TWI539403B - Radio spectrum trading - Google Patents

Description

Radio spectrum trading technology Field of invention

The content of this case relates to spectrum management and, more particularly, to systems and methods for trading spectrum between a spectrum owner and an attempt to lease a spectrum.

Background of the invention

As wireless technology continues to evolve, the number of wirelessly enabled devices on the market continues to increase. Not only do devices with primary tasks of wireless communication (eg, mobile phones, smart phones, etc.) appear, but applications that previously did not include any form of communication functionality become able to interact wirelessly. For example, vehicles, appliances, air conditioning (HVAC) systems, thermostats, manufacturing equipment, security systems, street signs, and the like can all be combined to interact wirelessly, and other wireless applications appear every day.

While the benefits of communication functionality associated with wireless devices are apparent, the unintended consequence of this wireless growth is the formation of a large number of traffic. Wireless communication bandwidth can usually be divided into two categories: regulated spectrum and unregulated spectrum. The regulated spectrum may be reserved for government services (eg, police, fire, etc.) or authorized to wireless service providers for exclusive use by its subscribers. Unacceptable The regulated spectrum is available to anyone and is typically limited to short-range wireless communication media (eg, Bluetooth, Wireless Local Area Network (WLAN), etc.) in a relatively "noisy" bandwidth. Due to factors such as availability, cost savings, etc., it seems logical for designers to use unregulated spectrum whenever possible. Although the unregulated spectrum is attractive to some users, the limitations of use (for example, only for short-range wireless communication), interference caused by other sources operating on the same spectrum, etc., make it impossible to directly replace the regulated spectrum. . On the other hand, the amount of regulated spectrum is very limited, so the cost of leasing regulated spectrum can be high. However, the exponential growth of new subscribers continues to drive demand.

According to an embodiment of the present invention, a system is specifically provided, comprising: a core service module for determining a radio spectrum transaction transaction for use in a spectrum of a radio frequency for wireless communication, the core service module including at least An analysis engine that sets a pricing curve based on usage data; and an instant transaction engine that determines spectrum availability in view of a spectrum request received from a requestor that wants to lease available spectrum, and determines and based on the spectrum availability The pricing curve allocates the available spectrum to satisfy the spectrum requests.

100, 100'‧‧‧ Cloud Spectrum Management System (CSMS)

102, 102'‧‧‧ Spectrum Market

104, 104'‧‧‧Marketing Communication Module

106, 106'‧‧‧ core service module

108, 108'‧‧‧Management Utility Module

110‧‧‧Administrative services

112‧‧‧Security/Persistent Module

112', 114‧‧‧Permanent modules

200‧‧‧ device

202‧‧‧System Module

204‧‧‧Processing module

206‧‧‧ memory module

208‧‧‧Power Module

210‧‧‧User Interface Module

212‧‧‧Communication interface module

214‧‧‧Communication Module

302‧‧‧Spectral exchange

304‧‧‧ Spectrum Owner

306‧‧‧Network Management

308‧‧‧Mediator

310‧‧‧Spectral Exchange API

312‧‧‧ Spectrum Owner API

314‧‧‧Intermediary to Intermediary (B2B) API

316‧‧‧Intermediary to Network (B2N) API

318‧‧‧Request Processor

320‧‧‧Event Processor

322‧‧‧Cloud Controller

400, 400'‧‧‧ instant trading engine

402, 402'‧‧‧ analysis engine

404‧‧‧Multi-target optimization engine

406‧‧‧Cognitive Engine

408‧‧‧match engine

410‧‧‧Rules based engine

412‧‧‧Consulting intermediary

414‧‧‧TFU distribution engine

416‧‧‧ Spectrum Trading Management Engine

418‧‧‧Intermediary-agent interface

500‧‧‧ Order Management Processor

502‧‧‧Settlement and billing engine

506‧‧‧Report Engine

510‧‧‧SLA Manager

512‧‧‧SLA Information Manager

514‧‧‧SLA monitoring and control

600‧‧‧Market Feed Database

602‧‧‧TFU hook database

604‧‧‧ Radio Environment Mapping Database

606‧‧‧Cloud Spectrum Database

608‧‧‧ Geographic Information System (GIS) database

610‧‧‧Enterprise Information System (EIS) database

700~710, 800~814, 1002~1012, 1202~1212, 1300~1306‧‧‧ operation

900‧‧‧core algorithm

902‧‧‧ spectrum request queue

904‧‧‧ Auction Engine

906‧‧‧ forecasted revenue engine

908‧‧‧Statistical Engine

910‧‧‧Price Curve Setting Engine

1100‧‧‧ pricing curve

1102~1106‧‧‧Area

1200‧‧‧Set pricing curve

Features and advantages of the various embodiments of the present invention will be apparent from the following description of the embodiments of the invention. Example and spectrum city Example cloud computing system for field interaction; FIG. 2 illustrates an example combination of devices available in accordance with at least one embodiment of the present disclosure; FIG. 3 illustrates an example combination of a market communication module in accordance with at least one embodiment of the present disclosure FIG. 4 illustrates an example combination of core service modules in accordance with at least one embodiment of the present disclosure; FIG. 5 illustrates an example combination of management utility modules in accordance with at least one embodiment of the present disclosure; FIG. Example assembly of a persistence module in accordance with at least one embodiment of the present disclosure; FIG. 7 illustrates example operations related to a cloud spectrum management system in accordance with at least one embodiment of the present disclosure; FIG. 8 illustrates and is based on the present disclosure Example operation related to radio spectrum transactions of at least one embodiment; FIG. 9 illustrates an example real-time transaction engine and analysis engine in accordance with at least one embodiment of the present disclosure; FIG. 10 illustrates a usage-based data based on at least one embodiment of the present disclosure And setting example operation related to the pricing curve; FIG. 11 illustrates an example pricing curve according to at least one embodiment of the present content; 12 shows the case in accordance with at least one embodiment of the content-based auction and spectrum allocation example operations related embodiment; and FIG. 13 illustrates the embodiment based on a prediction of at least one embodiment in accordance with the contents of the case Instance operations related to the distribution of spectrum.

While the following embodiments will be described with reference to the exemplary embodiments, many alternatives, modifications and variations are apparent to those skilled in the art.

Detailed description of the preferred embodiment

The present disclosure is directed to a cloud spectrum management system. In general, an example cloud spectrum management system may self-see a spectrum requester of an available radio spectrum and receive a request from a spectrum owner who wishes to lease an available radio spectrum and/or attempt to reclaim the leased radio spectrum. The Cloud Spectrum Management System can accumulate these requests and match the spectrum requestor request to the spectrum owner who wants to lease the available radio spectrum. The resulting radio spectrum transaction transaction can be performed by a cloud spectrum management system that can further monitor radio spectrum transaction changes to help ensure that the transaction is conducted in accordance with the agreed terms.

In an embodiment, the example system may include: a market communication module that communicates with the market to trade the spectrum of the radio frequency for wireless communication; the core service module, the core service module is based at least on the market communication The communication between the module and the market determines the radio spectrum transaction transaction; and the management utility module is configured to manage the radio spectrum transaction transaction determined by the core service module. The market communication module can include, for example, at least one application programming interface (API) that self-seeks the spectrum requestor of the available radio spectrum or wants to lease the available radio spectrum or reclaim the leased radio spectrum. At least one of the spectrum owners receives the information. Market communication model The group may also include at least one of: a request processor that accumulates information received from a spectrum requester and a spectrum owner; an event processor that monitors the request processor for an event; A cloud controller that communicates with the core service module (eg, incoming spectrum requests received from the spectrum market).

The example core service module can include: an instant transaction engine that receives accumulated information from a market information module; and an analysis engine that utilizes at least one of a multi-target optimization engine or a cognitive engine to at least The radio spectrum transaction transaction is determined based on the accumulated information. In an embodiment, the multi-target engine may achieve at least one of: maximizing the revenue of the spectrum owner, ensuring the quality of service of the spectrum requestor, or maximizing radio spectrum utilization. However, the cognitive engine may include a machine learning algorithm that predicts the predicted spectrum usage. The analysis engine can interact with at least one of a matching engine, a rules-based engine, a negotiation intermediary, a time-frequency unit (TFU) distribution engine, a mediator agent interface, or a spectrum transaction management engine when determining a radio spectrum transaction transaction. In the same or different embodiments, the management utility module can include an order management processor that performs radio spectrum transaction transactions. The management utility module may also include a service level agreement (SLA) manager to ensure that the spectrum requester and spectrum owner meet the terms agreed upon in the radio spectrum transaction transaction performed by the order management processor.

