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Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The integration of orthogonal time frequency space signals into integrated sensing and communication systems has emerged as a highly promising approach for constructing intelligent transportation systems. Among these advancements, beamforming prediction techniques that incorporate multiple-input multiple-output technology have gained widespread attention. However, challenges remain in acquiring initial high-precision state parameters of vehicles and establishing continuous, reliable communication links in high-mobility scenarios. In this paper, we propose a novel MIMO-OTFS beamforming prediction scheme, leveraging a continuous-delay-and-Doppler-shift channel to facilitate information exchange between vehicles and the roadside unit. Furthermore, we develop a three-dimensional parameter estimation algorithm named orthogonal matching pursuit based on maximum likelihood dictionary correction, which offers high accuracy and low complexity. Utilizing this algorithm, we achieve precise multi-target beamforming prediction without approximation. Simulation results demonstrate that our approach significantly outperforms the traditional unscented Kalman filter method based on matched filtering in terms of multi-target beamforming prediction in the ISAC system.

The integrated sensing and communication(ISAC) system based on orthogonal time frequency space(OTFS) as the transmission waveform is recognized for its higher efficiency of resources, making it one of the key technologies for addressing the shortage of spectrum resources. As the number of sensing targets increases, the difference in signal power received by the base station from the superposition of multiple sensing echo signals becomes less significant. Traditional multi-target channel sensing and target detection algorithms result in error transmission and accumulation, thereby degrading the performance of the system's channel sensing and target detection. A maximum likelihood estimator based multi-objective channel parameter sensing and target detection algorithm was proposed to improve the estimation accuracy of the sensed channel and target parameters. Specifically, the parallel interference cancellation(PIC) algorithm was adopted to the received superimposed signals. The signals were reconstructed using the results obtained from the previous iteration and were subtracted from the received signals. The signal-to-interference-plus-noise ratio of the echo signals in the estimation of the sensed channel and target parameters was improved, so the performance of the maximum likelihood estimator was improved. Simulation results show that the proposed algorithm outperforms the traditional ones in terms of channel estimation accuracy. Additionally, the convergence of the proposed algorithm is also validated to be overhead saving.

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For a multi-user integrated sensing and communication system in the network of vehicles, a robust sensing-assisted communication massive multiple-input multiple-output (MIMO) orthogonal time frequency space (OTFS) transmission scheme was proposed.Due to the limited sensing accuracy of the radar, errors existed in the channel state information (CSI) reconstructed based on sensing parameters.The transmission performance decreased as a result.To address this issue, the CSI in the delay doppler domain was reconstructed based on the sensing parameters by the transmitter firstly.And a robust beam forming scheme was designed considering the CSI error.Secondly, the channel estimation error and inter user interference were perceived by receivers based on sensing parameters.Then the robust receiver was designed by incorporating the perceived interference errors into the signal detector in an analytical way.Finally, numerical simulation results show that the proposed method effectively reduces the system bit error rate and increases the data reception rate of users.The proposed method improves the overall system performance in this situation.

With the development of science and technology and the continuous improvement of related technologies, low earth orbit (LEO) satellite communication has become a hot technology that countries all over the world are chasing.The advantages of orthogonal time frequency spacetechnology can well solve the signal transmission problem of broadband satellite ground link in high moving speed scenarios, which is conducive to the unifi cation of modulation waveforms between satellites and the ground, and the realization of space-based integrated communication.However, its transmission performance is aff ected by the accuracy of channel estimation, and the special modulation makes its channel estimation method diff erent from the traditional technology, so it needs to be studied.The existing mainstream OTFS channel estimation schemes are introduced, and the advantages and disadvantages of each scheme were analyzed, which laied a foundation for subsequent research.

In order to provide reliable communication service for high-mobility scenarios, 6G can consider DD (delay-Doppler) domain based OTFS (orthogonal time frequency space) as its modulation scheme.By mapping the transmitted symbols onto DD domain and transforming them into TF (time-frequency) domain, OTFS endows all the transmitted symbols with the potential of capturing time-frequency full diversity, effectively improving the performance of communication in time-varying fading channels.Due to the superior properties of DD effective channel, the existing OTFS channel estimation methods were mostly carried out in DD domain.Considering the difference of implementation and application scenarios, existing DD channel estimation methods for OTFS were divided into three categories and overviewed, after which the challenges and potential solutions for current DD channel estimation methods were summarized and analyzed.

