Near-Field Terahertz Communications: Model-Based and Model-Free Channel Estimation (original) (raw)
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Approximate Message Passing for Indoor THz Channel Estimation
arXiv: Signal Processing, 2019
Compressed sensing (CS) deals with the problem of reconstructing a sparse vector from an under-determined set of observations. Approximate message passing (AMP) is a technique used in CS based on iterative thresholding and inspired by belief propagation in graphical models. Due to the high transmission rate and a high molecular absorption, spreading loss and reflection loss, the discrete-time channel impulse response (CIR) of a typical indoor THz channel is very long and exhibits an approximately sparse characteristic. In this paper, we develop AMP based channel estimation algorithms for indoor THz communications. The performance of these algorithms is compared to the state of the art. We apply AMP with soft- and hard-thresholding. Unlike the common applications in which AMP with hard-thresholding diverges, the properties of the THz channel favor this approach. It is shown that THz channel estimation via hard-thresholding AMP outperforms all previously proposed methods and approache...
IEEE Access, 2022
Terahertz (THz) communication has been envisioned as a promising technique for the future sixth generation (6G) and beyond wireless networks because of its tens of gigahertz (GHz) bandwidth. However, wideband THz channel results in an increase in bandwidth, which gives rise to the phenomenon known as beam squint. Additionally, techniques based on the standard multiple-input multiple-output (MIMO) paradigm, such as channel estimation (CE), are rendered inapplicable by beam squint. Several sparse CE algorithms have been proposed in compressed sensing (CS) to accurately estimate the wideband THz massive multiple-input-multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) channel. However, the exploitation of these expert algorithms constitutes a committee machine (CM), which is likely to be superior to that obtained by any one of the committee expert acting separately. In this paper, by leveraging the notion of CM methodology, we address the CE problem in wideband THz mMIMO-OFDM systems with beam squint. To estimate the wideband THz mMIMO sparse channel vectors efficiently, we first present a committee machine technique for CS (CMTCS), which makes use of the estimations from multiple expert algorithms. Next, in order to enhance the wideband THz mMIMO channel estimation performance, we develop the iterative CMTCS (ICMTCS) technique, a CMTCS algorithm extension. Using the restricted isometry property (RIP), the theoretical analysis of the proposed schemes for realizing an improved channel reconstruction performance is presented. Simulation results demonstrate that the proposed schemes are effective and offer better CE performance in terms of normalized mean squared-error (NMSE) than those dictated by other CS-based CE algorithms and the traditional least-squares-based methods. INDEX TERMS Compressed sensing (CS), Committee machine, orthogonal frequency division multiplexing (OFDM), restricted isometry property (RIP), sparse channel estimation, Beam squint effect, massive MIMO, wideband THz communication.
Initial Access & Beam Alignment for mmWave and Terahertz communications
IEEE Access, 2022
The initial access in Millimeter wave (mmWave) 5G communications is very challenging and time consuming. In general, mmWave and terahertz communications require the use of directional antennas to seek narrow beams. However, due to this directionality, many issues can impact the beam alignment between transmitter and receiver. In this paper, we present a comprehensive survey of beam alignment and initial access in mmWave and terahertz 5G/6G systems. First, we present a detailed overview of initial access methods, techniques and beam management procedures. Then, we classify recent works related to beam alignment based on their objective functions (i.e., latency, power allocation, QoS, energy consumption, cost). We also highlight the beam alignment in terahertz 6G where we find that deep learning and reconfigurable intelligent surface are the two protagonists that help to achieve fast beam alignment.
Hierarchical beam alignment in SU-MIMO terahertz communications
ITU Journal on Future and Evolving Technologies, 2021
Single-Carrier Frequency Division Multiple Access (SC-FDMA) is a promising technique for high data rate indoor Terahertz (THz) communications in future beyond 5G systems. In an indoor propagation scenario, the Line-Of-Sight (LOS) component may be blocked by the obstacles. Thus, efficient THz SC-FDMA communications require a fast and reliable Beam Alignment (BA) method for both LOS and Non-Line-Of-Sight (NLOS) scenarios. In this paper, we first adopt the hierarchical discrete Fourier transform codebook for LOS BA, and introduce the hierarchical k-means codebook for NLOS BA to improve the beamforming gain. Simulation results illustrate that the hierarchical DFT codebook and the hierarchical k-means codebook can achieve the beamforming gain close to that of the maximum ratio transmission in LOS and NLOS cases, respectively. Based on these two codebooks, we propose a Multi-Armed Bandit (MAB) algorithm named Hierarchical Beam Alignment (HBA) for single-user SC-FDMA THz systems to reduce ...