In the same or different embodiments, the system can include a persistence module that includes at least one database. Databases available for storage and radio spectrum availability, radio spectrum characteristics information, radio spectrum Information relating to at least one of the information and historical radio spectrum transaction transaction information. A method consistent with at least one embodiment of the present disclosure can include, for example, receiving a request from the market to find available spectrum to trade a spectrum of radio frequencies for wireless communication; matching a request to find available spectrum with a request to lease a spectrum To form a radio spectrum transaction transaction; and to supervise the implementation of radio spectrum transaction transactions.

1 illustrates an example cloud spectrum management system (CSMS) 100 that interacts with a spectrum marketplace 102 in accordance with at least one embodiment of the present disclosure. A "radio spectrum" as referred to herein may include portions of the electromagnetic spectrum, the portion of which includes a radio spectrum that can be used for wireless communication. Portions of the radio spectrum may be regionally authorized to a particular entity (eg, a wireless service provider) for their exclusive use. An entity that may have a dedicated license to use portions of the radio spectrum is referred to herein as a spectrum owner. The spectrum owner may be an entity that seeks permission to temporarily utilize portions of the regulated bandwidth owned by the spectrum owner. For example, a spectrum requestor may be a wireless service provider that is implementing heavy traffic within its own licensed spectrum and looking for additional spectrum to mitigate bottlenecks and improve customer service quality. In another example, the spectrum requestor can be a video broadcast, lecture, seminar, or not for any licensed spectrum and only for scheduled events (eg, telex conferences, wide area networks (WANs) over similar networks, lectures, seminars, Music or theater performances, etc.) Wireless service providers that lease spectrum from spectrum owners.

The CSMS 100 can communicate with the spectrum market 102 to facilitate radio spectrum transaction transactions between the spectrum requester and the spectrum owner. In this regard, CSMS 100 can also be called "intermediary" because CSMS 100 can be used in the spectrum. The radio spectrum is available between the requester and the spectrum owner. During operation, the CSMS 100 can communicate directly with the spectrum requester and the spectrum owner or with another CSMS 100 present in the spectrum market 102 to determine the spectrum requirements and the available spectrum that meets the requirements. Thus, it is possible for the CSMS 100 to interact with another CSMS 100 in the spectrum market 102 to determine the presence/availability of another CSMS 100 and to mediate between the spectrum requestor and the spectrum intermediaries associated with different mediator systems. transaction.

The CSMS 100 can include, for example, at least a market communication module 104, a core service module 106, and a management utility module 108. Modules may be customized and/or assembled via administrative services 110 and may utilize various methods and/or mechanisms known or to be developed (including, for example, access control, privacy protection, data theft, etc.) Protected by 112. The information can be stored in the persistence module 114 and can access each of the three modules. Initially, the functionality of the market communication module 104 can interact with the spectrum market 102. This interaction may include exchanging information related to the current situation in the spectrum requester, spectrum owner, and spectrum marketplace 102. The information from this exchange can then be provided to the core service module 106, which can use this information and historical or statistical information derived, for example, from the persistence module 114 to determine radio spectrum transaction transactions. Radio spectrum transaction transactions may involve the spectrum owner negotiating a spectrum requestor to temporarily lease an available radio spectrum (eg, for a specific time period or a specific amount of data). Subsequently, the radio spectrum transaction transaction determined by the core service module 106 can be provided to the management utility module 108 to perform radio spectrum transaction transactions (eg, to formalize the temporary delivery of usage rights to initiate payment, etc.), And to monitor spectrum requesters And the performance of the spectrum owner to ensure that the terms of the radio spectrum trading transaction are fulfilled.

The administrative management service 110 and the security 112 can serve as a "cross layer" that links the market communication module 104, the core service module 106 and the management utility module 108 together. These cross-layers provide administrative management of the entire spectrum management process to identify spectrum holders and verify the eligibility of spectrum requesters and spectrum holders to participate in the intermediary process. The administrative management service 110 and the security 112 can also facilitate the creation and execution of rules for managing how the CSMS 100 operates.

2 illustrates an example combination of devices 200 that may be utilized in accordance with at least one embodiment of the present disclosure. Apparatus 200 presents an example of a device that can be used to implement some or all of CSMS 100 as illustrated in FIG. For example, the CSMS 100 may be implemented partially or fully in a "cloud" assembly, including one or more of the modules illustrated in FIG. 1 that are accessible via a WAN (eg, the Internet). Servers, storage devices, network devices, and more. One or more cloud servers may, for example, include features such as those described with respect to device 200. Moreover, although some portions of CSMS 100 may be implemented in cloud provisioning, other portions may reside in different possible participants in spectrum marketplace 102. For example, some or all of the modules depicted in FIG. 1 may reside with a spectrum requestor and/or spectrum owner (eg, a wireless service provider), and a third party operator residing with CSMS 100, such as , private or government spectrum control agencies, etc. In addition, it is also possible to implement all aspects of the CSMS 100 on the same device 200. However, device 200 is only intended as an example of a device that is available in accordance with various embodiments consistent with the present disclosure, and is not intended to be Various embodiments are limited to any particular manner of implementing the scheme.

Device 200 can include a system module 202 that is assembled to operate as a general management device. The system module 202 can include, for example, a processing module 204, a memory module 206, a power module 208, a user interface module 210, and a communication interface module 212. The communication interface module 212 can be configured to The communication module 214 communicates. Device 200 can also include a CSMS 100' that is configured to interact with at least memory module 206 and communication module 214. Although CSMS 100' and communication module 214 are shown as being separate from system module 202, this is for purposes of explanation only. Some or all of the functionality associated with CSMS 100' and/or communication module 212 may also be incorporated into system module 202.

In apparatus 200, processing module 204 can include one or more processors in separate components, or can include one or more processing cores embedded in a single component (eg, embedded system single-chip (SOC)), And any processor related support circuitry (eg, bridge interface, etc.). Examples of processors may include x86-based microprocessors available from Intel Corporation, including Pentium, Xeon, Itanium, Celeron, Atom (Astro Boy), Core i-series (Core i series) product family. Examples of support circuits may include a set of wafers (e.g., Northbridge, Southbridge, etc., available from Intel Corporation), which are assembled to provide processing module 204 with which Interfaces for other system components in 200 that can operate at different speeds, on different bus bars, and the like. Some or all of the functionality typically associated with a support circuit may also be included in the same entity as the processor The package (for example, available from Intel Corporation's SOC package, similar to the Sandy Bridge integrated circuit).

Processing module 204 can be assembled to execute various instructions in device 200. The instructions can include code that is configured to cause the processing module 204 to perform activities related to reading data, writing data, processing data, formulating data, converting data, transforming data, and the like. Information (eg, instructions, materials, etc.) can be stored in the memory module 206. The memory module 206 can include random access memory (RAM) or read only memory (ROM) in a fixed or removable form. The RAM may include information that is assembled to hold during operation of device 200, such as, for example, static RAM (SRAM) or dynamic RAM (DRAM). The ROM may include memory that is configured to provide instructions when the device 200 is booted, such as bios (basic input and output system) memory, programmable memory such as electronically programmable ROM (EPROM), flash memory, and the like. Other fixed and/or removable memories may include magnetic memory such as floppy disks, hard disks, etc., electronic memory such as solid state flash memory (eg, embedded multimedia card (eMMC), etc.), removable In addition to memory cards or sticks (eg, micro-storage devices (uSD), USB, etc.), optical memory, such as compact disc-based ROM (CD-ROM), and the like. The power module 208 can include an internal power source (eg, a battery) and/or an external power source (eg, an electromagnetic or solar generator, a power grid, etc.), and a correlation that is assembled to supply the device 200 with the power required for operation. Circuit.

