Abstract: In an embodiment, a method for determining a MIMO mode for a wireless communication system includes providing input parameters, an electronic device determining a probability of each MIMO mode being a dominant MIMO mode; and selecting the MIMO mode based on the determining.

Abstract: A system and method for cooperative spectrum sensing in cognitive radio (CR) systems is provided. A method for CR user operation includes coordinating with partner CR users to share spectrum sensing information, combining spectrum sensing information from partner CR users, and determining if a transmission opportunity exists based on the combined spectrum sensing information. The method also includes transmitting a message to a CR user if the transmission opportunity exists, and storing the message if the transmission opportunity does not exist.

Abstract: A system and method for probability-based resource allocation in a wireless communications system is provided. A method for centralized resource allocation includes coordinating spectrum sensing information with a set of cognitive radio (CR) user pairs, computing probability-based information for CR user pairs in the set of CR user pairs, computing adjustment values for each channel available for allocation, assigning a CR user pair to an unassigned channel in a set of channels available for allocation, the assigning based on the probability-based information, updating the adjustment values, repeating the assigning a CR user pair and the updating the adjustment values if the adjustment values have not converged, and transmitting a message to the set of CR user pairs, wherein the message comprises information regarding CR user pair to channel assignments.

Abstract: A system and method for rehome sequencing optimization of a telecommunications network. In a preferred embodiment, a practicable optimized rehome sequencing plan is determined for a rehome plan in order to migrate the network topology from an initial state to a final state while minimizing the costs incurred during the network state transitions across multiple time periods. Constraints that may be considered include specific market restrictions such as the limit on the number of network elements in a cluster, the limit on the number of clusters in a sequencing step, the limit on the number of sequencing steps, and the immobility limit on the network elements. Constraints also may include cost restrictions incurred during network transitions, such as individual cost limits during each network transition state and an overall cost limit of network transitions from the initial state to the final state.

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.