Channel Estimation via Orthogonal Matching Pursuit for Hybrid MIMO Systems in Millimeter Wave Communications

By Junho Lee, Gye-Tae Gil, Yong Hoon Lee. IEEE Transactions on Communications, 2016

661 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/415ff894bfdc4dccc32ba13015914ee9c7bdb1f3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Chau Yuen
2. Chongwen Huang
3. Linglong Dai
4. Sumei Sun
5. Lei Liu
6. E. De Poorter
7. Ingrid Moerman
8. Ahmed Musa

In Signal Processing

1. Gonzalo Seco-Granados
2. Chau Yuen
3. Ahmed Alkhateeb
4. Henk Wymeersch
5. Ingrid Moerman
6. Linglong Dai
7. Sumei Sun
8. Mingyao Cui

Citations in the corpus

• A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives (2018, methodology): “Channel estimation for mmWave massive MIMO system with a TX with Nt antennas and a RX with Nr antennas is presented in [139].”
• A Tutorial on Fluid Antenna System for 6G Networks: Encompassing Communication Theory, Optimization Methods and Hardware Designs (2024, methodology): “To improve the accuracy, OMP in [153] can be adopted to jointly estimate the AoA-AoD pair in an alternative manner, at the expense of higher computational complexity.”
• Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems (2016, methodology): “Essentially, the beamspace channel representation is to map the signal of the spatial domain to the signal of the beam domain by employing a carefully designed discrete lens antenna array instead of the electromagnetic antenna array [9], [38]–[42].”
• Channel Estimation for Extremely Large-Scale MIMO: Far-Field or Near-Field? (2021, methodology): “For example, by utilizing the angular-domain sparsity, the classical orthogonal matching pursuit (OMP) algorithm was used in [9] to recover the angular-domain channel, where the channel was transformed into its angular-domain representation through the standard spatial Fourier transform.”
• Position and Orientation Estimation Through Millimeter-Wave MIMO in 5G Systems (2017, positive): “In [16], a CS method is proposed based on the redundant dictionary matrices.”
• A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G (2023, neutral): “the location-based beam alignment, respectively [208,209].”
• Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems (2018, background): “Prior work on mmWave channel covariance estimation leveraged the sparse nature of the channels and developed compressive sensing based techniques [3], [4].”