Delay Line Channel Model Research Articles

Analysis of potential 5G transmission methods concerning Bit Error Rate

Fifth-generation wireless (5G) significantly impacts individuals' lives and work and is expected to increase. Although OFDM has been used in previous generation technologies (4G), it has limitations in meeting specific criteria such as data. Issues like better power consumption and Bit Error Rate make this technology unsuitable for meeting current needs such as the Internet of Things and user-based processing. This research aims to test the BER success of the transmission technique proposed as a candidate for the 5G communication system. Performance analysis is carried out considering the Tapped Delay Line (TDL-A) channel model, which is recommended for 5G research. Various scenarios, including situations where the transmitter/receiver is fixed or mobile, are considered to provide a more comprehensive evaluation. Evaluations were also carried out on various channel delay distribution profiles to expand the scope of analysis. The research results show that in channel conditions with high delay distribution and mobility, the communication system that uses the FBMC transmission technique shows better and more stable performance compared to OFMD, F-OFMD, WOLA, UFMC systems, it has an SNR of about 36 dB to achieve a BER of approx 10-3 under 10 ns delay spreading conditions, demonstrating the superiority of FBMC in difficult channel conditions These findings emphasize the importance of considering BER and system complexity in the design of future communications systems. Thus, this research provides a significant original contribution to the understanding and developing 5G communication systems.

Demodulation Reference Signal (DM-RS) based channel estimation for non-terrestrial networks to support high mobility

This paper provides an adaptive 5G-NR based solution for non-terrestrial networks (NTN) to support the high mobility of the user equipment (UE). A front-loaded demodulation reference signal (DM-RS) symbol pattern with additional orthogonal symbols is proposed to support UE mobility 500 km/h. We develop a 5G-NR link-level simulator (LLS) to analyze the performance of physical downlink shared channel (PDSCH) under the proposed front-loaded DM-RS symbol pattern, tapped delay line (TDL) channel model, and precoding-based beamforming/MIMO schemes. The simulation results show that the proposed channel estimation method based on front-loaded DM-RS helps to improve the link reliability and achieves the maximum spectral efficiency up to 5.05 bps/Hz under 64-QAM, which can also contribute to the evolution of NTN in 6G networks to support the transonic speed mobility of UE.

Measurement Based Tapped Delay Line Model for Train-to-Train Communications

Train-to-train (T2T) communication is proposed as an auxiliary safety-guaranteed measure for railway communications. Vehicular communication standards have been supporting railway use cases and T2T communications. It is essential to consider the propagation characteristics of railway environments with dedicated T2T channel models for simulation and testing of vehicular communication standards. In this paper, we propose six tapped delay line (TDL) channel models for T2T communications in Hilly Terrain and Railway Station. The measurement based proposed channel models consider different T2T distances and relative speeds of up to 50 km/h with trains moving in an approaching maneuver. Also, a study about the Doppler-delay behavior in the considered scenarios is presented using the scattering function. The proposed TDL channel models as well as the measured propagation characteristics are used in a 802.11bd simulation framework. Both simulation results, which are based on the TDL channel models or on the measurements, are compared to each other. The results show a very good match between the TDL channel models and the measurement data and indicate a good accuracy of the theoretical derivations and the simulation method.

5G-NR Physical Layer-Based Solutions to Support High Mobility in 6G Non-Terrestrial Networks

