A Sparsity Adaptive Algorithm to Recover NB-IoT Signal from Legacy LTE Interference
Abstract
As a forerunner in 5G technologies, Narrowband Internet of Things (NB-IoT) will be inevitably coexisting with the legacy Long-Term Evolution (LTE) system. Thus, it is imperative for NB-IoT to mitigate LTE interference. By virtue of the strong temporal correlation of the NB-IoT signal, this letter develops a sparsity adaptive algorithm to recover the NB-IoT signal from legacy LTE interference, by combining $K$-means clustering and sparsity adaptive matching pursuit (SAMP). In particular, the support of the NB-IoT signal is first estimated coarsely by $K$-means clustering and SAMP algorithm without sparsity limitation. Then, the estimated support is refined by a repeat mechanism. Simulation results demonstrate the effectiveness of the developed algorithm in terms of recovery probability and bit error rate, compared with competing algorithms.
- Publication:
-
arXiv e-prints
- Pub Date:
- October 2021
- DOI:
- 10.48550/arXiv.2110.02515
- arXiv:
- arXiv:2110.02515
- Bibcode:
- 2021arXiv211002515G
- Keywords:
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- Computer Science - Information Theory;
- Electrical Engineering and Systems Science - Signal Processing
- E-Print:
- 5 pages, 7 figures, to appear in IEEE Wireless Communications Letters