The user interface module 210 can include circuitry that is configured to allow a user to interact with the device 200, such as, for example, various input mechanisms (eg, microphones, switches, buttons, knobs, keyboards, speakers, touch-sensitive surfaces, via Combine to capture images and/or sense proximity, distance, motion, One or more sensors of gestures, etc.) and output mechanisms (eg, speakers, displays, illumination/flicker indicators, electromechanical components for vibration, motion, etc.). The communication interface module 212 can be configured to handle packet routing and other control functions of the communication module 214. The communication module 214 can include resources configured to support wired and/or wireless communication. Wired communications can include serial and side-by-side wired media such as, for example, Ethernet, Universal Serial Bus (USB), Firewire, Digital Visual Interface (DVI), High Definition Multimedia Interface (HDMI) ,and many more. Wireless communication can include, for example, near-nearline wireless media (eg, radio frequency (RF), such as near field communication (NFC) based standards, infrared (IR), optical character recognition (OCR), magnetic character sensing, etc. And so on, short-range wireless media (eg, Bluetooth, WLAN, Wi-Fi, etc.) and long-range wireless media (eg, cell areas, satellites, etc.). In an embodiment, the communication interface module 212 can be configured to prevent active wireless communication in the communication module 214 from interfering with each other. During the execution of this function, the communication interface module 212 can schedule the activity of the communication module 214 based on, for example, the relative priority of the messages awaiting transmission.

In an embodiment, CSMS 100' may include software and/or hardware that are assembled to include some or all of the functional elements depicted in FIG. Some of the functional elements illustrated in Figure 1 are also likely to be located in other devices that are configured to interact with the CSMS 100' via wired or wireless communication (e.g., in a decentralized or cloud topology). For example, CSMS 100' can interact with memory module 206 to store information in a database and retrieve information from a database, such as persistence module 114. In addition, the CSMS 100' can also communicate with the communication module 214 when communicating with the frequency market 102. Other CSMS 100' communications in the geographic area, and so on. Although not shown in FIG. 2, CSMS 100' may also interact with other modules in device 200, including, for example, interacting with processing module 204 to execute instructions associated with CSMS 100', interacting with user interface module 210 A command is received from the operator of CSMS 100' to display information related to CSMS 100' to issue visual/audible warnings, and the like.

FIG. 3 illustrates an example combination of a market communication module 104' in accordance with at least one embodiment of the present disclosure. The market communication module 104' can include a plurality of APIs that are configured to interact with the spectrum marketplace 102', as well as other components that are configured to monitor/process information received from such APIs. The spectrum switching API 310 can provide an interface to the spectrum switch 302 in the spectrum market 102' to update and/or maintain the state of the spectrum market 102'. For example, the spectrum switching API 310 can be dynamically linked with the operator of the CSMS 100 and the spectrum holders participating in the CSMS 100, performing backlash operations and payment management, and the like. The spectrum owner API 312 can provide an interface through which the spectrum owner 304 in the spectrum market 102' can communicate with the CSMS 100 (e.g., to lease the available radio spectrum to reclaim the leased radio spectrum, etc.). The Mediator-to-Mediator (B2B) API 314 may provide an interface through which the mediator 308 (e.g., including at least one other CSMS 100) in the spectrum marketplace 102' interacts with the CSMS 100. The Mediator-to-Network (B2N) API 316 can provide an interface through which the network management 306 in the spectrum market 102' can communicate with the CSMS 100. For example, B2N 316 may make it easier for CSMS 100 to communicate with other network components in the wireless network connection infrastructure covered by spectrum market 102'.

Request processor 318 can be used to process marketing communication module 104' Information received from APIs 310 through 316. For example, request processor 318 can receive a request from a spectrum requester looking for an available radio spectrum, from a frequency owner attempting to lease an available spectrum to receive a lease offer, from a spectrum having a leased spectrum, but now experiencing unintended demand The user recovers the leased spectrum and similar information from other intermediaries (eg, at least one other CSMS 100). In processing this information, request processor 318 can aggregate similar requests/offers, filter specific types of information, organize information for later processing, etc., depending on the type of information. Event processor 320 can monitor the information received by request processor 218 to look for specific events (e.g., trends, values, types of information, etc.). For example, event processor 318 can detect the growth of spectrum orders, detect triggers used to indicate increased order congestion, and the like. If an event is detected, the event processor 320 can, for example, cause certain functionality to occur in the CSMS 100 (e.g., to reduce congestion), cause an alert to be presented to the operator of the CSMS 100, and the like. The cloud controller 322 can communicate with the core service module 106. For example, cloud controller 322 can provide core service module 106 with information processed by request processor 318 and can request processing of radio spectrum transaction transactions.

4 illustrates an example combination of core service modules 106' in accordance with at least one embodiment of the present disclosure. The instant transaction engine 402 can be responsible for transactions in the radio spectrum where the spectrum requester matches the spectrum owner. In an embodiment, the radio spectrum may be traded in time frequency units (TFU). Determining the match between the spectrum requestor and the spectrum owner can be based on a number of criteria. In this regard, the instant transaction engine 400 can receive input from the analysis engine 402. Analysis engine 402 can include, for example, multi-target optimization engine 404 and cognitive engine 406. in In one embodiment, the multi-target optimization engine 404 can include one or more optimization algorithms used by the analysis engine 402 to achieve the goal of spectrum trading in the following aspects, for example, to maximize spectrum holders. Benefits, ensuring the quality and performance of spectrum lenders, maximizing frequency utilization and optimal allocation, and more. Such goals may be performed based on criteria such as, for example, radio context information, application requirements, device mobility models, wireless traffic requirements, power levels, spectrum availability, geographic locations, spectrum lease offers/requests, and the like. The cognitive engine 406 is also important to the operation of the analytics engine 402 because the cognitive engine 406 can be comprised of a collection of machine learning algorithms that use spectrum usage patterns and historical information in an attempt to predict and predict the use of the radio spectrum (eg, At a specific time, location, etc.). For example, video conferencing calls can be made in a regular manner (time and location), and the cognitive engine 406 can identify patterns of radio spectrum usage to help predict the allocation of radio spectrum required for a video call of the desired quality in a smooth and appropriate manner. .

Other elements of core service module 106' may provide useful information to analysis engine 403 to determine the best match between the spectrum requestor and the spectrum owner. For example, the matching engine 408 can help determine a match between TFUs available for transactions based on price (eg, bid and inquiry price) and geographic location of the available radio spectrum. The rules-based engine 410 can be responsible for establishing TFU transaction rules and mediation criteria to help develop an effective, customizable transaction and mediation system. The negotiating intermediary 412 can assist in selecting a policy (eg, selecting a policy from a selection of predetermined policies based on, for example, historical performance information). The strategy can specify how a particular bargaining situation can be automatically disposed, including, for example, the initial price /TFU offer, counter offer, offer acceptance, unfinished request disposal, and more. The TFU Distribution Engine 414 is operable to collect information relating to the settled transaction operations for the following aspects, such as the amount of available spectrum leased, the time period of the available spectrum, the price of the leased available spectrum/TFU, etc. . The TFU Distribution Engine 414 may also collect information relating to the leased available spectrum, including, for example, frequency bands, radio interfaces, power levels, etc., which may be communicated as part of the transaction to the entity that leased the spectrum (eg, The wireless service provider) to initiate the actual scheduling and distribution of the available spectrum. The spectrum transaction management engine 416 can collect, store, modify, retrieve radio spectrum transaction transactions and other operations, and thus, the spectrum transaction management engine 416 can interact with the management utility module 108. For example, the spectrum transaction management engine 416 can ensure that the transaction experience is consistent and atomic for all parties (eg, spectrum requesters and spectrum owners), and can also be arranged to "redo", where the lease is The spectrum is returned to the spectrum owner on a case-by-case basis, including, for example, the spectrum requestor's actions are not based on the terms of the radio spectrum transaction (eg, the leased spectrum is not paid, not used by the spectrum owner) The leased spectrum) or the spectrum owner needs to recover the spectrum (for example, due to unforeseen traffic increases, for urgent needs, etc.). The mediator-agent interface 418 can provide an interface to the core service module 106' to, for example, allow other mediators to determine transaction characteristics (e.g., for standardization, etc.).

Figure 5 illustrates an example assembly of a management utility module 108' in accordance with at least one embodiment of the present disclosure. Initially, the order management processor 500 can receive radio spectrum transaction transactions from the core service module 106. In one implementation In an example, the order management processor 500 can check the accuracy and/or error of the incoming radio spectrum transaction transaction. Subsequently, the settlement and billing engine 502 can be responsible for billing the appropriate entity (e.g., spectrum requester) for the leased spectrum and paying the revenue to the spectrum owner. The reporting engine 506 can report statistical information of the CSMS 100, including, for example, transaction amount, transaction type, amount of completed/re-transactions, geographic spectrum rental statistics, and the like. The monitoring engine 506 is operable to typically monitor the CSMS 100 and alert the operator of the CSMS 100 to any anomalies or problems with the system. The Service Level Agreement (SLA) Manager 510 can monitor completed radio spectrum transaction changes at least for both parties to comply with the agreed terms. SLA manager 510 can include, for example, SLA information manager 512 and SLA monitoring and control 514. The SLA Information Manager 512 can track the terms of the active radio spectrum transaction transaction. For example, the SLA information manager 512 can include settings for standardized terms, such as minimum start time, lease duration, rental frequency, rental geographic limits, power limits, and the like. Subsequently, SLA monitoring and control 514 can monitor the performance of both the spectrum requester and the spectrum owner to ensure that the terms are met. If the terms are not met, the SLA Monitoring and Control 514 can automatically take action, including, for example, sending a notification to the spectrum requester, the spectrum owner, and/or the operator of the CSMS 100, for the radio spectrum transaction transaction, and for the radio spectrum transaction. The transaction has made a refund, a suspension of the spectrum requester and/or the spectrum owner's transaction, and so on.

