To achieve, when a common-channel signal of a public switched telephone network is connected to an IP network, the automation of the operation of allocating logical links for accommodating the common-channel signal, and thus increase the efficiency of the operation of a continuity test and the like. A link management device with a special function is connected to the IP network, and the link management device controls a process of establishing a link between an IP converter device and a signal transfer point (IP-STP). The IP converter device transmits a request including a point code to the link management device, and the link management device determines the IP address and the like of the signal transfer point as a connection destination from the received point code. The link management device transmits information for identifying the signal transfer point to the IP converter device, and also transmits information for identifying the IP converter device to the signal transfer point as the connection destination. The port number of the IP converter device is determined by the link management device or the IP converter device. The port number of the signal transfer point is determined by the link management device or the signal transfer point.

The disclosed wireless transmitter estimates a client location in space and transmits power in the form of electromagnetic (EM) waves to that location. In response to receiving the power, a client sends a power request signal. In some implementations, the power request signal includes a request that the wireless transmitter transmit more power to the client. In response to the power request signal, the wireless transmitter can modify the power transmitted to the client to increase/decrease the amount of power the client is receiving. For example, the wireless transmitter can modify the emitted EM waves to increase coherent addition or decrease coherent addition at the location of the client to increase the amount of power the client receives. In some implementations, the wireless transmitter modifies the phase distribution of EM waves to increase the amount of power a client receives.

Undesirable signalling traffic received at a telecommunications network is detected by establishing at least one statistical parameter in respect of signalling traffic received at the telecommunications network from at least one specific source and evaluating the established at least one statistical parameter against one or more predetermined statistical profiles.

Systems and methods for adapting traditional landline telephones to make and receive Voice over Internet Protocol (VoIP) calls and other communications are described. In some embodiments, an adapter, adaptor, or other device or apparatus connects an IP router, such as a WiFi router or other access point, to a traditional landline telephone (e.g., a phone using dual-tone multi-frequency, or DTMF, signaling), enabling the traditional landline phone to make and/or receive VoIP calls.

Systems and methods for adapting traditional landline telephones to make and receive Voice over Internet Protocol (VoIP) calls and other communications are described. In some embodiments, an adapter, adaptor, or other device or apparatus connects an IP router, such as a WiFi router or other access point, to a traditional landline telephone (e.g., a phone using dual-tone multi-frequency, or DTMF, signaling), enabling the traditional landline phone to make and/or receive VoIP calls.

A method in which a high-quality packet telephony terminal apparatus performing low-latency and lossless packet communication with a counterpart packet telephony terminal apparatus operates in an integrated network structure in which a time sensitive network (TSN) and a packet communication network are combined may be disclosed. The packet telephony terminal apparatus may perform packet telephony call processing, perform a TSN stream reservation procedure when the counterpart packet telephony terminal apparatus is capable of performing a TSN function for lossless packet communication, adjust a size of a dejitter buffer when the TSN stream reservation procedure is successful, and perform low-latency packet telephony communication through the minimized size of the dejitter buffer.

Herein are machine learning (ML) techniques for unsupervised training with a corpus of signaling system 7 (SS7) messages having a diversity of called and calling parties, operation codes (opcodes) and transaction types, numbering plans and nature of address indicators, and mobile country codes and network codes. In an embodiment, a computer stores SS7 messages that are not labeled as anomalous or non-anomalous. Each SS7 message contains an opcode and other fields. For each SS7 message, the opcode of the SS7 message is stored into a respective feature vector (FV) of many FVs that are based on respective unlabeled SS7 messages. The FVs contain many distinct opcodes. Based on the FVs that contain many distinct opcodes and that are based on respective unlabeled SS7 messages, an ML model such as a reconstructive model such as an autoencoder is unsupervised trained to detect an anomalous SS7 message.

Herein are machine learning (ML) techniques for unsupervised training with a corpus of signaling system 7 (SS7) messages having a diversity of called and calling parties, operation codes (opcodes) and transaction types, numbering plans and nature of address indicators, and mobile country codes and network codes. In an embodiment, a computer stores SS7 messages that are not labeled as anomalous or non-anomalous. Each SS7 message contains an opcode and other fields. For each SS7 message, the opcode of the SS7 message is stored into a respective feature vector (FV) of many FVs that are based on respective unlabeled SS7 messages. The FVs contain many distinct opcodes. Based on the FVs that contain many distinct opcodes and that are based on respective unlabeled SS7 messages, an ML model such as a reconstructive model such as an autoencoder is unsupervised trained to detect an anomalous SS7 message.

Systems, methods and computer software are disclosed for providing a Service Bus for telecommunications infrastructure. The services bus provides a communications system between mutually interacting software applications, including a plurality of microservices, each microservice comprising: an internal bus; a data store in communication with the internal bus; a data access object in communication with the internal bus; a message exchange object in communication with the internal bus; a MAPReduce engine in communication with the internal bus; and a restful Application Programming Interface (API) bus in communication with the data access object, the message exchange object and the MAPReduce engine. The Service Bus provides a messaging service, a synchronization service and a persistence service, and routes messages between services, monitors and controls routing of message exchange between servers, resolves contention between communicating service components, controls deployment and versioning of services, marshals use of redundant services, and provides commodity services.

Herein are machine learning (ML) techniques for unsupervised training with a corpus of signaling system 7 (SS7) messages having a diversity of called and calling parties, operation codes (opcodes) and transaction types, numbering plans and nature of address indicators, and mobile country codes and network codes. In an embodiment, a computer stores SS7 messages that are not labeled as anomalous or non-anomalous. Each SS7 message contains an opcode and other fields. For each SS7 message, the opcode of the SS7 message is stored into a respective feature vector (FV) of many FVs that are based on respective unlabeled SS7 messages. The FVs contain many distinct opcodes. Based on the FVs that contain many distinct opcodes and that are based on respective unlabeled SS7 messages, an ML model such as a reconstructive model such as an autoencoder is unsupervised trained to detect an anomalous SS7 message.