Cloud based spectrum management analytics

Abstract

A system and method are provided for implementing a spectrum management analytics (SMA) algorithm that references a plurality of enumerated inputs to generate a set of output parameters for use in attempting to optimize spectrum. The SMA algorithm is a part of a cloud spectrum broker (CSB) analytic. The CSB analytic provides for:(1) Managing CSS transactions involving transfer of spectrum resources from participating primary spectrum holders (PSH's) to one or more alternate spectrum holders (ASH's);(2) Reclaiming spectrum resources from an ASH back to the corresponding PSH on request;(3) Initiating queries to PSH's based on requests from MMD's, or through other ASH's; and(4) Performing a series of predictive resource allocations that may optimize spectrum use as the MMD moves between a number of regions.

Description

[0001]This application claims priority to U.S. Provisional Patent Application No. 61 / 603,261, entitled “Intelligent Spectrum Allocation Based on User Behavior Patterns For Efficient Spectrum Usage,” filed on Feb. 25, 2012. This application is related to co-pending International Patent Application Nos. (Attorney Docket Nos. P43616PCT and P43618PCT), filed on the same day as this application, the disclosures of which are hereby incorporated by reference herein in their entirety.BACKGROUND[0002]1. Field of the Disclosed Embodiments[0003]This disclosure relates to systems and methods for implementing a spectrum management analytics (SMA) algorithm as part of an automated cloud spectrum broker (CSB) to provide spectrum management for networks using spectrum allocated through a Dynamic Spectrum Access (DSA) scheme that allows spectrum holders, or a proxy assigned to manage a given allocation of spectrum, to temporarily “rent” access to the spectrum they hold to other entities.[0004]2. Rel...

AI Technical Summary

Benefits of technology

[0019]A challenge in achieving an efficient and scalable DSA scheme that becomes economically viable is effective spectrum management. In other words, given the temporary lease of spectrum to different operators or users, in different locations, for different time periods, a challenge resides in determining how best to coordinate the leasing of the spectrum so that the spectrum brokering scheme maximizes: (1) the incentive for the ASH's; (2) the incentive for the PSH's and (3) experience for the user / operator that is paying for that spectrum (ideally, with minimal cost), all while avoiding interference and assuring the PSH that its spectrum is recoverable on demand. This is an optimization problem that lends itself to the use of computational analytics. Currently, there are no known global spectrum management schemes with computational analytics across networks employing DSA. While mobile cellular network operators do make use of spectrum management within their own networks, there is no cross-network, or cross-operator, spectrum management between potential ASH's. Today, with spectrum exclusively licensed, there has been no push for a large scale spectrum management. However, with future spectrum exhaustion of their exclusively-licensed spectrum expected by carriers, the larger pool of rented spectrum provides a greater pool of spectrum resources from which to optimize utilization, i.e., optimization would no longer be limited to just the local spectrum resources of each individual carrier.

Problems solved by technology

As the increase in demand for wireless data access continues, the world is headed toward a global spectrum shortage.

If solutions are not found, users of wireless devices will frustratingly experience increased instances of dropped calls and slow data speeds all while paying higher fees for access to the scarce resource that will be the wireless data and voice communication spectrum.

A cursory review of the breakdown of the licensed spectrum for any particular geographic area reveals that the availability of new spectrum to support the assignment of additional exclusive licenses to any particular licensee is nearly exhausted.

As mobile cellular network communication traffic continues its dramatic increase, congestion occurs today and the congestion problem is forecast to rise significantly in coming years in the portions of the spectrum currently licensed to mobile cellular network operators to support wireless voice and data communications.

Regardless of these efforts, however, the pipe will never get any bigger due to the fixed, finite spectrum covered by licenses.

The above efforts may delay the inevitable.

There will still come a time, however, when the currently licensed portions of the spectrum that support commercial mobile voice and data communications will become overburdened.

Often these methods reduce the quality of service experienced by individual customers.

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