FIG. 6 illustrates an example assembly of the persistence module 112 in accordance with at least one embodiment of the present disclosure. Persistence module 112' may include one that is configured to store information related to transaction market 102 and radio spectrum transaction transactions. Or multiple databases. Although for purposes of explanation herein, FIG. 6 illustrates various example databases, various embodiments consistent with the present disclosure are not limited to such databases, and may include more or less databases that store other materials.

The market feed database 600 may include information regarding the status of the spectrum market 102, such as, for example, market status, market news, publication regarding availability of the radio spectrum, and the like. The TFU hook database 602 can include a snapshot of the allocation and/or de-allocation of the TFU (eg, instant). This information may allow the intermediary to have an instantaneous and accurate state of availability of the radio spectrum to be leased to the spectrum requestor or spectrum owner. The radio environment mapping database 604 can include domain environment information from cognitive radios (e.g., wireless radios capable of sensing information about the operation, environment, interference, etc. of the radio and capable of changing the operation of the radio). This information may include geographic features, available networks and services, spectrum policies and regulations, location and activity of adjacent/coming radios, experience, and more. The radio environment mapping database 604 can be used, for example, by the cognitive engine 406 to learn past experience, situational awareness, reasoning, and to predict the location of the appropriate channel for the end user. The cloud spectrum database 606 can include information about the spectrum availability for each of the available channels (eg, radio spectrum), usage of the channel schedule, coverage parameters, location (latitude and longitude), price per TFU, Maximum power level and spectrum grant (authorized or unauthorized). Geographic Information System (GIS) database 608 may include information about geographic features and/or boundaries, such as, for example, roads, railways, intersections, traffic conditions, and the like. This type of information is available to the analysis engine 402 because the available spectrum can be identified based on location and time. Enterprise Information System (EIS) database 610 captures information about radio spectrum transactions Historical information on changes, payments, orders, etc. The information in the EIS database 610 can be used, for example, to determine historical trends, predict performance, identify potential problem locations and/or times, perform system reports for the CSMS 100, and the like.

FIG. 7 illustrates example operations related to a cloud spectrum management system in accordance with at least one embodiment of the present disclosure. In operation 700, the CSMS can listen for spectrum requests. For example, the market communication module can interact with the spectrum market to self-see the spectrum requestor of the available radio spectrum and the spectrum owner who wants to lease the available radio spectrum or reclaim the leased radio spectrum to receive the request. These requests may be accumulated in operation 702 before the matching is performed in operation 704, where the spectrum request may match the available radio spectrum. Operation 704 can be performed by, for example, a core service module in the CSMS.

The matching performed in operation 704 may result in one or more radio spectrum transaction transactions, and the execution of the one or more radio spectrum transaction transactions may be supervised in operation 706. For example, in an embodiment, the management sharing in the CSMS ensures that the leased spectrum is reserved for the spectrum requestor and that the spectrum owner is compensated according to the terms of the radio spectrum transaction transaction. In operation 708, the radio spectrum transaction transaction may be monitored to ensure that the terms agreed upon by the party (eg, the spectrum requestor and the spectrum owner) are met. In operation 710, information related to the transaction may be stored in the persistence module. Operation 710 can be optional (eg, dashed lines) because whether the information is stored depends on whether a corresponding repository exists in the persistence module to accept the data. Operation 710 may then return to the optional return of operation 700 for preparation of the preparation of the additional spectrum request.

Radio spectrum trading

The following disclosure describes exemplary systems and methods for radio spectrum transactions that may be implemented, for example, using devices previously described above in connection with various embodiments consistent with the present disclosure. However, the following system level methods are not limited to implementations using only the devices presented above. References to any of the above features are for the purpose of explanation herein. In fact, systems and methods, such as the radio spectrum transactions described below, can be implemented using any combination of devices and software that can be combined to support the example functionality, operations, etc. disclosed below.

In general, the radio spectrum transaction may include a requester for determining a pool of available radio spectrum and a portion of the pool of available radio spectrum to be leased, and a system and method for allocating available spectrum to the requester. The pricing curve can be set based on historical information and/or requests from the requester regarding the leased spectrum. Subsequently, it can be determined that the amount of available spectrum is less than or greater than the amount of the requested spectrum. If it is determined that the amount of available spectrum is less than the amount of the requested spectrum, the available spectrum may be auctioned, where the initial bid is set based on the pricing curve. If it is determined that the amount of available spectrum is greater than the amount of the requested spectrum, the requestor may rank based on the revenue of the predicted amount to be generated by the request, and the available spectrum may be allocated from the highest to lowest order of the revenue generated.

In an embodiment, the example system can include at least a core service module to determine radio spectrum transaction transactions for use in translating radio frequency spectrum for wireless communication. The instance core service module can include an analysis engine and an instant transaction engine. The analysis engine can be used to set a pricing curve based, for example, on usage data. An instant trading engine can be used, for example, in view of the desire to rent The spectrum availability is determined by the spectrum request received by the requester of the spectrum, and the available spectrum is allocated based on the spectrum availability decision and pricing curve to satisfy the spectrum request.

When setting the pricing curve based on the usage data, the analysis engine can be used to determine whether the historical usage data is available, and if it is determined that the historical usage data is not available, the pricing curve is set based on the predetermined usage data. On the other hand, if the analysis engine determines that historical usage data is available, the analysis engine can be used to determine a future probability of receiving a spectrum request requesting at least one of a particular amount of spectrum or a particular lease duration based on historical usage. At least one of the data and the spectrum request. The analysis engine can then be further used to determine future revenue estimates based on future probabilities, and can continue to set pricing curves based on future revenue estimates.

The determination of the real-time transaction engine for spectrum availability may include the instant transaction engine determining whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. If it is determined that the amount of available spectrum is less than the amount of spectrum requested in the spectrum request, the instant transaction engine can further be used to allocate the available spectrum to satisfy the spectrum request by auctioning the available spectrum based on the bid submitted by the requester. The available spectrum can then be allocated based on the highest bid to the lowest bid received during the auction. In an embodiment, the instant transaction engine may be further configured to set an initial bid based on the lowest price determined based on the pricing curve plus an empirical gap value. Alternatively, if it is determined that the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request, the instant transaction engine may further be configured to allocate the available spectrum by assigning the available spectrum by sorting the spectrum request via the predicted revenue generation and ranking based on the ranking. To meet spectrum requests. For each The predicted return determined by a spectrum request can be based, for example, on at least a pricing curve. A method consistent with at least one embodiment of the present disclosure can include, for example, setting a pricing curve based on usage data that can be used to trade the spectrum of radio frequencies for wireless communication: in view of the requestor who wants to lease the available spectrum The spectrum availability is determined by the received spectrum request; and the available spectrum is allocated based on the spectrum availability decision and pricing curve to satisfy the spectrum request.

8, 10 and 12 through 13 describe example operations that may be covered within the matching of the spectrum request and available spectrum as set forth in operation 704. Initially, it is important to note that the example operations disclosed in Figures 8, 10, and 12 through 13 may correspond to various geographic regions. The characteristics of various geographic regions (eg, the number of wireless users, the number of wireless providers, the economic status of the user, the average charge for the provider to utilize, etc.) may be similar or different. Thus, the manner in which the operations disclosed in Figures 8, 10, and 12 through 13 may be performed may vary depending on the characteristics of the geographic region being served. For example, very different geographic areas may require independent processing. Therefore, the operations described in FIGS. 8, 10, and 12 to 13 can be performed individually on a region-by-region basis. Alternatively, if the region has very similar characteristics, a centralized processing scheme can be used to simultaneously process radio spectrum transactions for multiple regions (eg, some of the information used in the processing of shared spectrum shifts across multiple regions, similar to common pricing) curve).