With the explosive growth of Internet devices, the 5G new radio (NR) system faces congestion and high latency issues due to the low access efficiency of traditional orthogonal multiple access (OMA).Besides this, the performance of the orthogonal frequency-division multiplexing (OFDM)-based system is severely degraded due to the Doppler effect in high-speed scenarios.To meet the low-latency, high-reliability, and massive connection requirements of 6G communication in high-mobility scenarios, firstly, a novel orthogonal time frequency space (OTFS)-based pattern division multiple access (PDMA) scheme, shortened as OTFS-PDMA, was proposed.Then, the system input-output relationship of different types of PDMA codeword allocation schemes in the delay-Doppler (DD) domain was derived.Finally, a low-complexity expectation propagation algorithm (EPA)-based receiver was proposed.Simulation results illustrate that the proposed OTFS-PDMA scheme achieves significant performance gains over the conventional OTFS-OMA scheme.For regular PDMA patterns, the PDMA codeword allocation has a slight impact on the system performance.For irregular patterns, the centralized spreading method outperforms the discrete one.For discrete spreading scheme, the system can achieve better performance by assigning irregular PDMA spread signals along the Doppler direction.In addition, the proposed EPA receiver outperforms its conventional counterparts.

Sixth generation (6G) wireless networks are envisioned to provide global coverage for the intelligent digital society of the near future, ranging from traditional terrestrial to non-terrestrial networks, where reliable communications in high-mobility scenarios at high carrier frequencies would play a vital role. In such scenarios, the conventional orthogonal frequency division multiplexing (OFDM) modulation, which has been widely used in both the fourth generation (4G) and the emerging fifth generation (5G) cellular systems, is vulnerable to severe Doppler spread. A new two-dimensional modulation technique called Orthogonal Time Frequency Space (OTFS) modulation designed in the delay-Doppler domain is introduced. Through this design, which exploits full diversity over time and frequency, OTFS coupled with equalization converts the fading, time-varying wireless channel experienced by modulated signals such as OFDM into a time-independent channel with a complex channel gain that is roughly constant for all symbols. In this paper, we evaluate and analyze the performance of the OTFS receiver using four data detection algorithms: Single-tap frequency domain equalizer, Linear minimum mean-square error detection (LMMSE), Message passing detection (MP), and Maximum-ratio combining detection (MRC). Further, we extend our study to the variants of OTFS, where the waveform is transmitted with a cyclic prefix (CP) or zero padding (ZP) added to each OTFS frame or block. The simulation results show that the MRC detector can be improved the detection of the OTFS receiver. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of science and technology and the continuous improvement of related technologies, low earth orbit (LEO) satellite communication has become a hot technology that countries all over the world are chasing. The advantages of orthogonal time frequency spacetechnology can well solve the signal transmission problem of broadband satellite ground link in high moving speed scenarios, which is conducive to the unification of modulation waveforms between satellites and the ground, and the realization of space-based integrated communication. However, its transmission performance is affected by the accuracy of channel estimation, and the special modulation makes its channel estimation method different from the traditional technology, so it needs to be studied. The existing mainstream OTFS channel estimation schemes are introduced, and the advantages and disadvantages of each scheme were analyzed, which laied a foundation for subsequent research. [ABSTRACT FROM AUTHOR]

Orthogonal Time Frequency Space (OTFS) as a two-dimensional modulation scheme designed in the delay-Doppler domain, is realized by inverse symplectic finite Fourier transform (ISFFT) and symplectic finite Fourier transform (SFFT), for combating the high Doppler channels toward future wireless communications. Meanwhile, generalized spatial modulation (GSM) offers an efficient implementation for multi-input multi-output (MIMO) systems, by activating only part of the transmit antennas to alleviate inter-channel interference (ICI). In this paper, the combination of the above two concepts is exploited, for bridging their unique advantages. On the other hand, an iterative detector based on generalized approximate message passing (GAMP) is also developed for GSM-OTFS. Simulation results demonstrate that the proposed GAMP detector can achieve better performance than the conventional minimum mean square error (MMSE) detector.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Compared with the orthogonal frequency division multiplexing (OFDM) modulation, the orthogonal time frequency space(OTFS) modulation has a lower peak-to-average power ratio. It can effectively resist the time selective fading caused by the Doppler effect and has significant performance advantages over doubly dispersive channels. However, the conventional OTFS linear minimum mean square error (LMMSE) method has a high complexity and is not easy to process in real time. In order to solve this problem, we propose a low-complexity equalization algorithm with infinite norm constraints based on the optimal coordinate reduction. The equalization algorithm not only obtains the optimal solution through a certain number of iterations and avoids direct matrix inversion but also equalizes infinite norm constraints to improve the symbol detection performance gains. At the same time, the OTFS delay-Doppler channel matrix we utilize is sparse and the two-norm squares of each column vector equally reduces the complexity of optimal coordinate descent. Finally, the simulation in the underwater acoustic communication scenario we designed verify the effectiveness of the proposed equalization algorithm. The simulation results show that the performance of the proposed equalization algorithm is close to that of the LMMSE method, while its low complexity is ensured.

