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Cognitive backscattering, an integration of cognitive radio and backsattermodulation, is emerging as a potential candidate for green Internet of Things(IoT). In cognitive backscatter systems, the backscatter device (BD) shares notonly the same spectrum, but also the same radio-frequency (RF) source with thelegacy system. In this paper, we investigate the signal transmission problem,in which a basic transmission model is considered which consists of K RFsources, one BD and one reader equipped with M antennas. A non-cooperativescenario is considered, where there is no cooperation between the legacysystems and the backscatter system, and no pilots are transmitted from the RFsources or BD to the reader. The on-off keying differential modulation isadopted to achieve noncoherent transmission. Firstly, through the capacityanalyses, we point out that high-throughput backscatter transmission can beachieved when the number of the receive antennas satisfies M>K. The ChernoffInformation (CI) is also derived to predict the detection performance. Next, weaddress the signal detection problem at the reader. The optimal soft decision(SD) and suboptimal hard decision (HD) detectors are designed based on themaximum likelihood criterion. To tackle the non-cooperation challenge, a fullyblind channel estimation method is proposed to learn the detection-requiredparameters based on clustering. Extensive numerical results verify theeffectiveness of the proposed detectors and the channel estimation method. Inaddition, it is illustrated that the increase of K may not necessarily lead toperformance degradation when multiple receive antennas are exploited.

Noncoherent Multiantenna Receivers for Cognitive Backscatter System with Multiple RF Sources