Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access

@article{Wang2022TwoStageCE,
  title={Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access},
  author={Xinhua Wang and Alexei E. Ashikhmin and Zhicheng Dong and Chao Zhai},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2022},
  volume={40},
  pages={1428-1440}
}
We investigate the activity detection and channel estimation issues for cell-free Internet of Things (IoT) networks with massive random access. In each time slot, only partial devices are active and communicate with neighboring access points (APs) using non-orthogonal random pilot sequences. Different from the centralized processing in cellular networks, the activity detection and channel estimation in cell-free IoT is more challenging due to the distributed and user-centric architecture. We… 
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SHOWING 1-10 OF 26 REFERENCES

Device Activity and Embedded Information Bit Detection Using AMP in Massive MIMO

TLDR
The proposed approach is inspired by the approximate message passing (AMP) and demonstrates a superior performance compared to the original AMP approach and the numerical analysis reveals that the performance of the proposed approach scales with number of devices, which makes it suitable for user detection in cellular networks with massive number of Devices.

Massive Connectivity With Massive MIMO—Part I: Device Activity Detection and Channel Estimation

  • Liang LiuWei Yu
  • Computer Science
    IEEE Transactions on Signal Processing
  • 2018
TLDR
It is shown that in the asymptotic massive multiple-input multiple-output regime, both the missed device detection and the false alarm probabilities for activity detection can always be made to go to zero by utilizing compressed sensing techniques that exploit sparsity in the user activity pattern.

A Unified Design of Massive Access for Cellular Internet of Things

TLDR
A three-phase transmission protocol which consists of device detection and channel estimation, uplink data transmission, and downlink data transmission for the cellular IoT, so as to realize massive access over limited radio spectrum is designed.

Internet of Things Based on Cell-Free Massive MIMO

TLDR
Simulation results show a 40% improvement over existing Cell-Free wireless systems and a 10-fold improvement over known IoT systems based on small-cell systems.

Sparse Signal Processing for Grant-Free Massive Connectivity: A Future Paradigm for Random Access Protocols in the Internet of Things

TLDR
It is argued that massive multiple-input, multiple-output (MIMO) is especially well suited for massive IoT connectivity because the device detection error can be driven to zero asymptotically in the limit as the number of antennas at the base station (BS) goes to infinity by using the multiplemeasurement vector (MMV) compressed sensing techniques.

Sparse Activity Detection for Massive Connectivity

TLDR
This paper proposes an AMP algorithm design that exploits the statistics of the wireless channel and provides an analytical characterization of the probabilities of false alarm and missed detection via state evolution and designs the minimum mean squared error denoiser for AMP according to the channel statistics.

Energy-Efficient User Scheduling and Power Allocation for NOMA-Based Wireless Networks With Massive IoT Devices

TLDR
This paper investigates the dynamic user scheduling and power allocation problem as a stochastic optimization problem with the objective to minimize the total power consumption of the whole network under the constraint of all users’ long-term rate requirements and devise an efficient algorithm which can obtain the optimal control policies with a low complexity.

Massive device activity detection by approximate message passing

  • Zhilin ChenWei Yu
  • Computer Science
    2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2017
TLDR
Simulation results show significantly improved detection threshold for the channel-aware denoiser as compared to standard soft threshold based AMP, and an analytic characterization of the false alarm versus missed detection probabilities using state evolution for AMP is provided.

Cell-Free Massive MIMO Versus Small Cells

TLDR
Under uncorrelated shadow fading conditions, the cell-free scheme provides nearly fivefold improvement in 95%-likely per-user throughput over the small-cell scheme, and tenfold improvement when shadow fading is correlated.

Massive MIMO for Internet of Things (IoT) Connectivity