Abstract
We present a distributed nullforming algorithm where a set of transmitters transmit at full power to minimize the received power at a designated receiver. Each transmitter adjusts the phase and frequency of its transmitted RF signal in a purely distributed fashion as it uses only an estimate of its own channel gain to the receiver, and a feedback signal from the receiver, that is common across all the transmitters. This assures its scalability; in contrast any noniterative approach to the nullforming problem requires that each transmitter know every other transmitter’s channel gain. We prove that the algorithm practically, globally converges to a null at the designated receiver. By practical convergence we mean that the algorithm always converges to a stationary trajectory, and though some of these trajectories may not correspond to a minimum, those that do not are locally unstable, while those that do are locally stable. Unlike its predecessors the paper does not assume prior frequency synchronization among the transmitters, but asymptotically secures frequency consensus.
This work was partly supported by US NSF grants CNS-1239509, CAREER award ECCS-1150801, and CCF-1302456, and ONR grant N00014-13-1-0202.
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Dasgupta, S., Mudumbai, R., Kumar, A. (2018). Feedback Control for Distributed Massive MIMO Communication. In: Tempo, R., Yurkovich, S., Misra, P. (eds) Emerging Applications of Control and Systems Theory. Lecture Notes in Control and Information Sciences - Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-67068-3_7
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