FIG. 8 illustrates example operations related to radio spectrum transactions in accordance with at least one embodiment of the present disclosure. Figure 8 provides further details regarding the operations that may be covered when matching spectrum requests and available spectrum. The operations of the inverse (inverse) operations (eg, operations 800, 808, and 810) will be shown separately. Further explanations are given in 10, 12 and 13. In operation 800, a pricing curve can be set based on usage data. In general, the potential revenue that can be generated by the request can be determined based on the pricing curve, as well as setting the initial bid for radio spectrum auctions, and the like. In an embodiment, in operation 802, a pricing curve can be used to update the pricing. The pricing may be updated, for example, based on comparing existing spectrum market pricing (eg, global pricing or geographic area pricing) to a pricing curve and adjusting pricing accordingly.

After setting the pricing curve, in operation 804, the spectrum availability can be determined based on the request for the leased spectrum received from the requestor. For example, the amount of spectrum available to the spectrum owner for lease can be compared to the amount of spectrum requested in the lease request submitted by the requester (eg, the wireless service provider). In an embodiment, the request may include an amount of spectrum (eg, bandwidth), an amount of time (eg, a lease period) at which the spectrum is to be leased, and a bid. The amount of the total price, the time period (eg, per minute), the amount of conditions (eg, a higher bid for a specified bandwidth of the radio spectrum and/or a smaller amount of lease period for a smaller bandwidth and/or Or a shorter rental period) and so on to receive the bid. Subsequently, it is determined in operation 806 whether the amount of the requested spectrum is greater than the amount of available spectrum. If it is determined in operation 806 that the amount of requested spectrum is greater than the amount of available radio spectrum, then in operation 808, the available spectrum may be allocated based on the auction. For example, the price may be derived from the requestor based on the initial bid, which is determined based on the pricing curve, and the available spectrum may be allocated to the requester based on the highest to lowest bid. Alternatively, if it is determined in operation 806 that the amount of available spectrum is greater than the requested bandwidth, then in operation 810 the available frequencies may be allocated based on the predicted revenue generation for each request. For example, The revenue is predicted for each request and the available spectrum can be allocated based on the highest to lowest amount of predicted revenue.

Operation 808 or 810 may be followed by operation 812, where it may be further determined whether the previously leased spectrum has been reclaimed by the spectrum owner. For example, the lease terms may include situations in which, for example, a public emergency, high wireless communication requirements, or even just selection, the spectrum owner may reclaim the leased spectrum. In such an example, in operation 814, the lease agreement may be reversed (eg, the leased spectrum may be returned to the spectrum owner and/or the spectrum requestor may refund the fee). Subsequently, the inverse of the lease agreement may then return to operation 804 where it may be determined again whether there are more available spectrum or spectrum requests so that a new spectrum lease agreement may be scheduled for any requestor forced to abandon the previous spectrum lease.

Figure 9 illustrates an example instant transaction engine 400' and analysis engine 402' in accordance with at least one embodiment of the present disclosure. In an embodiment, the transaction engine 400' may be responsible for various actions including, but not limited to, processing spectrum requests and auction bids, continually allocating and/or retrieving spectrum, and using current usage information (eg, resource attributes, spectrum usage, utilization periods) , etc.) logging into the resource utilization database (eg, in the persistence module 112), determining the lowest rental price (eg, corresponding to different spectral frequencies, wherein the spectral frequency with higher demand may be compared to the lower demand frequency High base prices) and adjustment pricing, auctions, sequencing of spectrum based on projected earnings, and more. In performing the above example actions, the instant transaction engine 400' may receive spectrum availability information from the spectrum owner and a request to reclaim the leased spectrum, as well as receive spectrum requests and auction bids from the spectrum requester. In response, the instant transaction engine 400' can be frequency-oriented The spectrum owner provides notification that the spectrum has been returned, as well as providing the initial bid and bid update for the auction to the spectrum requester participating in the spectrum auction.

In at least one example implementation, the instant transaction engine 400' can include, for example, a core algorithm 900, a spectrum request queue 902, an auction engine 904, and a predicted revenue engine 906. The analysis engine 402' can include, for example, a statistics engine 908 and a pricing curve setting engine 910. Although the above-described elements constituting the instant transaction engine 400' and the analysis engine 402' have been separately illustrated, some or all of the elements 900-906 are also likely to be merged, and/or the elements 908-910 are also likely to be merged (eg, Depends on the combination of CSMS 100). In an embodiment, the core algorithm 900 may be a central engine that schedules the available spectrum to be distributed to the spectrum requestor. In this role, core algorithm 900 can access spectrum request queue 902 to determine pending spectrum requests. For example, a spectrum request may request a particular amount of spectrum (eg, S1) for a particular time period (eg, T1), and may include an amount of money (eg, bid B1) that the spectrum requestor is willing to pay. The core algorithm 900 can then determine how to allocate the available spectrum based on the amount of spectrum availability information received from the spectrum owner, based on the amount of spectrum requested. For example, if the amount of available spectrum is less than the amount of the requested spectrum, the core algorithm 900 can use the auction engine 904 to allocate the available spectrum, and if, on the other hand, if the amount of available spectrum is greater than the amount of the requested spectrum, The core algorithm 900 can then use the predictive revenue engine 906.

In another example, core algorithm 900 would require pricing information for determining an initial bid to start an auction for determining a predicted revenue based on a spectrum request received from a spectrum requestor, and the like. This information can be obtained from the pricing curve determined by the statistics engine 908 and/or the pricing curve setting engine 910. Got it. The statistics engine 908 can provide a learning mechanism by which the spectrum occupancy and utilization statistics of available resources (eg, available spectrum) can be determined. The utilization statistics may be based on historical usage information (e.g., may include previous "current usage information" stored by the instant transaction engine 400' in the persistence module 112) and pending requests in the spectrum request queue 902. The utilization statistics can be used by the pricing curve setting module to set the pricing curve using the operation, for example, as proposed in FIG.

FIG. 10 illustrates example operations related to setting a pricing curve based on usage data in accordance with at least one embodiment of the present disclosure. Figure 10 illustrates example operations that may be covered when setting a pricing curve based on usage data in operation 800'. Initially, it is determined in operation 1002 whether historical usage information is available. For example, historical usage information may include, but is not limited to, previous pricing curves, previously negotiated spectrum leases, previous wireless usage (eg, by region, by time period, by spectrum owner or spectrum requester, etc.), description Geographic maps for wireless traffic, and more. If it is determined in operation 1002 that no history usage information is available, the predetermined usage profile may be used in operation 1004 to set the pricing curve in operation 1006. The predetermined usage profile may be, for example, data for initializing the radio spectrum transaction system during startup, and may include usage information corresponding to another geographic area similar to the area in which the radio spectrum transaction system will operate, across a plurality of different regions Spectrum usage information, best guess prices based on the characteristics of geographic regions, and more.

If it is determined in operation 1002 that historical usage information is available, historical usage data may be obtained from a repository (eg, persistence module 112) in operation 1008, which may then be based on historical usage information and/or about renting in operation 1010. The current request is used to determine the probability of future use. The future usage probabilities may be related, for example, to the frequency of the available spectrum, the amount of available spectrum, and the predicted duration of the lease that is most popular among the spectrum requesters. Estimating future probability information helps predict which requests will likely become the most frequently requested lease requests. In operation 1012, a predicted future benefit can then be estimated based on future probabilities. Predicting future earnings allows the radio spectrum trading system to calibrate the pricing curve in operation 1006. In this way, revenue generation can be maximized by ensuring that the majority of the lease request can be completed by the system.

Figure 11 illustrates an example pricing curve in accordance with at least one embodiment of the present disclosure. Although FIG. 11 reveals an example pricing curve 1100, other shapes of pricing curves are possible depending on the pricing philosophy employed in the system. The example pricing curve 1100 is displayed in a three-dimensional axis describing the relationship between the amount of (required available spectrum), the duration of (spectral lease), and the price of (the leased spectrum). The lowest price per time frequency unit (TFU) is displayed at the center of area 1102. In the disclosed embodiment, if the amount becomes higher or lower, and if the duration becomes longer and shorter, the pricing on curve 1100 moves upward from the lowest price at the center of region 1102. Coordinating the pricing curve 1100 in this manner allows for a focus on maximizing the number of leases that fall within the region 1102 of the curve 1100 (eg, the future probability determined in FIG. 9 predicts the region in which the lease will be concentrated). Outside of zone 1102 (eg, zone 1104 or 1106), the price per TFU rises. In fact, areas 1104 and 1106 can be considered as "punishment" areas because the price per TFU is likely to rise, due to the amount of available spectrum requested and/or the duration of the lease being too small (eg, processing lease changes is economically Not feasible) or too large (for example, greedy because most The requester does not actually use the spectrum). Therefore, a requestor (e.g., a wireless service provider) that expects a minimum price per TFU will tend to focus on requests that fall into the zone 1102, which tends to maximize the revenue of the radio spectrum transaction.

