Deep Learning-Based Estimation of Emission Time and Arrival Time in Diffusive Multi-Receiver Molecular Communication

Compressed sensing (CS) theory provides a new solution for the possibility of using impulse radio ultra-wideband (IR-UWB) for high-precision time of arrival (TOA) estimation. Because of the sparsity of IR-UWB signals, the CS theory enables the reconstruction of signals from a small set of random measurements at a sub-Nyquist rate. In current studies involving CS-based sampling architectures, the quantization process is usually idealized and the TOA estimation threshold is fixed. In this paper, the influence of quantization noise is fully considered, and a TOA estimation method for IR-UWB system with overloading quantization is proposed. Further, a dynamic-threshold setting model is proposed for the TOA estimation method based on the analysis of both thermal noise and quantization noise. Simulation results show that the proposed method can achieve sub-nanosecond TOA estimation accuracy under the quantized CS framework, and the effectiveness of the proposed dynamic-threshold setting model is verified.

In this paper we present and evaluate a low cost simple method for accurate Time Of Arrival (TOA) estimation in multipath fading channels for positioning purposes. It is well known that TOA estimations are biased in multipath propagation and non-line-of-sight (NLOS) conditions. These biases will result in poor position estimations in wireless networks. Recently supper-resolution methods have been widely used for high resolution TOA estimations. Although these methods result in accurate TOA estimates, but they need strong processors that in many cases makes them impractical. Here, using time domain properties of the estimated channel delay profile, we introduce a simple method to reduce the TOA estimation errors due to the multipath fading channels. In order to evaluate the proposed method, we simulate a UMTS network based on 3GPP standards. The positioning error using the proposed method will be compared with the ones obtained by MUSIC algorithm which is a famous and accurate supper-resolution method. Simulation results show the effectiveness of the proposed method.

The ultra-wideband (UWB) system, which transmits information using nanosecond or even sub-nanosecond pulses, has been widely applied in precise positioning. In this paper, we investigate the problem of the time of arrival (TOA) estimation and the direction of arrival (DOA) estimation in the UWB systems with antenna array and propose a joint TOA and DOA estimation algorithm with doubled frequency sample points and extended number of clusters. Specifically, the proposed algorithm uses two antennas to receive impinging signals and utilizes the conjugate symmetry characteristic of the delay matrices to extend the sample points as well as the number of clusters. Moreover, in order to obtain TOA estimates with low computational complexity, the proposed algorithm transforms the two-dimensional (2D) spectral search to one-dimensional (1D) searches. The DOA estimates can then be achieved by using the TOA estimation results and the geometric information. Simulation results are given to testify the performance of the proposed algorithm.

In time of arrival (TOA) estimation of received ultra-wideband (UWB) pulses, traditional maximum likelihood (ML) and generalized likelihood estimators become impractical due to their high sampling rate. Sub-nyquist ML-based TOA estimation currently assumes a priori knowledge of the UWB channels in the form of the average power delay profile (APDP). In this paper, instead of assuming a known APDP, we propose and investigate a joint estimator of the TOA and the APDP. A parametric model is assumed for the APDP and its parameters are estimated via a least-squares approach; the estimated APDP is then used to find the TOA estimate. The proposed method requires low sampling rate and is well-suited for real-time implementation. Simulation results show that it can achieve a fine accuracy in practical UWB TOA estimation scenarios.

Trajectory clustering for SVR-based Time of Arrival estimation

Time of arrival and power delay profile estimation for IR-UWB systems

A novel TOA estimation method with effective NLOS error reduction

Owing to the extremely high-time resolution of impulse radio ultra-wideband (IR-UWB), time of arrival (TOA) estimation has been an important and tempting issue of this technology ever since its emergence. Conventional TOA estimation (TOAE) schemes require prohibitively high sampling rate and a priori knowledge of the received signal, and hence render a practical implementation rigorous or even infeasible. To tackle these drawbacks, this paper proposes a low-complexity energy detection-based non-coherent TOAE scheme, which is composed of two processing stages: initial signal acquisition (ISA) and fine timing estimation (FTE). In the ISA stage, a linear quadrature optimisation (LQO)-based weighting scheme is proposed to coarsely capture the arrival of the IR-UWB signals. Capitalising on the acquisition of the IR-UWB signal in a relatively short time range, the authors then develop in the FTE stage, a double-threshold test (DTT) tailored for locating the leading edge of the IR-UWB signal. Simulations illustrate that the LQO algorithm yields a considerably increased probability of seizing the arrival of the IR-UWB signals in a blind manner, and the DTT strategy significantly ameliorates the TOAE accuracy in terms of mean absolute error, compared with the conventional energy detection-based TOAE methods.

