Abstract: The principal object of the embodiments herein is to disclose predictive capacity analysis and pro-active performance bottleneck identification using multivariate machine learning techniques for efficient network capacity expansion and optimization to enhance customer experience by improving quality of service (QoS) while ensuring better return of investment (ROI).

Abstract: A computer network data center includes a persistent storing device storing raw data from an external data source, a multi-core parallel modelling system coupled to the persistent storing device, and a gateway server coupled to the persistent storing device as a reverse firewall. In operation, the raw data in the persistent storing device is not erased, altered or destroyed. The multi-core parallel modelling system processes the raw data to provide anonymized information for an external user device. The gateway server has a communication channel for secure communication with external devices but prevents access to the raw data stored in the persistent storing device by the external devices.

Abstract: A system, method, and computer program product are provided for probabilistic estimation and prevention of muting occurrence in VoLTE. In operation, a system estimates a muting probability associated with a current state of a newly initiated call between calling user equipment (UE) and called UE by computing a muting contribution per interface between the calling UE and the called UE utilizing a muting probability estimation algorithm. Further, the system determines possible corrective actions to be performed specific to the current call state utilizing a correlation algorithm for prevention of muting occurrences.

Abstract: A system, method, and computer program product are provided for failure avoidance due to Discontinuous Reception (DRX) configuration issues. In operation, a system checks DRX parameters for preventing non-compliant DRX parameters in an eNodeB (eNB) and performs autocorrection of non-compliant to compliant DRX parameters. The DRX parameters may be checked by the eNB or by any OEM. The system also identifies a cause of reconfiguration failure by user equipment (UE).

Abstract: A system, method, and computer program product are provided for smart inter-Radio Access Technology (IRAT) Voice over Long-Term Evolution (VoLTE) mobility. In operation, a serving cell receives an indication of poor coverage from user equipment (UE) during an active call. The serving cell determines to initiate an inter-Radio Access Technology (IRAT) handover process if the coverage for the UE has become worse than a threshold value. The serving cell identifies at least one parameter (e.g. CovTriggerdBlindHoAllowed) indicating a conditional state in which selection between a measurement-based handover and a blind-based handover for the IRAT handover process is based on a critical condition threshold. The serving cell selects between the measurement-based handover and the blind-based handover for the IRAT handover process, as a result of identifying the conditional state of the parameter.

Abstract: A system, method, and computer program product are provided for mitigation of user-specific ping-pong handover. In operation, user equipment (UE) monitors for a ping-pong handover scenario between the UE and a plurality of nodes in a wireless communication network. The UE determines whether a state of the UE is static, if it is determined that the UE is experiencing a ping-pong handover scenario. The UE receives a deferred measurement time indicator from a best serving node of the plurality of nodes, if it is determined that the state of the UE is static. The UE defers sending a measurement report to the plurality of nodes for a time-period associated with the deferred measurement time indicator.