MLE-based Device Activity Detection under Rician Fading for Massive Grant-free Access with Perfect and Imperfect Synchronization
CoRR(2023)
摘要
Most existing studies on massive grant-free access, proposed to support
massive machine-type communications (mMTC) for the Internet of things (IoT),
assume Rayleigh fading and perfect synchronization for simplicity. However, in
practice, line-of-sight (LoS) components generally exist, and time and
frequency synchronization are usually imperfect. This paper systematically
investigates maximum likelihood estimation (MLE)-based device activity
detection under Rician fading for massive grant-free access with perfect and
imperfect synchronization. We assume that the large-scale fading powers, Rician
factors, and normalized LoS components can be estimated offline. We formulate
device activity detection in the synchronous case and joint device activity and
offset detection in three asynchronous cases (i.e., time, frequency, and time
and frequency asynchronous cases) as MLE problems. In the synchronous case, we
propose an iterative algorithm to obtain a stationary point of the MLE problem.
In each asynchronous case, we propose two iterative algorithms with identical
detection performance but different computational complexities. In particular,
one is computationally efficient for small ranges of offsets, whereas the other
one, relying on fast Fourier transform (FFT) and inverse FFT, is
computationally efficient for large ranges of offsets. The proposed algorithms
generalize the existing MLE-based methods for Rayleigh fading and perfect
synchronization. Numerical results show that the proposed algorithm for the
synchronous case can reduce the detection error probability by up to 50.4
78.6
the proposed algorithms for the three asynchronous cases can reduce the
detection error probabilities and computation times by up to 65.8
respectively, compared to the MLE-based state-of-the-arts.
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关键词
Massive grant-free access,device activity detection,Rician fading,synchronization,time offset,frequency offset,maximum likelihood estimation (MLE),fast Fourier transform (FFT)
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