Non-terrestrial network (NTN) systems can offer wide area coverage for applications requiring high mobility, which is expected in the sixth generation (6G) of telecommunication systems. This paper proposes a high-mobility support system based on the 5G-NR physical layer components for NTN connectivity. In this paper, we propose the optimization of 5G-NR numerologies and the impact of various modulation and coding schemes (MCS), 3GPP NR-NTN channel models, and MIMO/beamforming schemes with link-level simulation under pilot-aided-based perfect and DM-RS-based practical channel estimation at stationary UE and high mobility of 500 km/h, respectively. This paper also develops a link-level simulation of the 5G-NR physical downlink shared channel (PDSCH) under the 3GPP NR-NTN tapped delay line (TDL) channel model to support UE mobility up to 500 km/h. The bit error rate (BER), maximum achievable throughput (Mbps), and spectral efficiency (bps/Hz) are analyzed for the 5G-NR-based potential elements to be utilized in the evolution of NTN. Furthermore, the denser DM-RS symbol pattern is proposed for utilization in channel estimation to support high mobility, as simulation results prove their capability of fast decoding while using the front-loaded symbol structure. The simulation results show that the large 5G-NR numerologies, such as 120 kHz and DM-RS-based channel estimation, support the high UE mobility by providing high link reliability and the maximum achievable throughput of 368.832 Mbps and spectral efficiency of 3.68 bps/Hz under 64-QAM for TDL-E (LOS) channel model, which can also be a potential solution to support transonic speed mobility in the NTN of 6G services.

Channel Prediction Using Ordinary Differential Equations for MIMO Systems

Channel state information (CSI) estimation is part of the most fundamental problems in 5G wireless communication systems. In mobile scenarios, outdated CSI will have a serious negative impact on various adaptive transmission systems, resulting in system performance degradation. To obtain accurate CSI, it is crucial to predict CSI at future moments. In this paper, we propose an efficient channel prediction method in multiple-input multiple-output (MIMO) systems, which combines genetic programming (GP) with higher-order differential equation (HODE) modeling for prediction, named GPODE. In the first place, the variation of one-dimensional data is depicted by using higher-order differential, and the higher-order differential data is modeled by GP to obtain an explicit model. Then, a definite order condition is given for the modeling of HODE, and an effective prediction interval is given. In order to accommodate to the rapidly changing channel, the proposed method is improved by taking the rough prediction results of Autoregression (AR) model as a priori, i.e., Im-GPODE channel prediction method. Given the effective interval, an online framework is proposed for the prediction. To verify the validity of the proposed methods, We use the data generated by the Cluster Delay Line (CDL) channel model for validation. The results show that the proposed methods has higher accuracy than other traditional prediction methods.

Spectral Efficiency of Precoded 5G-NR in Single and Multi-User Scenarios under Imperfect Channel Knowledge: A Comprehensive Guide for Implementation

Digital precoding techniques have been widely applied in multiple-input multiple-output (MIMO) systems to enhance spectral efficiency (SE) which is crucial in 5G New Radio (NR). Therefore, the 3rd Generation Partnership Project (3GPP) has developed codebook-based MIMO precoding strategies to achieve a good trade-off between performance, complexity, and signal overhead. This paper aims to evaluate the performance bounds in SE achieved by the 5G-NR precoding matrices in single-user (SU) and multi-user (MU) MIMO systems, namely Type I and Type II, respectively. The implementation of these codebooks is covered providing a comprehensive guide with a detailed analysis. The performance of the 5G-NR precoder is compared with theoretical precoding techniques such as singular value decomposition (SVD) and block-diagonalization to quantify the margin of improvement of the standardized methods. Several configurations of antenna arrays, number of antenna ports, and parallel data streams are considered for simulations. Moreover, the effect of channel estimation errors on the system performance is analyzed in both SU and MU-MIMO cases. For a realistic framework, the SE values are obtained for a practical deployment based on a clustered delay line (CDL) channel model. These results provide valuable insights for system designers about the implementation and performance of the 5G-NR precoding matrices.

Deep Learning Channel Estimation for OFDM 5G Systems with Different Channel Models

At cellular wireless communication systems, channel estimation (CE) is one of the key techniques that are used in Orthogonal Frequency Division Multiplexing modulation (OFDM). The most common methods are Decision‐Directed Channel Estimation, Pilot-Assisted Channel Estimation (PACE) and blind channel estimation. Among them, PACE is commonly used and has a steadier performance. Applying deep learning (DL) methods in CE is getting increasing interest of researchers during the past 3 years. The main objective of this paper is to assess the efficiency of DL-based CE compared to the conventional PACE techniques, such as least-square (LS) and minimum mean-square error (MMSE) estimators. A simulation environment to evaluate OFDM performance at different channel models has been used. A DL process that estimates the channel from training data is also employed to get the estimated impulse response of the channel. Two channel models have been used in the comparison: Tapped Delay Line and Clustered Delay Line channel models. The performance is evaluated under different parameters including number of pilots (64 pilots or 8 pilots), number of subcarriers (64), the length of cyclic prefix (16 or 0 samples) and carrier frequency (4 GHz) through computer simulation using MATLAB. From the simulation results, the trained DL estimator provides better results in estimating the channel and detecting the transmitted symbols compared to LS and MMSE estimators although, the complexity of the proposed LSTM estimator exceeds the equivalent LS estimator. Furthermore, the DL estimator also demonstrates its effectiveness with various pilot densities and with different cyclic prefix periods.

