Performance Analysis of NR based Vehicular IoT System with OTFS Modulation

Reddy, Ch Santosh; Singhal, Chetna

doi:10.1109/vtc2021-fall52928.2021.9625242

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…where g t (t) denotes the shape filter function in the transmit end. When g t (t) is a nonrectangular pulse, it will cause non-orthogonality between subcarriers, which will reduce the bit error rate (BER) performance [21]. Therefore, in this paper, we assume that g t (t) is a rectangular pulse, and Equation ( 2) also degenerates into inverse discrete Fourier transform (IDFT), which is equivalent to traditional OFDM modulation.…”

Section: The Transmitted Signalmentioning

confidence: 99%

GAMP-Based Low-Complexity Sparse Bayesian Learning Channel Estimation for OTFS Systems in V2X Scenarios

Zheng,

Wang,

Wang

et al. 2023

Electronics

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Vehicle to everything (V2X) is widely regarded as a critical application for future wireless communication networks. In V2X, large relative speeds between vehicles may severely deteriorate the performance of communication between vehicles. Orthogonal time frequency space (OTFS) modulation, which converts time- and frequency-selective channels into non-selective channels in the delay-Doppler (DD) domain, provides a solution for establishing reliable wireless communications in V2X scenarios. However, in the complex multi-scattering scenarios, the channel also suffers from a serious inter-Doppler interference (IDI) problem, which poses a great challenge to the accurate demodulation of OTFS receiver signals. To address the above problems, this paper considers the variation of Doppler sampling points within one symbol when deriving the channel model, which effectively overcomes the IDI problem, and employs a basis expansion model (BEM) to convert the channel estimation into a sparse recovery problem for the basis coefficients. In addition, to better utilize the sparse nature of the OTFS channel, a generalized approximate message passing-sparse Bayesian learning (GAMP-SBL)-based algorithm is employed to estimate the basis coefficients of the channel. The complexity of this algorithm is greatly reduced compared to the conventional SBL algorithm. Finally, system simulation results are reported to verify the superiority of the proposed scheme.

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Section: The Transmitted Signalmentioning

confidence: 99%

GAMP-Based Low-Complexity Sparse Bayesian Learning Channel Estimation for OTFS Systems in V2X Scenarios

Zheng,

Wang,

Wang

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

“…First, at the transmitter side, there is the placement of M 1 N 1 data information symbols into the TDD domain signal grid, where there are N 1 rows of data in the Doppler domain and M 1 columns of data in the time delay domain. Then, the TDD domain signal is transformed to the TF domain by ISFFT [28]. The formula can be expressed as…”

Section: Transmission Modelmentioning

confidence: 99%

Resource Allocation and Trajectory Optimization in OTFS-Based UAV-Assisted Mobile Edge Computing

Guo

et al. 2023

Electronics

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Mobile edge computing (MEC) powered by unmanned aerial vehicles (UAVs), with the advantages of flexible deployment and wide coverage, is a promising technology to solve computationally intensive communication problems. In this paper, an orthogonal time frequency space (OTFS)-based UAV-assisted MEC system is studied, in which OTFS technology is used to mitigate the Doppler effect in UAV high-speed mobile communication. The weighted total energy consumption of the system is minimized by jointly optimizing the time division, CPU frequency allocation, transmit power allocation and flight trajectory while considering Doppler compensation. Thus, the resultant problem is a challenging nonconvex problem. We propose a joint algorithm that combines the benefits of the atomic orbital search (AOS) algorithm and convex optimization. Firstly, an improved AOS algorithm is proposed to swiftly obtain the time slot allocation and high-quality solution of the UAV optimal path. Secondly, the optimal solution for the CPU frequency and transmit power allocation is found by using Lagrangian duality and the first-order Taylor formula. Finally, the optimal solution of the original problem is iteratively obtained. The simulation results show that the weighted total energy consumption of the OTFS-based system decreases by 13.6% compared with the orthogonal frequency division multiplexing (OFDM)-based system. The weighted total energy consumption of the proposed algorithm decreases by 11.7% and 26.7% compared with convex optimization and heuristic algorithms, respectively.

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A review on orthogonal time–frequency space modulation: State-of-art, hotspots and challenges

2023

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Performance Analysis of NR based Vehicular IoT System with OTFS Modulation

Cited by 5 publications

References 7 publications

GAMP-Based Low-Complexity Sparse Bayesian Learning Channel Estimation for OTFS Systems in V2X Scenarios

GAMP-Based Low-Complexity Sparse Bayesian Learning Channel Estimation for OTFS Systems in V2X Scenarios

Resource Allocation and Trajectory Optimization in OTFS-Based UAV-Assisted Mobile Edge Computing

A review on orthogonal time–frequency space modulation: State-of-art, hotspots and challenges

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