Design and Implementation of a Neural Network Aided Self Interference Cancellation Scheme for Full-Duplex Radios

In-band full-duplex systems are able to transmit and receive information simultaneously on the same frequency band. Due to the strong self-interference caused by the transmitter to its own receiver, the use of non-linear digital self interference cancellation is essential. In this work, we present a hardware architecture for a neural network based non-linear self-interference canceller and we compare it with our own hardware implementation of a conventional polynomial based canceller. We show that, for the same cancellation performance, the neural network canceller has a significantly higher throughput and requires fewer hardware resources.


Published in:
2018 Conference Record Of 52Nd Asilomar Conference On Signals, Systems, And Computers, 589-593
Presented at:
52nd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct 28-Nov 01, 2018
Year:
Jan 01 2018
Publisher:
New York, IEEE
ISSN:
1058-6393
ISBN:
978-1-5386-9218-9
Keywords:
Laboratories:




 Record created 2019-06-18, last modified 2020-04-20


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