Figure 12 illustrates example operations related to allocating a spectrum based on an auction in accordance with at least one embodiment of the present disclosure. After setting the pricing curve 1200 and determining that the requested bandwidth is greater than the available bandwidth, then example operations such as illustrated in FIG. 12 may be employed to allocate the spectrum based on the auction proposed in operation 808'. For example, in operation 1200, an initial bid for an auction may be set based on a pricing curve 1000. In an embodiment, the initial bid may be based on the lowest price per TFU plus a positive gap constant. The positive gap constant can be based, for example, on empirical observations of how bids were made in previous auctions. The auction timer may be reset in operation 1202 prior to starting the auction in operation 1204. In particular, the auction time may begin, and the bid may then be received in operation 1202 until it is determined in operation 1206 that based on the expiration of the auction timer and no time remaining.

After the expiration of the auction in operation 1206, the requested spectrum may be allocated to the next highest bidder in the auction (eg, the highest bidder, the next highest bidder) in operation 1208. The amount of available spectrum may be updated in operation 1210 before moving to the next highest bidder in operation 1212. The allocation of available spectrum can continue in this manner until all available spectrum has been allocated to the requestor or there are no more requesters to whom the spectrum is to be allocated (eg, available spectrum depletion is more likely because of the requested spectrum) The amount is greater than the available spectrum and is predicted to continue to operate 806').

Figure 13 illustrates example operations related to allocating a spectrum based on predicted revenue in accordance with at least one embodiment of the present disclosure. If it is determined in operation 804 that the amount of available spectrum is greater than the amount of the requested spectrum, then in operation 810', the available spectrum may be allocated based on the predicted revenue to, for example, maximize the revenue of the radio spectrum trading system. In operation 1300, requests for lease available spectrum may be ordered based on predicted revenue. The amount of revenue to be generated by the request can be predicted based on the pricing curve 1000. For example, a request for revenue falling within the region 1002 of the pricing curve 1000 yields more revenue because the requests maximize the use of the available spectrum that is predicted to be the most advantageous. Requests falling within the region 1004 or 1006 of the pricing curve 1000 may be penalized for inefficient use of the available spectrum and may therefore have lower predicted returns.

In operation 1302, the available spectrum may be allocated to complete the request for the available spectrum with the next highest predicted revenue value. For example, after the request with the highest predicted return is allocated, the request with the next highest predicted return can be allocated, and so on. The remaining available spectrum may then be updated in operation 1304 before the spectrum is allocated to the request with the next highest predicted return. Operations 1302 and 1304 may continue until it is determined in operation 1306 that all available spectrum has been allocated, or that all pending requests have been serviced. In this example, the probability of completing all spectrum requests before consuming the available spectrum is higher because there is more available spectrum at the original decision. However, if the spectrum owner reclaims the available spectrum, this situation will change, resulting in a reduction in the amount of available spectrum, and the number of requests may increase due to lease termination.

Although Figures 7, 10 and 11 through 12 illustrate operations in accordance with various embodiments, it will be appreciated that for other embodiments, Figures 7, 10 and 11 through 12 All operations depicted are not necessary. In fact, this document is fully covered: in other embodiments of the present disclosure, the operations depicted in Figures 7, 10, and 11 through 12 and/or other operations described herein may be combined in any manner not specifically shown in the drawings. However, it is still completely consistent with the content of this case. Therefore, a request for a feature and/or operation that is not explicitly shown in a drawing may be considered as falling within the scope and content of the present disclosure.

As used in any embodiment herein, the term "module" may be referred to as software, firmware, and/or circuitry that is configured to perform any of the operations described above. The software can be implemented as a software package, code, instructions, instruction set, and/or data recorded on a non-transitory computer readable storage medium. The firmware can be implemented as a code, an instruction or a set of instructions and/or a hard code (non-electrical) data in the memory device. As used in any embodiment herein, a "circuit" can include, for example, a hardwired circuit in a single or any combination, a programmable circuit, state, such as a computer processor including one or more individual instruction processing cores. A machine circuit, and/or a firmware that stores instructions that can be programmed to execute the circuit. Modules can be implemented in total or individually as circuits that form part of a larger system, such as integrated circuits (ICs), system-on-a-chip (SoC), desktops, laptops, tablets, servers , smart phones, and so on.

Any of the operations described herein can be implemented in a system including one or more storage media that are stored individually or in combination with execution methods executed by one or more processors. Instructions. Herein, the processor may include, for example, a server CPU, a mobile device CPU, and/or other programmable circuitry. Additionally, it is contemplated that the operations described herein may be distributed across multiple physical devices, such as in more than one The processing structure at the same physical location. The storage medium may include any type of tangible media, such as any type of disc, including hard discs, floppy discs, compact discs, CD-ROMs, CD-RWs, and magneto-optical discs. Semiconductor devices such as read-only memory (ROM), random access memory (RAM) such as dynamic and static RAM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, solid state disk (SSD), embedded multimedia card (eMMC), secure digital input/output (SDIO) card, magnetic or optical card, or any type of media suitable for storing electronic instructions. Other embodiments may be implemented as a software module executed by a programmable control device.

Therefore, the content of this case is for radio spectrum transactions. Radio spectrum transactions involve determining the available radio spectrum and the requestor who wants to lease a portion of the available radio spectrum; and allocating the available spectrum to the requester. The pricing curve can be set based on historical information and/or requests for leased spectrum. Subsequently, it can be determined that the amount of available spectrum is less than or greater than the amount of the requested spectrum. If it is determined that the amount of available spectrum is less than the amount of the requested spectrum, then the available spectrum is auctioned, with the initial bid being set based on the pricing curve. If it is determined that the amount of available spectrum is greater than the amount of the requested spectrum, the requests may be ordered based on the predicted revenue generation, and the available spectrum may be allocated in descending order of the resulting revenue.

The following examples pertain to other embodiments. In an example, a system is provided. The system can include: a core service module to determine a radio spectrum transaction transaction for use in trading a radio frequency spectrum for wireless communication, the core service module including at least an analysis engine to set based on usage data A pricing curve; and an instant transaction engine that determines spectrum availability in view of spectrum requests received from a requestor that wants to lease available spectrum, and allocates available spectrum to satisfy spectrum requests based on spectrum availability decisions and pricing curves.

The above example system may be further configured, wherein the analysis engine sets the pricing curve based on the usage data including: the analysis engine determines whether the historical usage data is available, and if it is determined that the historical usage data is not available, the pricing curve is set based on the predetermined usage data. In this assembly, the example system can be further configured, wherein if the historical usage data is determined to be available, the analysis engine determines a future probability of receiving a spectrum request requesting at least one of a particular amount of spectrum or a particular lease duration, The future probability determination is based on at least one of the historical usage data and the spectrum request, further determining the future revenue estimate based on the future probability, and setting the pricing curve based on the future revenue estimate.

The above example system may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine determines that the spectrum availability comprises: the instant transaction engine determines whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. . In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be less than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The instant transaction engine is based on the request. The bids are submitted to auction the available spectrum, and the available spectrum is allocated based on the highest bid to the lowest bid received during the auction. In this assembly, the instance system can be further assembled, wherein the real-time trading engine is further based on the lowest determined according to the pricing curve The initial bid is set by the price plus the experience gap value. In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The predicted revenue is generated while the spectrum requests are ordered and the available spectrum is allocated based on the ranking. In this assembly, the example system can be further assembled, wherein the predicted return for each spectrum request is determined based at least on the pricing curve.

The above example systems may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine includes at least one of a core algorithm, a spectrum request queue, an auction engine, and a predictive revenue engine.

In another example, a method is provided. The method can include: setting a pricing curve based on usage data, the pricing curve can be used to trade a spectrum of radio frequencies for wireless communication; determining spectrum availability in view of a spectrum request received by a requestor that wants to lease available spectrum; and based on spectrum The availability decision and pricing curve are assigned to the available spectrum to satisfy the spectrum request.