Initial Access & Beam Alignment for mmWave and Terahertz Communications
IEEE Access
The initial access in Millimeter wave (mmWave) 5G communications is very challenging and time consuming. In general, mmWave and terahertz communications require the use of directional antennas to seek narrow beams. However, due to this directionality, many issues can impact the beam alignment between transmitter and receiver. In this paper, we present a comprehensive survey of beam alignment and initial access in mmWave and terahertz 5G/6G systems. First, we present a detailed overview of initial access methods, techniques, and beam management procedures. Then, we classify recent works related to beam alignment based on their objective functions (i.e., latency, power allocation, QoS, energy consumption, cost). We also highlight the beam alignment in terahertz 6G, where we find that deep learning and reconfigurable intelligent surface are the two protagonists that help to achieve fast beam alignment. INDEX TERMS 5G/6G, mmWave, terahertz, beamforming, initial access, beam alignment, beam steering, reconfigurable intelligent surface.
Channel Estimation Algorithms for Hybrid Antenna Arrays: Performance and Complexity
2019 16th International Symposium on Wireless Communication Systems (ISWCS)
At the millimeter wave and higher frequency bands the radio channel can often be expressed as a linear combination of a small number of scattering clusters. Hence, the number of angles of arrivals with significant components is limited. Due to severe path losses, the receiver must be equipped with an antenna array capable of forming narrow beams. The channel estimation with narrow beams is challenging. Algorithms developed for sparse estimation problems can be utilized to overcome the problem. In this paper, the performance and computational complexity of channel estimation methods for millimeter and terahertz frequency bands are compared. The methods considered are based on Bayesian learning with the relevance vector machine, orthogonal matching pursuit and the least absolute shrinkage and selection operator optimization. The conventional least squares channel estimator is used as a reference method. The complexity of the least squares estimator is found to be the smallest. The estimation accuracy of the Bayesian learning based estimator is the best but with increased computational complexity.
2021
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems relying on sparse channel state information (CSI) estimation techniques is conceived. To begin with, a practical MIMO channel model is developed for the THz band that incorporates its molecular absorption and reflection losses, as well as its non-line-of-sight (NLoS) rays associated with its diffused components. Subsequently, a novel CSI estimation model is derived by exploiting the angular-sparsity of the THz MIMO channel. Then an orthogonal matching pursuit (OMP)-based framework is conceived, followed by designing a sophisticated Bayesian learning (BL)-based approach for efficient estimation of the sparse THz MIMO channel. The Bayesian Cramer-Rao Lower Bound (BCRLB) is also determined for benchmarking the performance of the CSI estimation techniques developed. Finally, an optimal hybrid transmit precoder and receiver combiner pair is designed, which directly relies on the beamspace domain C...
IEEE Transactions on Wireless Communications
Millimeter-wave (mmWave) and Terahertz (THz)-band communications exploit the abundant bandwidth to fulfill the increasing data rate demands of 6G wireless communications. To compensate for the high propagation loss with reduced hardware costs, ultra-massive multiple-input multiple-output (UM-MIMO) with a hybrid beamforming structure is a promising technology in the mmWave and THz bands. However, channel estimation (CE) is challenging for hybrid UM-MIMO systems, which requires recovering the high-dimensional channels from severely few channel observations. In this paper, a Pruned Approximate Message Passing (AMP) Integrated Deep Convolutional-neural-network (DCNN) CE (PRINCE) method is firstly proposed, which enhances the estimation accuracy of the AMP method by appending a DCNN network. Moreover, by truncating the insignificant feature maps in the convolutional layers of the DCNN network, a pruning method including training with regularization, pruning and refining procedures is developed to reduce the network scale. Simulation results show that the PRINCE achieves a good trade-off between the CE accuracy and significantly low complexity, with normalizedmean-square-error (NMSE) of −10 dB at signal-to-noise-ratio (SNR) as 10 dB after eliminating 80% feature maps.
Investigation of Radio Channel Characterization in Terahertz Range
Journal of Nano- and Electronic Physics
To determine the performance of a wireless system, channel characterization must be carried out. In fact, in a wireless system, the propagation of an electromagnetic wave in space is of particular importance. For this reason, it is necessary to study the correctness of this channel before starting to work on it and implementing it in a communication system. It is therefore essential to have knowledge of the mechanisms involved in the propagation channel and of its interactions with the environment in order to be able to predict the chances and conditions for establishing a radio link between a transmitter and a receiver. In this work, we propose some strategies to model the transmission channel in the THz band. Indeed, before we can evaluate a transition system over wireless system, we have to model the propagation channel. First, we present the main tools allowing the modelling of the channel in the THz frequency range, which is considered a key new technology to meet the growing demand for higher speed wireless communications, as well as its impact on radio systems. In this paper, we propose a channel model for a wireless system working in the THz band. Besides, we propose some strategies to model the entire system as well as the propagation channel. We also simulate the proposed channel model. The simulation results show that the proposed system can be considered as an example for evaluating the performance of a communication chain based on a wireless system in the THz bands.