System and method for reduction of cost of ownership for wireless communication networks
First Claim
1. A method of reducing a total cost of ownership for a wireless telecommunications core network, the method comprising:
- determining, by a computer system, an optimal core wireless network evolution plan for a network planning period;
determining, by the computer system, an optimal core wireless network equipment count for supporting a first amount of wireless network traffic; and
determining, by the computer system, an optimal core wireless network configuration for supporting the first amount of wireless network traffic, wherein the total cost of ownership includes capital expenditures, operational cost, customer acquisition and retention (CAR) cost, and staffing and engineering cost, and wherein the CAR cost is based on unsupported traffic and inter-system handovers.
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Abstract
Systems and methods to assist wireless telecom service providers to determine the optimal core network evolution plan in a network planning time period. Total cost of ownership of wireless core networks is generally modeled to include capital expenditure, customer acquisition and retention cost, network operational cost and staffing and engineering cost. The total cost of ownership model is used to determine the optimal core network evolution plan at different layers of the core networks, which are modeled as a number of abstract networks in mathematical terms. A core network evolution optimization algorithm determines the optimal number of core network configurations and when to deploy the configurations in the planning period in order to minimize the total cost of ownership. A multi-level serving area optimization algorithm determines an optimal core network configuration at a given point of time.
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Citations
24 Claims
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1. A method of reducing a total cost of ownership for a wireless telecommunications core network, the method comprising:
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determining, by a computer system, an optimal core wireless network evolution plan for a network planning period; determining, by the computer system, an optimal core wireless network equipment count for supporting a first amount of wireless network traffic; and determining, by the computer system, an optimal core wireless network configuration for supporting the first amount of wireless network traffic, wherein the total cost of ownership includes capital expenditures, operational cost, customer acquisition and retention (CAR) cost, and staffing and engineering cost, and wherein the CAR cost is based on unsupported traffic and inter-system handovers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A method of reducing a total cost of ownership for a wireless telecommunications core network, the method comprising:
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determining, by a computer system, an optimal core wireless network evolution plan for a network planning period; determining, by the computer system, an optimal core wireless network equipment count for supporting a first amount of wireless network traffic; and determining, by the computer system, an optimal core wireless network configuration for supporting the first amount of wireless network traffic, wherein the total cost of ownership includes capital expenditures, operational cost, customer acquisition and retention (CAR) cost, and staffing and engineering cost, and wherein the staffing and engineering cost for the core network is based on network node re-parenting efforts involved in transactions between network configurations.
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23. A method of reducing a total cost of ownership for a wireless telecommunications core network, the method comprising:
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determining, by a computer system, an optimal core wireless network evolution plan for a network planning period; determining, by the computer system, an optimal core wireless network equipment count for supporting a first amount of wireless network traffic; determining, by the computer system, an optimal core wireless network configuration for supporting the first amount of wireless network traffic; and determining, by a multi-level serving area optimization, a minimal core network equipment count for supporting predicted network traffic at any given time during the network planning period, wherein the multi-level serving area optimization splits the wireless core network into a number of abstract networks, each for a core network level, where a network node is a node in the abstract network, traffic demands from the network node are node weights in the abstract network, a network node adjacency between two adjacent network nodes is an edge in the abstract network, mobility between adjacent network nodes is an edge weight in the abstract network, and a serving area is a sub-network in the abstract network.
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24. A method of reducing a total cost of ownership for a wireless telecommunications core network, the method comprising:
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determining, by a computer system, an optimal core wireless network evolution plan for a network planning period; determining, by the computer system, an optimal core wireless network equipment count for supporting a first amount of wireless network traffic; determining, by the computer system, an optimal core wireless network configuration for supporting the first amount of wireless network traffic; and determining, by a multi-level serving area optimization, a minimal core network equipment count for supporting predicted network traffic at any given time during the network planning period, wherein the multi-level serving area optimization is based on the determined optimal core network equipment count, and wherein the multi-level serving area optimization generates a sequence of network models based on the wireless core network, the optimization comprising (a) generating an network model by combining adjacent nodes in each serving area in the wireless core network; (b) determining whether traffic demand on each node of the network model is over a selected fraction of a capacity of equipment for a serving area in which the node is located; and (c) repeating the generating the network model and the determining the traffic demand until the traffic demand on each node is over the selected fraction.
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Specification