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arXiv · 2110.02515

A Sparsity Adaptive Algorithm to Recover NB-IoT Signal from Legacy LTE Interference

Yijia Guo·Wenkun Wen·Peiran Wu·Minghua Xia
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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.

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Yijia Guo, Wenkun Wen, Peiran Wu, Minghua Xia. 2021-10-06. A Sparsity Adaptive Algorithm to Recover NB-IoT Signal from Legacy LTE Interference. https://arxiv.org/abs/2110.02515

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