The above example method may be further configured, wherein setting the pricing curve based on the usage data includes determining whether the historical usage data is available, and if it is determined that the historical usage data is not available, using the predetermined usage data to set the pricing curve. In this combination, the example method can further include determining, if the historical usage data is available, a future probability of receiving a spectrum request including at least one of a particular amount of spectrum or a particular lease duration, the future probability being based on history Use at least one of the data and the spectrum request Decision; determine future revenue estimates based on future probabilities; and set pricing curves based on future revenue estimates.

The above example methods may be further assembled independently or in combination with other combinations above, wherein determining spectrum availability includes determining whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. In this combination, the example method can further include: if the amount of available spectrum is determined to be less than the amount of spectrum requested in the spectrum request, auctioning the available spectrum based on the bid submitted by the requestor; and based on the highest received during the auction period The available spectrum is allocated by bidding to the minimum bid. In this combination, the example method can further include setting an initial bid based on the lowest price determined based on the pricing curve plus an empirical gap value. In this combination, the example method can further include: if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, the spectrum request is ordered by the predicted revenue generation; and the available spectrum is allocated based on the ranking. In this combination, the example methods can be further assembled, wherein the predicted return is determined for each spectrum request based at least on the pricing curve.

In another example, a system is provided that includes at least a core service module configured to perform any of the above-described example methods.

In another example, a wafer set configured to perform any of the above example methods is provided.

In another example, at least one machine readable medium is provided, the medium comprising a plurality of instructions that, in response to execution on a computing device, cause the computing device to perform any of the example methods described above.

In another example, an apparatus is provided for use in radio spectrum transactions, the apparatus being configured to perform any of the example methods described above.

In another example, a system is provided having a component that performs any of the above-described example methods.

In another example, a system is provided. The system can include: a core service module to determine a radio spectrum transaction transaction for use in trading a radio frequency spectrum for wireless communication, the core service module including at least an analysis engine to set a pricing curve based on usage data; and an instant transaction The engine determines the spectrum availability in view of the spectrum request received from the requestor that wants to lease the available spectrum, and allocates the available spectrum to satisfy the spectrum request based on the spectrum availability decision and pricing curve.

The above example system may be further configured, wherein the analysis engine sets the pricing curve based on the usage data, including: the analysis engine determines whether the historical usage data is available, and if it is determined that the historical usage data is not available, the pricing curve is set based on the predetermined usage data, and if Determining a historical usage profile, determining a future probability of receiving a spectrum request requesting at least one of a particular amount of spectrum or a particular lease duration, the future probability determination being based on at least one of a historical usage profile and a spectrum request; The future earnings estimate is determined by future probabilities; and the pricing curve is set based on future earnings estimates.

The above example system may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine determines that the spectrum availability comprises: the instant transaction engine determines whether the amount of available spectrum is greater than the spectrum request The amount of spectrum requested in . In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be less than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The instant transaction engine is based on the request. The available spectrum is auctioned for the bid submitted, the initial bid for the auction is based on the lowest price determined based on the pricing curve plus the experience gap value; and the available spectrum is allocated based on the highest bid to the lowest bid received during the auction. In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The spectrum requests are ordered based on at least the predicted revenue generation of the pricing curve and the available spectrum is allocated based on the ranking.

The above example systems may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine includes at least one of a core algorithm, a spectrum request queue, an auction engine, and a predictive revenue engine.

In another example, a method is provided. The method can include: setting a pricing curve based on usage data, the pricing curve can be used to trade a spectrum of radio frequencies for wireless communication; determining spectrum availability in view of a spectrum request received by a requestor that wants to lease available spectrum; and based on spectrum The availability decision and pricing curve are assigned to the available spectrum to satisfy the spectrum request.

The above example method may be further configured, wherein setting a pricing curve based on usage data includes: determining whether historical usage data is available; If it is determined that the historical usage data is not available, the predetermined usage profile is used to set the pricing curve, and if the historical usage profile is determined to be available, then the future probability of receiving the spectrum request including at least one of the specific spectral amount or the specific lease duration is determined, The future probability is determined based on at least one of historical usage data and a spectrum request; future revenue estimates are determined based on future probabilities; and a pricing curve is set based on future revenue estimates.

The above example methods may be further assembled independently or in combination with other combinations above, wherein determining spectrum availability includes determining whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. In this combination, the example method can further include: if it is determined that the amount of available spectrum is less than the amount of spectrum requested in the spectrum request, auctioning the available spectrum based on the bid submitted by the requestor, the initial bid is based on the pricing curve The lowest price determined plus the experience gap value; and the available spectrum is allocated based on the highest bid to the lowest bid received during the auction. In this combination, the example method can further include: if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, ordering the spectrum request by at least based on the predicted revenue generation of the pricing curve; and based on the ranking The available spectrum is allocated.

In another example, a wafer set configured to perform any of the above example methods is provided.

In another example, at least one machine readable medium is provided, the medium comprising a plurality of instructions that, in response to execution on a computing device, cause the computing device to perform any of the example methods described above.

In another example, a provision is provided for use in radio frequency A system of spectral transactions configured to perform any of the above example methods.

In another example, a system is provided having a component that performs any of the above-described example methods.

In another example, a system is provided. The system can include: a core service module to determine a radio spectrum transaction transaction for use in trading a radio frequency spectrum for wireless communication, the core service module including at least an analysis engine to set a pricing curve based on usage data; and an instant transaction The engine determines the spectrum availability in view of the spectrum request received from the requestor that wants to lease the available spectrum, and allocates the available spectrum to satisfy the spectrum request based on the spectrum availability decision and pricing curve.

The above example system may be further configured, wherein the analysis engine sets the pricing curve based on the usage data including: the analysis engine determines whether the historical usage data is available, and if it is determined that the historical usage data is not available, the pricing curve is set based on the predetermined usage data. In this assembly, the example system can be further configured, wherein if the historical usage data is determined to be available, the analysis engine determines a future probability of receiving a spectrum request requesting at least one of a particular amount of spectrum or a particular lease duration, The future probability determination is based on at least one of historical usage data and spectrum requests; determining future revenue estimates based on future probabilities; and setting pricing curves based on future revenue estimates.

The above example system may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine determines that the spectrum availability comprises: the instant transaction engine determines whether the amount of available spectrum is greater than the spectrum request The amount of spectrum requested in . In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be less than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The instant transaction engine is based on the request. The available spectrum is auctioned for the bid submitted by the bid; and the available spectrum is allocated based on the highest bid to the lowest bid received during the auction. In this assembly, the example system can be further assembled, wherein the instant transaction engine further sets the initial bid based on the lowest price determined based on the pricing curve plus the empirical gap value. In this assembly, the instance system can be further configured, wherein if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, the instant transaction engine allocates the available spectrum to satisfy the spectrum request. The predicted revenue is generated while the spectrum requests are ordered and the available spectrum is allocated based on the ranking. In this assembly, the example system can be further assembled, wherein the predicted return for each spectrum request is determined based at least on the pricing curve.

The above example systems may be further assembled independently or in combination with other combinations above, wherein the instant transaction engine includes at least one of a core algorithm, a spectrum request queue, an auction engine, and a predictive revenue engine.

In another example, a method is provided. The method can include: setting a pricing curve based on usage data, the pricing curve can be used to trade a spectrum of radio frequencies for wireless communication; determining spectrum availability in view of a spectrum request received by a requestor that wants to lease available spectrum; and based on spectrum The availability decision and pricing curve are assigned to the available spectrum to satisfy the spectrum request.

The above example method may be further configured, wherein setting the pricing curve based on the usage data includes determining whether the historical usage data is available, and if it is determined that the historical usage data is not available, using the predetermined usage data to set the pricing curve. In this combination, the example method can further include determining, if the historical usage data is available, a future probability of receiving a spectrum request including at least one of a particular amount of spectrum or a particular lease duration, the future probability being based on history Determining using at least one of the data and the spectrum request; determining a future revenue estimate based on future probabilities; and setting a pricing curve based on future revenue estimates.

The above example methods may be further assembled independently or in combination with other combinations above, wherein determining spectrum availability includes determining whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. In this combination, the example method can further include: if the amount of available spectrum is determined to be less than the amount of spectrum requested in the spectrum request, auctioning the available spectrum based on the bid submitted by the requestor; and based on the highest received during the auction period The available spectrum is allocated by bidding to the minimum bid. In this combination, the example method can further include setting an initial bid based on the lowest price determined based on the pricing curve plus an empirical gap value. In this combination, the example method can further include: if the amount of available spectrum is determined to be greater than the amount of spectrum requested in the spectrum request, the spectrum request is ordered by the predicted revenue generation; and the available spectrum is allocated based on the ranking. In this combination, the example methods can be further assembled, wherein the predicted return is determined for each spectrum request based at least on the pricing curve.

