier signals including infrared signals.
- ah major system components may connect to a bus 916, which may represent any number of physical buses. However, various system components may or may not be in physical proximity to one another. For example, input data and/or output data may be remotely transmitted from one physical location to another. In addition, programs that implement various aspects of the disclosure may be accessed from a remote location (e.g., a server) over a network.
- a remote location e.g., a server
- Such data and/or programs may be conveyed through any of a variety of machine-readable medium including, but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and holographic devices; magneto-optical media; and hardware devices that are specially configured to store or to store and execute program code, such as application specific integrated circuits (ASICs), programmable logic devices (PLDs), flash memory devices, and ROM and RAM devices.
- ASICs application specific integrated circuits
- PLDs programmable logic devices
- flash memory devices ROM and RAM devices.
- aspects of the present invention may be encoded upon one or more non-transitory computer-readable media with instructions for one or more processors or processing units to cause steps to be performed. It shah be noted that the one or more non-transitory computer- readable media shah include volatile and non-volatile memory. It shall be noted that alternative implementations are possible, including a hardware implementation or a software/hardware implementation. Hardware-implemented functions may be realized using application specific integrated circuits (ASICs), programmable arrays, digital signal processing circuitry, or the like. Accordingly, the terms in any claims are intended to cover both software and hardware implementations.
- ASICs application specific integrated circuits
- programmable arrays programmable arrays
- digital signal processing circuitry or the like. Accordingly, the terms in any claims are intended to cover both software and hardware implementations.
- the term“computer-readable medium or media” as used herein includes software and/or hardware having a program of instructions embodied thereon, or a combination thereof.
- embodiments of the present invention may further relate to computer products with a non-transitory, tangible computer-readable medium that have computer code thereon for performing various computer-implemented operations.
- the media and computer code may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind known or available to those having skill in the relevant arts.
- Examples of tangible computer-readable media include, but are not limited to: magnetic media such as hard disks; optical media such as CD-ROMs and holographic devices; magneto-optical media; and hardware devices that are specially configured to store or to store and execute program code, such as ASICs, programmable logic devices (PLDs), flash memory devices, and ROM and RAM devices.
- Examples of computer code include machine code, such as produced by a compiler, and files containing higher level code that are executed by a computer using an interpreter.
- Embodiments of the present invention may be implemented in whole or in part as machine-executable instructions that may be in program modules that are executed by a processing device.
- Examples of program modules include libraries, programs, routines, objects, components, and data structures. In distributed computing environments, program modules may be physically located in settings that are local, remote, or both.
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Power Engineering (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
Description
Claims
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP20770112.9A EP3935901A4 (en) | 2019-03-08 | 2020-03-06 | Constrained optimization of wireless links in networks with competing objectives |
BR112021016771A BR112021016771A2 (en) | 2019-03-08 | 2020-03-06 | Constrained wireless link optimization in networks with competing objectives |
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201962815869P | 2019-03-08 | 2019-03-08 | |
US62/815,869 | 2019-03-08 | ||
US201962816774P | 2019-03-11 | 2019-03-11 | |
US62/816,774 | 2019-03-11 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2020185605A1 true WO2020185605A1 (en) | 2020-09-17 |
Family
ID=72335853
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2020/021515 WO2020185605A1 (en) | 2019-03-08 | 2020-03-06 | Constrained optimization of wireless links in networks with competing objectives |
Country Status (4)
Country | Link |
---|---|
US (2) | US11445555B2 (en) |
EP (1) | EP3935901A4 (en) |
BR (1) | BR112021016771A2 (en) |
WO (1) | WO2020185605A1 (en) |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130272285A1 (en) * | 2012-04-06 | 2013-10-17 | Accelera Mobile Broadband, Inc. | Interference management and network performance optimization in dense wifi networks |
US20150171953A1 (en) * | 2013-12-13 | 2015-06-18 | Futurewei Technologies, Inc. | Software-Defined Network Infrastructure Having Virtual Range Extenders |
US20150223114A1 (en) * | 2014-01-31 | 2015-08-06 | Cable Television Laboratories, Inc. | Mesh networking of access points for load balancing |
US20150223160A1 (en) | 2014-01-31 | 2015-08-06 | Qualcomm Incorporated | Directing network association of a wireless client |
US20170135018A1 (en) * | 2015-11-10 | 2017-05-11 | Netgear, Inc. | Roaming in a wireless mesh network |
US20170272194A1 (en) * | 2014-09-30 | 2017-09-21 | British Telecommunications Public Limited Company | Interference detection |
US20170272310A1 (en) | 2016-03-18 | 2017-09-21 | Plume Design, Inc. | Optimization of distributed wi-fi networks estimation and learning |
US20180213416A1 (en) * | 2017-01-24 | 2018-07-26 | Abb Schweiz Ag | Wireless communication network |
