Efficient Parallel Testing and Tuning of Beamforming MIMO Wireless Systems
There has been a revolution in the use of multiple-input multiple-output (MIMO) wireless communication systems over the last decade. It is expected that mobile data traffic will increase by up to 1000X by 2020 as compared to 2010. Future 5G wireless systems (communication data rates > 50Gbps) will deploy massive MIMO systems with large numbers of transmit and receive antennas and novel RF transceiver architectures that admit RF beamforming. Research on 5G massive MIMO systems is moving forward at an electrifying pace. It will be possible to point electromagnetic beams towards moving targets while simultaneously communicating at extremely high speeds and minimizing interference with other users. Downloading a high definition film will be possible in less than a second. However, with the dramatically increasing levels of circuit complexity and higher operating speeds, the underlying electronics will be highly susceptible to manufacturing process variations, electrical degradation and defects. At high data rates of communication, the effects of device non-idealities on RF system performance can be dramatic. Power consumption will be a major issue since a large number of transmitter and receiver chains will be involved. Such massive MIMO systems will need to be tested extensively and tuned for quality prior to sale. In the extreme, such systems will need to possess built-in self-testing and self-tuning capability to automatically compensate for field wear and tear due to electrical, thermal and mechanical stress.
The first problem to solve is efficient low-cost manufacturing production test of a range of MIMO systems with the capacity to handle 5G systems with 10-100 RF chains. State of the art test methods require that test signals to individual RF chains have frequency separation for the individual RF chain non-linearities to be assessed independent of nonlinearities in other chains. Conversely, given a set of frequencies that can be generated, only a certain maximum number of RF chains can be tested in parallel. A key goal is to design "frequency-efficient" tests and back-end response analysis algorithms that do not require such frequency separation allowing large numbers of RF chains to be tested in parallel. A second key goal is parallel gain and phase tuning of as many RF chains as possible using intelligent testing and response-analysis algorithms. One way to speed up the tuning procedure is to use the parallel testing procedure described above, to perform parallel tuning of the MIMO system well. Such parallel tuning can be supported by machine learning algorithms that predict the best tuning knob configurations for each chain based on specific time and frequency domain response features extracted from parallel testing techniques. To enable testing and tuning, high-speed signals need to be captured and analyzed for signal fidelity. To this end, the use of proposed incoherent undersampling for acquisition of test response signals provides a significant avenue for reducing testing costs by significantly simplifying the hardware required for high-speed device testing and characterization. Overall, the use of the proposed techniques will allow massive MIMO systems to be tested and tuned, post-manufacture and in the field, without the need for complex test instrumentation in 10s of ms test time, significantly reducing test cost while increasing product yield and field reliability.
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