This technology implements a time-segmented quadrature analog-to-information converter (TS-QAIC) for rapid detection of up to six interferers.
Future 5G/next-G networks will require a tremendous increase in network wireless data traffic capacity. Emerging cognitive radio (CR) or 5G/next-G technologies like LTE-LAA and LTE-U will employ under-utilized unlicensed spectrum in addition to designated licensed spectrum, with network operators directing data traffic between the two. Knowing the instantaneous interference conditions in the unlicensed bands is key to managing the spectrum allocation of the LTE-LAA/LTE-U terminal and ensuring harmonious coexistence with WiFi and other devices in unlicensed spectrum. Future smart devices operating in small cell environments will need to rapidly detect a few strong interferers within roughly a 1GHz span and accordingly request adjustments to their wireless connection.
This technology is a time-segmented quadrature analog-to-information converter (TS-QAIC) that is capable of detecting up to 6 interferers in less than 11us within a 1GHz-wide span. The TS-QAIC maintains the advantages in power consumption and sensitivity of band pass compressed sampling approaches, and is also able to detect twice the number of interferers with the same number of physical branches. The TS-QAIC implements virtual extension of physical hardware through time segmentation and adaptive thresholding, enabling system scaling in multiple dimensions to meet user performance goals like number of detectable interferers, energy consumption and scan time while limiting silicon cost and complexity. Rapid detection of interferers enabled by the TS-QAIC could have a significant impact on increasing data traffic capacity on 5G/next-G networks.
A demonstration of the TS-QAIC architecture has verified the enhanced capabilities of this technology.
IR CU16078
Licensing Contact: Greg Maskel