Research on Performance Metrics and Environmental Conditions for 5G MIMO OTA

For Multiple-input, multiple-output (MIMO) user equipment (UE), over-the-air (OTA) testing of radiated multi-antenna reception performance is crucial to guarantee actual network performance and is mandatory in North America, Europe and China. For 5G MIMO OTA, 3GPP has specified the clustered delay line (CDL) channel models as the reference channel models, which present higher order and directivity than those of 4G. Therefore, which kinds of performance metrics and environmental conditions are feasible and necessary to better characterize the MIMO performance should be studied. In this paper, MIMO OTA measurement results of different figures of merits (FoMs) under both UE noise-limited and interference-limited environmental conditions have been compared and discussed, respectively. In addition, the impact of different channel models on MIMO OTA throughput performance as well as the variance per azimuth are compared. Based on the analysis, Peak-Null can better reflect the difference between the 12 azimuth positions than Variance. Total Radiated Multi-antenna Sensitivity (TRMS) under both channel models presents nearly the same performance trends at different thresholds. On the contrary, MIMO Average Radiated SIR Sensitivity (MARSS) exhibits a high dependence on channel models. The MARSS under UMi channel model shows a much smaller performance variation between UEs than UMa channel model. TRMS under 3GPP UE noise-limited environmental condition exhibits a stronger ability to distinguish between good and bad performing devices than that of MARSS under CTIA interference-limited environmental condition. The discrepancy can reach 4 dB at most. This discrepancy does not come from different average manners between TRMS and MARSS, but originates from environmental condition itself. Therefore, it is proposed to adopt TRMS under UE noise-limited environmental condition as the unique or baseline test condition in 5G FR1 MIMO OTA. Peak-Null can be considered as a secondary FoM to characterize the variance per azimuth.

Broadband Extended Array Response-Based Subspace Multiparameter Estimation Method for Multipolarized Wireless Channel Measurements

The clustered delay line channel model, in which each cluster consists of many rays, is widely used for link-level evaluations in mobile communications. Multiple parameters of each ray, including the delay, amplitude, cross-polarization ratio (XPR), initial phases of four polarization combinations, and the azimuth and elevation angles of arrival and departure, must be known and are measured using a channel sounder. The number of rays in every cluster is usually greater than the number of elements in the antenna array of the channel sounder, which represents a challenging issue in multipolarized channel measurements. Based on the broadband extended array response of an electromagnetic vector antenna array, a new subspace estimation method is proposed to resolve a large number of rays. The inter-element spacing of the array can be greater than half the carrier wavelength, which reduces inter-element coupling and simplifies the array design, especially for millimeter-wave bands. The delay of each cluster is first estimated using the reference antenna element. Next, two-dimensional angles of every ray are estimated using the classic rank-deficient multiple signal classification algorithm. Finally, the initial phases, XPR, and amplitude of every ray are estimated. Simulation results validate the proposed method.

5G system throughput performance evaluation using Massive-MIMO technology with Cluster Delay Line channel model and non-line of sight scenarios

The fourth-generation system for mobile cellular communications (4G) has achieved great developments. The main problem here is that, with the passage of time and technical development, the need for new applications and services has emerged, and thus we need a new system that supports these matters in addition to the problems and limitations. One of the main challenges that the 4G system suffers from is the ability to support a larger number of devices, low latency, working in real time, provide greater capacity, in addition to providing a high data rate (bit rate) – hence 4G stands unable to support many new applications. This is what made researchers aspire to overcome these problems or reduce their impact to the maximum extent and this is what we expect to achieve in the new generation (5G). In this research, a presentation was made of the 5G system regarding with one of its most important techniques (Massive MIMO technology), clarification of some concepts related to the study such as throughput and NLOS (Non-Line of Sight), as well as the channel model used. The results of the experiments were presented with the discussion.