The Impulse Radio - Ultra Wideband (IR-UWB) technology, which benefits from unprecedented ranging capabilities through precise Time of Arrival (TOA) estimation, is now widely considered as a credible solution for Location and Tracking (LT) applications in Wireless Sensor Networks (WSN). In this context, low-complexity receiver architectures such as Energy Detectors (ED) have been favored for the past years. Recent methods have also been proposed to determine ED thresholds for optimal leading-edge detection under simplified channel assumptions. Nevertheless, more realistic indoor multipath profiles still make threshold-based TOA estimation challenging with such receivers. In this paper, we present two new Bayesian TOA estimators that rely on the overall energy profile available at the output of the ED, as well as on realistic channel statistics (typically that of the IEEE 802.15.4a standard). Simulation results are provided for performance comparison with two popular threshold-based estimators, showing the robustness of the new methods at practical Signal to Noise Ratio (SNR) values.

Time of arrival (TOA) estimation in multipath dense environment for UWB backscattering radio frequency identification (RFID) system is challenging due to the presence of strong clutter. In addition, the backscattering RFID system has peculiar signal transmission and modulation characteristics, which are considerably different from conventional communication and localization systems. The existing TOA estimators proposed for conventional UWB systems are inappropriate for the backscattering RFID system since they lack the required clutter suppression capability and do not account for the peculiar characteristics of backscattering system. In this paper, we derive a nondata-aided (NDA) least square (LS) TOA estimator for UWB backscattering RFID system. We show that the proposed estimator is inherently immune to clutter and is robust in under-sampling operation. The effects of various parameter settings on the TOA estimation accuracy are also studied via simulations.

In wireless sensor networks, ranging or positioning via ultra-wideband (UWB) has caused widespread research interests where the non-coherent energy detection (ED) method with low sampling rate and low complexity is widely studied. However, the traditional energy detection methods only analyze the signal energy in the time domain, so their error is relatively large. In this paper, the simulation results show that most of the signal energy concentrates in the low-frequency band, so a novel threshold selection method for time of arrival (TOA) estimation is proposed that analyzes the signals in both time domain and frequency domain. In this method, the received signal is decomposed by “db6” wavelet and the kurtosis of energy blocks of the low-frequency wavelet coefficients (Kc) is analyzed. At last, the mapping relationship between Kc and the normalized threshold for TOA estimation is created using polynomial fitting with degree 3. The simulation results show that the TOA estimation error of the proposed method is significantly less than the method without wavelet decomposition.

The paper provides an evaluation of a non-coherent UWB system, which is suitable for low complexity, cost and data rate UWB wireless sensor networks with positioning capability. Synchronization and time of arrival (TOA) estimation is performed using a non-coherent energy collection method. Coarse and fine synchronization are performed to identify the energy clusters and refine the energy collection window respectively. The effect of the integration window size is evaluated for both TOA estimation and position estimation. Direct method (DM) and Davidon-Fletcher-Powell (DFP) algorithms are implemented for position estimation. The result shows the possibility of attaining sub-meter performance using a low complexity and cost device.

요즈음에는 GPS 및 GIS을 기반으로, 운전자에게 최단 경로탐색 및 예상도착시간을 인터넷 및 휴대폰으로 검색할 수 있다. 그러나, 아무리 좋은 자동항법 장치도 평균차량속도가 10- 20 Km 일 때에는 최단경로를 생성할 수 없다. 그러므로 승용차대기시간과 평균차량속도를 개선하기 위해서, 서로 다른 교차로 길이 및 교차로 차선수 일 때에도, 퍼지 적응 규칙을 이용한 최적녹색시간 알고리즘을 제안한다. 본 논문에서는 인터넷을 이용해서 위험한 도로, 공사중인 도로 및 목적지 예상 도착시간 및 최적의 교통상황을 예보하는 기능을 제공할 수 있도록 하였다. Now days, It is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic information, estimation of destination arrival time, under construction road, and dangerous road using internet.

We synthesize the quasi-likelihood, maximum-likelihood, and quasioptimal algorithms for estimating the arrival time and duration of a radio signal with unknown amplitude and initial phase. The discrepancies between the hardware and software realizations of the estimation algorithm are shown. The characteristics of the synthesized-algorithm operation efficiency are obtained. Asymptotic expressions for the biases, variances, and the correlation coefficient of the arrival-time and duration estimates, which hold true for large signal-to-noise ratios, are derived. The accuracy losses of the estimates of the radio-signal arrival time and duration because of the a priori ignorance of the amplitude and initial phase are determined.

This paper addresses the problem of TOA and DOA estimation in IR-UWB systems. It considers a frequency domain approach for joint high resolution estimation of Time Of Arrival (TOA) and Direction Of Arrival (DOA). The proposed scheme performs timing acquisition following a two step approach: a first stage where coarse symbol timing is achieved by means of chip energy estimation and a minimum distance criterion based on the time-hopping sequence knowledge, followed by a reduced complexity high resolution TOA estimator that provides fine timing acquisition. The proposed algorithm can resolve time synchronization blindly, without the need for channel estimation and can operate on a single symbol basis. DOA estimation is then obtained from TOA estimates at each array element applying a linear estimator. The joint estimation of TOA and DOA provides robustness and potentially allows positioning with a single reference node. Furthermore, the paper derives the Cramer-Rao Lower Bound from a frequency domain signal model for a multipath channel where no assumptions are made with respect to the paths, which results in a compact closed form.