The University of South Carolina is offering licensing opportunities for Methods and Procedures for Synchronization and Over-the-Air Computation
Over-the-air computation (OAC) reduces the communication latency that linearly increases with the number of devices in a wireless network for machine learning applications. Despite its merit, an OAC scheme may require the radios to start their transmissions synchronously with high accuracy, which can impose stringent requirements for the underlying mechanisms. On the other hand, when software-defined radios (SDRs) are used as radios for this application, synchronization is hard to maintain.
The disclosed synchronization method and procedures enable an SDR-based network to realize OAC for machine-learning applications in a reliable way.
In a practical network, time synchronization can be maintained via an external timing reference such as the Global Positioning System (GPS), a triggering mechanism as in IEEE 802.11, or well-designed synchronization procedures over random-access and control channels as in cellular networks. However, while using a GPS-based solution can be costly and unsuitable for indoor applications, the implementations of trigger-based synchronization or some synchronization protocols may not be self-sufficient. This is because an entire baseband besides the synchronization blocks may need to be implemented as a hard-coded block to satisfy the timing constraints. On the other hand, when a software-defined radio (SDR) is used as an I/O peripheral connected to a companion computer (CC) for flexible baseband processing, the transmission/reception instants are subject to a large jitter due to the underlying protocols (e.g., USB, TCP/IP) for the communication between the CC and the SDR. Hence, it is not trivial to use SDRs to test an OAC scheme in practice. Also, the procedures for over-the-air computation are needed and it is not actually clear how it will work in a practical network. This invention addresses these challenges.
Advantages and Benefits:
The proposed synchronization method enables low-cost SDR to be time-synchronous without using GPS or some additional circuitry. The proposed procedures enable over-the-air computation in practice by describing the alignment, calibration, and computation signals. The market size is large as it is related to both commercial wireless and AI technologies. It could be useful for artificial intelligence technologies over wireless or sensor networks, 5G and beyond, 6G wireless standardization, IEEE 802.11 Wi-Fi. Also, Recently, IEEE 802.11 has formed a Topic Interest Group (TIG), where distributed learning over a wireless network has been mentioned.