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 -means clustering and sparsity adaptive matching pursuit (SAMP). In particular, the support of the NB-IoT signal is first estimated coarsely by -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.
Cite
@article{arxiv.2110.02515,
title = {A Sparsity Adaptive Algorithm to Recover NB-IoT Signal from Legacy LTE Interference},
author = {Yijia Guo and Wenkun Wen and Peiran Wu and Minghua Xia},
journal= {arXiv preprint arXiv:2110.02515},
year = {2021}
}
Comments
5 pages, 7 figures, to appear in IEEE Wireless Communications Letters