MLE-based Device Activity Detection for Grant-free Massive Access under Frequency Offsets

Liu, Wang; Cui, Ying; Yang, Feng; Ding, Lianghui; Xu, Jiyong; Xu, Xingchen

doi:10.1109/icc45855.2022.9838874

Cited by 4 publications

(9 citation statements)

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“…We also analytically compare the computational complexities of the two iterative algorithms. Note that the proposed algorithms successfully generalize the MLE-based methods for Rayleigh fading in the time asynchronous case [22] and frequency asynchronous case [25].…”

Section: Introductionmentioning

confidence: 82%

“…GROUP LASSO [21], and an MLE-based method [22], respectively. For the frequency asynchronous case, [23] deals with joint device activity detection and channel estimation using norm approximation, and [24] and [25] handle device activity detection using MLE-based methods. For the time and frequency asynchronous case, [26] investigates joint device activity detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system using an AMP-based method.…”

Section: Introductionmentioning

confidence: 99%

“…For the time and frequency asynchronous case, [26] investigates joint device activity detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system using an AMP-based method. The optimization problems in [21]- [25] are solved using the majorizationminimization method [23], CD method [24], and block coordinate descent (BCD) method [21], [22], [25]. Notice that most existing works [21], [23], [24], [26] incur much higher computational June 13, 2023 DRAFT complexities than those for the synchronous case, especially at a large range of offset values.…”

Section: Introductionmentioning

confidence: 99%

“…Notice that most existing works [21], [23], [24], [26] incur much higher computational June 13, 2023 DRAFT complexities than those for the synchronous case, especially at a large range of offset values. To address this issue, our early work [25] proposes a low-complexity algorithm to solve the MLE problem for the frequency asynchronous case under Raleigh fading using the BCD method and fast Fourier transform (FFT).…”

Section: Introductionmentioning

confidence: 99%

“…Hence, Rician fading (including both LoS components and non-line-of-sight (NLoS) components), which includes Rayleigh fading (with only NLoS components) as a special case, can be applied to a wider variety of wireless communications systems than Rayleigh fading. Although device activity detection and channel estimation methods proposed for Rayleigh fading in [7]- [9], [22], [25] can be applied to Rician fading in a brute force manner, the resulting performance may significantly degrade.…”

Section: Introductionmentioning

confidence: 99%

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MLE-based Device Activity Detection for Grant-free Massive Access under Rician Fading

Liu

Cui

Yang

et al. 2022

2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)

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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. Specifically, 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 the notable gains of the proposed algorithms over existing methods in detection accuracy and computation time.

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Section: Introductionmentioning

confidence: 82%