Measurement‐based determination of parameters for non‐stationary TDL models with reduced number of taps

This study proposes a new strategy of extracting parameters for tapped delay line (TDL) channel models from vehicle to infrastructure channel measurements. The proposed approach is based on an already existing method to derive parameters for a non-stationary model using first-order Markov chains. It will be shown that with the proposed method, the number of taps necessary to regenerate the delay spread of a channel can be significantly reduced. An approach will be discussed to evaluate the performance of the model. The feasibility of the method will be confirmed using channel sounding measurements.

A Measurement-Based Multipath Channel Model for Signal Propagation in Presence of Wind Farms in the UHF Band

Scattering signals on wind turbines may lead to degradation problems on the communication systems provided in the UHF band, such as terrestrial television broadcasting, broadband wireless systems or public safety services. To date, despite the continuous requests from the International Telecommunication Union for studies on this field, no channel model has been developed to characterize signal propagation under these particular conditions. In response to this necessity, this paper presents a complete Tapped Delay Line (TDL) channel model to characterize multipath propagation in presence of a wind farm, including novel scattering modeling and Doppler spectra characterization. As proved later, this channel model, which is based on both theoretical development and empirical data obtained in the surroundings of a real wind farm, is adaptable to the particular features of any case under study: wind turbine dimensions, working frequency, and relative location of the wind farm, transmitter and receivers.

Performance of multicarrier DS/SSMA systems in frequency-selective fading channels

Multicarrier direct-sequence spread-spectrum multiple-access systems in frequency-selective fading channels are investigated. A consistent channel model is used for each system. First, the tapped delay line (TDL) channel model with uniformly spaced, uncorrelated taps is investigated to model a complex Gaussian, wide-sense stationary, uncorrelated scattering channel. An approximate average bit-error-rate expression is obtained for the receiver with RAKE fingers on each subcarrier branch, whose outputs are combined according to the maximum signal-to-noise ratio criterion. Various system configurations are examined for the same TDL channel model, data rate, total system bandwidth, and excess bandwidth of the chip waveform. All the systems compared employ the same number of correlators. The numerical results show that, given a contiguous spectrum, the systems with more fractionally-spaced RAKE fingers per subchannel are more robust than the systems with more subcarriers.

MLSE for an unknown channel .I. Optimality considerations

The problem of performing joint maximum-likelihood (ML) estimation of a digital sequence and unknown dispersive channel impulse response is considered starting from a continuous-time (CT) model. Previous investigations of this problem have not considered the front-end (FE) processing in detail; rather, a discrete-time signal model has been assumed. We show that a fractionally-spaced whitened matched filter, matched to the known data pulse, provides a set of sufficient statistics when a tapped delay line channel model is assumed, and that the problem is ill-posed when the channel impulse response is generalized to a CT, finite-length model. Practical approximations are considered that circumvent this ill-posed condition. Recursive computation of the joint-ML metric is developed. Together, the FE processing and metric recursion provide a receiver structure which may be interpreted as the theoretical foundation for the previously introduced technique of per-survivor processing, and they lead directly to generalizations. Several FE processors representative of those suggested in the literature are developed and related to the practically optimal FE.

Equaliser Performance for HIPERLAN in indoor channels

In order to accomplish practical deployment modelling for system performance evaluation and comparison for possible modulation and equalisation schemes to be used in HIPERLAN, a wide band tapped delay line (WTDL) channel model has been adopted by ETSI to characterise the multipath fading in the indoor radio environment. Based on this statistical channel model, and using Monte Carlo method, this paper evaluates the average probability of error for linear and decision feedback equaliser as a function of signal-to-noise ratio. It also evaluates the matched filter bound for this channel model. The results show the optimum performance levels achievable via the use of any equaliser.