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In bi-static Ambient Backscatter Communications (AmBC) systems, the receiver needs to operate at a large dynamic range because the direct path from the ambient source to the receiver can be several orders of magnitude stronger than the scattered path modulated by the AmBC device. In this paper, we propose a novel analog-digital hybrid null-steering beamformer which allows the backscatter receiver to detect and decode the weak AmBC-modulated signal buried in the strong direct path signals and the noise, without requiring the instantaneous channel state information. The analog cancellation of the strong signal components allows the receiver automatic gain control to adjust to the level of the weak AmBC signals. This hence allows common analog-to-digital converters to be used for sampling the signal. After cancelling the strong components, the ambient source signal appears as zero mean fast fading from the AmBC system point of view. We use the direct path signal component to track the phase of the unknown ambient signal. In order to avoid channel estimation, we propose AmBC to use orthogonal channelization codes. The results show that the design allows the AmBC receiver to detect the backscatter binary phase shift keying signals without decoding the ambient signals and requiring knowledge of the instantaneous channel state information.
|Title of host publication||2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings|
|Publication status||Published - 1 May 2019|
|MoE publication type||A4 Article in a conference publication|
|Event||IEEE International Conference on Communications Workshops - Shanghai, China|
Duration: 20 May 2019 → 24 May 2019
|Conference||IEEE International Conference on Communications Workshops|
|Abbreviated title||ICC Workshops|
|Period||20/05/2019 → 24/05/2019|
- Ambient backscatter
- Hybrid analog-digital beamformer
- Low-power receiver
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- 2 Finished
AIMHIS: Collaborative Research: Ambient Re-Scatter inspired Machine Type Communications for Heterogeneous IoT Systems
Jäntti, R. & Duan, R.
12/04/2017 → 31/12/2019
Project: Academy of Finland: Other research funding