A Low-Overhead Hierarchical Beam-tracking Algorithm for THz Wireless Systems

Stratidakis, Giorgos; Ntouni, Georgia D.; Boulogeorgos, Alexandros–Apostolos A.; Kritharidis, Dimitrios; Alexiou, Angeliki

doi:10.1109/eucnc48522.2020.9200946

Cited by 16 publications

(19 citation statements)

References 23 publications

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“…In addition, they apply a hierarchical codebook and study the relationship between beamwidth and the UAV's speed and flying range. A multi-resolution hierarchical codebook is also utilized in [13]- [15] to enable low-overhead beam training in mmWave and THz systems. Although [12]- [15] are able to reduce the training overhead, the time steps during which beam training is initiated are either considered to be periodic or follow a reactive or threshold-based approach.…”

Section: A Prior Artmentioning

confidence: 99%

“…We adopt the Saleh-Valenzuela channel model, that is widely used for THz communications (e.g., see [6], [13], [15]). Hence, the channel from BS j to the i-th UE is given by:…”

Section: A Channel Modelmentioning

confidence: 99%

“…The optimization of q k (including blockages) is covered in Section IV-A. Thus, based on these assumptions and the combiner in (13), the subproblem for beamforming optimization can be written as…”

Section: Reliable Variable-beamwidth Precodingmentioning

confidence: 99%

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Reliable Beam Tracking with Dynamic Beamwidth Adaptation in Terahertz (THz) Communications

Karacora¹,

Chaccour²,

Sezgin³

et al. 2022

Preprint

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THz communication is regarded as one of the potential key enablers for next-generation wireless systems. While THz frequency bands provide abundant bandwidths and extremely high data rates, the operation at THz bands is mandated by short communication ranges and narrow pencil beams, which are highly susceptible to user mobility and beam misalignment as well as channel blockages. This raises the need for novel beam tracking methods that take into account the tradeoff between enhancing the received signal strength by increasing beam directivity, and increasing the coverage probability by widening the beam. To address these challenges, a multi-objective optimization problem is formulated with the goal of jointly maximizing the ergodic rate and minimizing the outage probability subject to transmit power and average overhead constraints. Then, a novel parameterized beamformer with dynamic beamwidth adaptation is proposed. In addition to the precoder, an event-based beam tracking approach is introduced that enables reacting to outages caused by beam misalignment and dynamic blockage while maintaining a low pilot overhead. Simulation results show that our proposed beamforming scheme improves average rate performance and reduces the amount of communication outages caused by beam misalignment.Moreover, the proposed event-triggered channel estimation approach enables low-overhead yet reliable communication.

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Section: A Prior Artmentioning

confidence: 99%

“…We adopt the Saleh-Valenzuela channel model, that is widely used for THz communications (e.g., see [6], [13], [15]). Hence, the channel from BS j to the i-th UE is given by:…”

Section: A Channel Modelmentioning

confidence: 99%

See 1 more Smart Citation

Reliable Beam Tracking with Dynamic Beamwidth Adaptation in Terahertz (THz) Communications

Karacora¹,

Chaccour²,

Sezgin³

et al. 2022

Preprint

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“…This characteristic is expected to influence both beamforming design as well as resource allocation and user association. • The large penetration loss in the THz band, which may surpass 40 or even 50 dB (Kokkoniemi et al, 2016;Stratidakis et al, 2019;Petrov et al, 2020;Stratidakis et al, 2020a;Stratidakis et al, 2020b), renders questionable the establishment of the non-LoS links. As a result, blockage avoidance schemes are needed.…”

Section: Notationsmentioning

confidence: 99%

Machine Learning: A Catalyst for THz Wireless Networks

Boulogeorgos

Yaqub²,

Renzo

et al. 2021

Front. Comms. Net.

Self Cite

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With the vision to transform the current wireless network into a cyber-physical intelligent platform capable of supporting bandwidth-hungry and latency-constrained applications, both academia and industry turned their attention to the development of artificial intelligence (AI) enabled terahertz (THz) wireless networks. In this article, we list the applications of THz wireless systems in the beyond fifth generation era and discuss their enabling technologies and fundamental challenges that can be formulated as AI problems. These problems are related to physical, medium/multiple access control, radio resource management, network and transport layer. For each of them, we report the AI approaches, which have been recognized as possible solutions in the technical literature, emphasizing their principles and limitations. Finally, we provide an insightful discussion concerning research gaps and possible future directions.

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“…Their model relies on a practical user mobility trajectory [24] to develop a time-evolution based framework for the angle of arrival (AoA)/ angle of departure (AoD) of each user. Subsequent contributions in this direction, such as [25] and [26], consider base station (BS) cooperation and a multi-resolution codebook, respectively, for improving the accuracy of channel tracking obtained via the a priori information aided scheme of [12]. However, this improved tracking accuracy is achieved at the cost of inter-BS cooperation, which necessitates additional infrastructure and control overheads.…”

Section: A Related Work and Contributionsmentioning

confidence: 99%

Hybrid Transceiver Design for Tera-Hertz MIMO Systems Relying on Bayesian Learning Aided Sparse Channel Estimation

Srivastava¹,

Tripathi²,

Varshney³

et al. 2021

Preprint

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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 CSI estimates and only requires limited feedback. Finally, simulation results are provided for quantifying the improved mean square error (MSE), spectral-efficiency (SE) and bit-error rate (BER) performance for transmission on practical THz MIMO channel obtained from the HIgh resolution TRANsmission (HITRAN)-database.

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A Low-Overhead Hierarchical Beam-tracking Algorithm for THz Wireless Systems

Cited by 16 publications

References 23 publications

Reliable Beam Tracking with Dynamic Beamwidth Adaptation in Terahertz (THz) Communications

Reliable Beam Tracking with Dynamic Beamwidth Adaptation in Terahertz (THz) Communications

Machine Learning: A Catalyst for THz Wireless Networks

Hybrid Transceiver Design for Tera-Hertz MIMO Systems Relying on Bayesian Learning Aided Sparse Channel Estimation

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