In the scenario of the coexistence of long term evolution (LTE) system using orthogonal frequency division multiplexing (OFDM) and narrowband Internet-of-Things (NB-IoT), when the in-band model is used, the narrowband interference caused by NB-IoT will seriously degrade the performance of OFDM. Meanwhile, the phase noise (PHN) generated by the local oscillators also reduce the reliability of OFDM transmission. In this letter, an algorithm of jointly eliminating NB-IoT interference and PHN is proposed within the sparse Bayesian learning framework for OFDM system, when the channel noise follows non-Gaussian distribution. An iterative solution is derived after the optimization structure is constructed. Simulation results demonstrate that the gain of proposed method over the conventional methods is approximately 1.5-3.5 dB when the bit error rate is ${10^{-3}}$ .

中文翻译：

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OFDM系统中相位噪声和NB-IoT干扰的共同抵消

在使用正交频分复用（OFDM）和窄带物联网（NB-IoT）的长期演进（LTE）系统共存的情况下，当使用带内模型时，由NB引起的窄带干扰物联网将严重降低OFDM的性能。同时，本地振荡器产生的相位噪声（PHN）也降低了OFDM传输的可靠性。在这封信中，当信道噪声遵循非高斯分布时，在OFDM系统的稀疏贝叶斯学习框架内，提出了一种共同消除NB-IoT干扰和PHN的算法。构建优化结构后，得出迭代解。仿真结果表明，当误码率达到10％时，所提出的方法相对常规方法的增益约为1.5〜3.5 dB。 $ {10 ^ {-3}} $ 。