Self-interference cancellation

Résumé

Self-interference cancellation (SIC) is a signal processing technique that enables a radio transceiver to simultaneously transmit and receive on a single channel, a pair of partially-overlapping channels, or any pair of channels in the same frequency band. When used to allow simultaneous transmission and reception on the same frequency, sometimes referred to as “in-band full-duplex” or “simultaneous transmit and receive,” SIC effectively doubles spectral efficiency. SIC also enables devices and platforms containing two radios that use the same frequency band to operate both radios simultaneously. Self-interference cancellation has applications in mobile networks, the unlicensed bands, cable TV, mesh networks, the military, and public safety. In-band full-duplex has advantages over conventional duplexing schemes. A frequency division duplexing (FDD) system transmits and receives at the same time by using two (usually widely separated) channels in the same frequency band. In-band full-

Source officielle

https://en.wikipedia.org/wiki/Self-interference_cancellation

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

Alexios Konstantinos Balatsoukas Stimming, Andreas Peter Burg, Yann Kurzo

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.

IEEE2018

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Hardware Implementation of Neural Self-Interference Cancellation

Alexios Konstantinos Balatsoukas Stimming, Andreas Peter Burg, Andreas Toftegaard Kristensen, Yann Kurzo

In-band full-duplex systems can transmit and receive information simultaneously and on the same frequency band. However, 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 describe a hardware architecture for a neural network-based non-linear self-interference (SI) canceller and we compare it with our own hardware implementation of a conventional polynomial based SI canceller. Our results show that, for the same SI cancellation performance, the neural network canceller has an 8.1x smaller area and requires 7.7x less power than the polynomial canceller. Moreover, the neural network canceller can achieve 7 dB more SI cancellation while still being 1.2x smaller than the polynomial canceller and only requiring 1.3x more power. These results show that NN-based methods applied to communications are not only useful from a performance perspective, but can also lead to order-of-magnitude implementation complexity reductions.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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Full-duplex wireless communication offers improved spectral efﬁciency, as well as more efﬁcient relaying and medium access, but requires suppression of self-interference. In this paper we analyze the existing methods for active RF suppression and use the ”Rice architecture” for its low complexity and favorable scaling when applied to multi-antenna systems. We analyze the effects of the different sources of self-interference and quantify the potential for further suppression (genie-aided suppression). Our single-chain implementation using a circulator achieves −48 dB of active RF suppression, but only −66 dB of total suppression in the analog domain. On the other hand, our single-chain implementation using separate antennae reaches −85 dB of total analog suppression, thus reducing the self-interference to the noise ﬂoor. Extending these setups, we present a low complexity implementation of a 2 × 2 full-duplex MIMO node, which achieves even higher suppression than the single-chain counterparts.

2013

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