In another example, a system is provided. The system can include: a component for setting a pricing curve based on usage data, the pricing curve being usable for trading a spectrum of radio frequencies for use in wireless communications; means for determining spectrum availability in view of a spectrum request received by a requestor that desires to lease available spectrum; And means for allocating available spectrum to satisfy spectrum requests based on spectrum availability decisions and pricing curves.

The above example system may be further configured, wherein setting a pricing curve based on usage data includes: means for determining that historical usage data is available; and means for setting a pricing curve using predetermined usage data if it is determined that historical usage data is not available . In this combination, the above example system can further include: means for determining, if the historical usage data is available, determining a future probability of receiving a spectrum request including at least one of a particular amount of spectrum or a particular lease duration, The future probability determination is based on at least one of historical usage data and spectrum requests; means for determining future revenue estimates based on future probabilities; and means for setting pricing curves based on future revenue estimates.

The above example systems may be further assembled independently or in combination with other combinations above, wherein determining spectrum availability includes means for determining whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum request. In this combination, the example system can further include: means for auctioning the available spectrum based on the bid submitted by the requestor if the amount of available spectrum is less than the amount of the requested spectrum in the spectrum request; and for A component that allocates the available spectrum from the highest bid received during the auction to the lowest bid. In this combination, the example system can further include: for setting the initial based on the lowest price determined according to the pricing curve plus the empirical gap value The component that starts the bid. In this combination, the example system can further include: means for ordering the spectrum request by the predicted revenue generation if the amount of available spectrum is greater than the amount of the spectrum requested in the spectrum request; and for A component that sorts and allocates available spectrum. In this assembly, the example system can be further assembled, wherein the predicted return for each spectrum request is determined based at least on the pricing curve.

The terms and expressions used herein are used to describe the terms and are not intended to be limiting, and the use of such terms and expressions are not intended to exclude any equivalents of the features (or parts of the features) shown and described. It should be recognized that various modifications are possible within the scope of the patent application. Therefore, the scope of the patent application is intended to cover all such equivalents.

100‧‧‧Cloud Spectrum Management System (CSMS)

102‧‧‧Spectrum market

104‧‧‧Marketing Communication Module

106‧‧‧ Core Service Module

108‧‧‧Manage utility module

110‧‧‧Administrative services

112‧‧‧Security/Persistent Module

114‧‧‧Permanent modules

Claims (19)

A system for radio spectrum transactions, comprising: a core service module for determining a radio spectrum transaction transaction, the radio spectrum transaction transaction for transacting a spectrum of radio frequencies for use by wireless communication, The core service module includes at least: an analysis engine for setting a pricing curve based on the usage data, wherein: when the historical usage data is available, the analysis engine is configured to: determine whether the request for a specific spectrum amount or a specific lease continues to be received a future probability of a spectrum request for at least one of the times based on the historical usage data and at least one of the spectrum requests; determining a future revenue estimate based on the future probability; and based on the future revenue Estimating and setting the pricing curve; and when determining that the historical usage data is unavailable, the analysis engine is configured to set the pricing curve based on the predetermined usage data; and an instant transaction engine for requesting to lease the available spectrum Determine the spectrum availability by the spectrum request received by And for allocating available spectrum based on the spectrum availability decision and the pricing curve to satisfy the spectrum requests. The system of claim 1, wherein the instant transaction engine is operative to determine that the spectrum availability comprises: the instant transaction engine to determine whether the amount of available spectrum is greater than the amount of spectrum requested in the spectrum requests. The system of claim 2, wherein if the amount of the available spectrum is determined to be less than the amount of the spectrum requested in the spectrum request, the instant transaction engine is configured to allocate the available spectrum to satisfy the spectrum request: the instant The transaction engine is configured to auction the available spectrum based on bids submitted by the requestors and to allocate the available spectrum based on one of the highest bids received during the auction to a minimum bid. The system of claim 3, wherein the instant transaction engine is further configured to set an initial bid based on a lowest price determined from the pricing curve plus an experience gap value. The system of claim 2, wherein if the amount of the available spectrum is determined to be greater than the amount of the spectrum requested in the spectrum request, the instant transaction engine is configured to allocate the available spectrum to satisfy the spectrum request: the instant The transaction engine is operative to order the spectral requests by predicting the generation of revenue and to allocate the available spectrum based on the ranking. The system of claim 5, wherein determining the predicted return for each spectrum request is based at least on the pricing curve. The system of claim 1, wherein the instant transaction engine comprises at least one of a core algorithm, a spectrum request queue, an auction engine, and a predictive revenue engine. A method for radio spectrum trading, comprising: setting a pricing curve based on usage data, the pricing curve being usable for trading a spectrum of radio frequencies for wireless communication, wherein the pricing curve is set based on usage data: The historical usage data is a usable determination to determine a future probability of receiving a spectrum request including at least one of a particular amount of spectrum or a particular lease duration, the future probability being based on the historical usage data and at least one of the spectrum requests And determining; determining a future revenue estimate based on the future probability; and setting the pricing curve based on the future revenue estimates; and determining that the historical usage data is unavailable, using the predetermined usage data to set the pricing curve; The spectrum availability is determined by renting a spectrum request received by a requestor of the available spectrum; and the available spectrum is allocated based on the spectrum availability decision and the pricing curve to satisfy the spectrum request. The method of claim 8, wherein determining the spectrum availability comprises determining whether the amount of available spectrum is greater than the amount of the spectrum requested in the spectrum requests. The method of claim 9, further comprising: if the amount of the available spectrum is determined to be less than the request in the spectrum request The amount of the spectrum is sought, the available spectrum is auctioned based on the bids submitted by the requestors; and the available spectrum is allocated based on one of the highest bids received during the auction to a minimum bid. The method of claim 10, further comprising: setting an initial bid based on a lowest price determined from the pricing curve plus an experience gap value. The method of claim 9, further comprising: if the amount of the available spectrum is determined to be greater than the amount of the spectrum requested in the spectrum requests, ordering the spectrum requests by generating a predicted yield; and based on the ranking The available spectrum is allocated. The method of claim 12, wherein determining the predicted return for each spectral request is based at least on the pricing curve. A medium comprising one or more non-transitory machine-readable storage media having instructions stored thereon, individually or in combination, that when executed by one or more processors results in the following operations, such operations Include: setting a pricing curve based on the usage data, the pricing curve can be used to trade a spectrum of radio frequencies used for wireless communication, wherein the pricing curve is set based on the usage data: the response history usage data is available for determination, and the determination is Receiving a future probability of a spectrum request including at least one of a particular amount of spectrum or a particular lease duration, The future probability is determined based on the historical usage data and at least one of the spectrum requests; the future revenue estimate is determined based on the future probability; and the pricing curve is set based on the future revenue estimates; and the historical usage data is returned For the determination of unavailability, the predetermined usage profile is used to set the pricing curve; the spectrum availability is determined in view of the spectrum request received by the requester who wants to lease the available spectrum; and the available spectrum is allocated based on the spectrum availability determination and the pricing curve To meet these spectrum requests. The medium of claim 14, wherein the determining the spectrum availability comprises instructions executed by the one or more processors to cause an operation comprising: determining whether the amount of available spectrum is greater than the amount of the spectrum requested in the spectrum requests. . The medium of claim 15 further comprising instructions executed by the one or more processors to cause an operation comprising: determining that the amount of available spectrum is less than the amount of the spectrum requested in the spectral requests, The available spectrum is auctioned based on the bids submitted by the requestors; and the available spectrum is allocated based on one of the highest bids received during the auction to a minimum bid. The medium of claim 16, further comprising executing by one or more processors The instructions result in the operation of setting an initial bid based on a lowest price determined from the pricing curve plus an experience gap value. The medium of claim 15 further comprising instructions executed by the one or more processors to cause an operation comprising: determining that the amount of available spectrum is greater than the amount of the spectrum requested in the spectrum requests, Then, the spectrum requests are ordered by predicting the generation of the revenue; and the available spectrum is allocated based on the ranking. The medium of claim 18, wherein the predicted revenue is determined for each spectrum request based at least on the pricing curve.