US20180352493A1 (en) | 2017-05-17 | 2018-12-06 | Arris Enterprises Llc | Wireless steering controller |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9060289B2 (en) * | 2012-04-23 | 2015-06-16 | Wildfire.Exchange, Inc. | Interference management and network performance optimization in small cells |
US9357404B2 (en) * | 2013-05-03 | 2016-05-31 | Opentv, Inc. | Interference control in wireless communication |
US20160302096A1 (en) * | 2015-04-08 | 2016-10-13 | Amalavoyal Chari | Access Point and Extender Link Analysis, Data Stream Analysis, and Recommendations |
EP3462794A1 (en) * | 2017-09-29 | 2019-04-03 | Intel Corporation | Techniques for controlling communication networks |
US10932130B2 (en) * | 2018-05-31 | 2021-02-23 | Roku, Inc. | System and method for configuring an extender device |
-
2020
- 2020-03-06 WO PCT/US2020/021515 patent/WO2020185605A1/en active Application Filing
- 2020-03-06 EP EP20770112.9A patent/EP3935901A4/en active Pending
- 2020-03-06 BR BR112021016771A patent/BR112021016771A2/en unknown
- 2020-03-06 US US16/811,593 patent/US11445555B2/en active Active
-
2022
- 2022-09-12 US US17/942,795 patent/US20230006578A1/en active Pending
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130272285A1 (en) * | 2012-04-06 | 2013-10-17 | Accelera Mobile Broadband, Inc. | Interference management and network performance optimization in dense wifi networks |
US20150171953A1 (en) * | 2013-12-13 | 2015-06-18 | Futurewei Technologies, Inc. | Software-Defined Network Infrastructure Having Virtual Range Extenders |
US20150223114A1 (en) * | 2014-01-31 | 2015-08-06 | Cable Television Laboratories, Inc. | Mesh networking of access points for load balancing |
US20150223160A1 (en) | 2014-01-31 | 2015-08-06 | Qualcomm Incorporated | Directing network association of a wireless client |
US20170272194A1 (en) * | 2014-09-30 | 2017-09-21 | British Telecommunications Public Limited Company | Interference detection |
US20170135018A1 (en) * | 2015-11-10 | 2017-05-11 | Netgear, Inc. | Roaming in a wireless mesh network |
US20190007947A1 (en) | 2015-11-10 | 2019-01-03 | Netgear, Inc. | Roaming in a wireless mesh network |
US20170272310A1 (en) | 2016-03-18 | 2017-09-21 | Plume Design, Inc. | Optimization of distributed wi-fi networks estimation and learning |
US20180213416A1 (en) * | 2017-01-24 | 2018-07-26 | Abb Schweiz Ag | Wireless communication network |
US20180352493A1 (en) | 2017-05-17 | 2018-12-06 | Arris Enterprises Llc | Wireless steering controller |
Non-Patent Citations (1)
Title |
---|
See also references of EP3935901A4 |
Also Published As
Publication number | Publication date |
---|---|
EP3935901A1 (en) | 2022-01-12 |
US11445555B2 (en) | 2022-09-13 |
US20230006578A1 (en) | 2023-01-05 |
BR112021016771A2 (en) | 2021-11-30 |
EP3935901A4 (en) | 2022-12-07 |
US20200288510A1 (en) | 2020-09-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11470014B2 (en) | System and method of managing data connections to a communication network using tiered devices and telemetry data | |
US10764758B2 (en) | Dynamic spectrum sharing for wireless local area networks | |
US9288689B2 (en) | Configuration of wireless network cloud system based on density estimation | |
US20150245364A1 (en) | Radio resource management | |
US10142937B2 (en) | Information handling system mesh network power management | |
US11330551B2 (en) | Method and apparatus for location aware optimal wireless link selection system | |
US20210243639A1 (en) | System and method for prioritization of network traffic across multiple wireless options | |
US9722914B2 (en) | Heterogeneous network system, network apparatus, and rendezvous path selection method thereof | |
US10764959B2 (en) | Communication system of quality of experience oriented cross-layer admission control and beam allocation for functional-split wireless fronthaul communications | |
US11129125B1 (en) | Coordinated radio fine time measurement | |
US10855799B2 (en) | Management of network connections and priorities based on device profiles | |
US8649269B2 (en) | Method of controlling resource usage in communication systems | |
US11445555B2 (en) | Constrained optimization of wireless links in networks with competing objectives | |
CN103688587A (en) | Packet scheduling in a cellular communication network for the purpose of device -to -device communications | |
WO2021092548A1 (en) | Quality of experience measurements for control of wi-fi networks | |
US20190007843A1 (en) | Optimal wireless router positioning | |
US11153764B2 (en) | Determine channel plans | |
WO2016041459A1 (en) | System and Method of Traffic Engineering in a Software Defined Radio Access Network | |
US20150257023A1 (en) | Distribution of network status and information in wlan networks for self-optimization/organization | |
EP3225067B1 (en) | Method and apparatus for coordinating resources among different networks | |
US20240107331A1 (en) | Method performed by network node and network node | |
US20240314622A1 (en) | Smart network steering of wireless devices | |
US20240064610A1 (en) | Geographic limitation of Wi-Fi access points with cellular connection | |
Rea et al. | Location-aware MAC scheduling in industrial-like environment | |
JP2022151521A (en) | Method and system for providing contiguous slot in unlicensed band of radio slots |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 20770112 Country of ref document: EP Kind code of ref document: A1 |
|
REG | Reference to national code |
Ref country code: BR Ref legal event code: B01A Ref document number: 112021016771 Country of ref document: BR |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2020770112 Country of ref document: EP |
|
REG | Reference to national code |
Ref country code: BR Ref legal event code: B01E Ref document number: 112021016771 Country of ref document: BR Free format text: APRESENTE CESSAO DA PRIORIDADE US 62/815,869. |
|
ENP | Entry into the national phase |
Ref document number: 112021016771 Country of ref document: BR Kind code of ref document: A2 Effective date: 20210824 |