Recently proposed orthogonal time frequency space (OTFS) modulation has been considered as a promising candidate for accommodating various emerging communication and sensing applications in high-mobility environments. In this paper, we propose a novel cross domain iterative detection algorithm to enhance the error performance of OTFS modulation. Different from conventional OTFS detection methods, the proposed algorithm applies basic estimation/detection approaches to both the time domain and delay-Doppler (DD) domain and iteratively updates the extrinsic information from two domains with the unitary transformation. In doing so, the proposed algorithm exploits the time domain channel sparsity and the DD domain symbol constellation constraints. We evaluate the estimation/detection error variance in each domain for each iteration and derive the state evolution to investigate the detection error performance. We show that the performance gain due to iterations comes from the non-Gaussian constellation constraint in the DD domain. More importantly, we prove that the proposed algorithm can indeed converge and, in the convergence, the proposed algorithm can achieve almost the same error performance as the maximum-likelihood sequence detection even in the presence of fractional Doppler shifts. Furthermore, the computational complexity associated with the domain transformation is low, thanks to the structure of the discrete Fourier transform (DFT) kernel. Simulation results are consistent with our analysis and demonstrate a significant performance improvement compared to conventional OTFS detection methods. [ABSTRACT FROM AUTHOR]

In this correspondence, an efficient clipping noise recovery method using reliability-based compressed sensing (CS) is proposed for orthogonal time frequency space modulation with iterative clipping and filtering. Concretely, the message passing algorithm is first used to acquire the hard decision of transmit signal, along with the corresponding reliability. Then, an efficient method to determine the reliable observations of clipping noise is presented by utilizing the reliable hard decision signals and the sparsity of the equivalent delay-Doppler channel. Finally, from these reliable observations, the clipping noise can be recovered by CS techniques through utilizing its sparsity in the time-domain. Simulation results show that the proposed method can recover the clipping noise efficiently and thus improve the bit-error-rate performance significantly. [ABSTRACT FROM AUTHOR]

In this letter, the method to reduce peak-to-average power ratio (PAPR) is studied in the pilot-embedded orthogonal time frequency space modulation where guard symbols with zero padding are introduced to avoid the interference between data and pilot symbols. By permitting the guard symbols to be padded with signals of small magnitudes, an efficient PAPR reduction method based on the iterative clipping and filtering (ICF) framework is proposed. In the proposed method, first, the clipping noise other than the clipped signal is filtered; second, the filtering coefficients for the clipping noises in the data-plus-pilot region and guard region are set to be different values to achieve good tradeoff between PAPR and bit error rate (BER) performance. Simulation results show that the proposed method can reduce the PAPR efficiently with mild BER performance loss. [ABSTRACT FROM AUTHOR]

The emerging orthogonal time frequency space (OTFS) modulation technique has shown its superiority to the current orthogonal frequency division multiplexing (OFDM) scheme, in terms of its capabilities of exploiting full time-frequency diversity and coping with channel dynamics. The optimal maximum a posteriori (MAP) detection is capable of eliminating the negative impacts of the inter-symbol interference in the delay-Doppler (DD) domain at the expense of a prohibitively high complexity. To reduce the receiver complexity for OTFS scheme, this paper proposes a variational Bayes (VB) approach as an approximation of the optimal MAP detection. Compared to the widely used message passing algorithm, we prove that the proposed iterative algorithm is guaranteed to converge to the global optimum of the approximated MAP detector regardless the resulting factor graph is loopy or not. Simulation results validate the fast convergence of the proposed VB receiver and also show its promising performance gain compared to the conventional message passing algorithm. [ABSTRACT FROM AUTHOR]