Bandpass Sampling Theorem Research Articles

Study on weak signal enhancement method in wireless communication under electromagnetic interference environment

In order to overcome the problems of high bit error rate and high signal enhancement time in weak signal enhancement methods, this paper proposes a weak signal enhancement method in wireless communication under electromagnetic interference environment. Firstly, the transmission characteristics of electromagnetic wave are analysed and the attenuation results of electromagnetic wave signal transmission are determined. Then, the bandwidth of weak signal is determined by band-pass sampling theorem, and the key characteristics of weak signal are determined by time-domain characteristic analysis. Finally, the amplitude modulation coefficient is used to adjust the frequency offset and initial phase through a low-pass filter to enhance the weak signal in wireless communication. The experimental results show that the lowest bit error rate of this method is about 1%, the weak signal enhancement time is no more than 2.6 s, and the weak signal enhancement effect is good.

Airborne Acoustic Chirp Spread Spectrum Communication System for User Identification in Indoor Localization

In this contribution, we propose a reliable, longrange, communication system based on chirp spread spectrum techniques for aerial ultrasonic channels, to be employed for user identification in ultrasonic indoor localization systems. We adopt binary orthogonal keying, where the binary information, modulates the shape of the chirp instantaneous frequency, mapping zeros onto down-chirps and ones onto up-chirps. In order to reduce the demodulation computational costs, we exploit the band-pass sampling theorem and develop an ad-hoc algorithm to under-sample the received signal. The incoming packet detection and frame synchronization are guaranteed by employing a characteristic chirp signal, typically utilized for localization purposes, as a pilot for the transmitted identification packet. A simple, yet efficient, pilot detection scheme enables live features by constantly listening to the channel, triggering the demodulator only when the pilot is detected. The performance of our system has been evaluated in low power and ultra-low power real-world experiments in a warehouse-like environment. It is demonstrated that our system is capable of error-free communication up to a range of 22 m in the low power setup, where the transmitter had a transmission power of 80 mW, corresponding to a sound pressure level of approximately 37 dBSPL at 1 m distance. In the ultra-low power mode, with a transmission power to 15 mW, corresponding to a sound pressure level of approximately 29 dBSPL at 1 m, the system achieved 99% success rate up to 16 m. Moreover, the capability of the system to be robust against the Doppler effect and in a multi-user environment has been tested via simulations.

Dual-Polarization Bandwidth-Bridged Bandpass Sampling Fourier Transform Spectrometer from Visible to Near-Infrared on a Silicon Nitride Platform.

On-chip broadband optical spectrometers that cover the entire tissue transparency window (λ = 650–1050 nm) with high resolution are highly demanded for miniaturized biosensing and bioimaging applications. The standard spatial heterodyne Fourier transform spectrometer (SHFTS) requires a large number of Mach–Zehnder interferometer (MZI) arrays to obtain a broad spectral bandwidth while maintaining high resolution. Here, we propose a novel type of SHFTS integrated with a subwavelength grating coupler (SWGC) for the dual-polarization bandpass sampling on the Si3N4 platform to solve the intrinsic trade-off limitation between the bandwidth and resolution of the SHFTS without having an outrageous number of MZI arrays or adding additional active photonic components. By applying the bandpass sampling theorem, the continuous broadband input spectrum is divided into multiple narrow-band channels through tuning the phase-matching condition of the SWGC with different polarization and coupling angles. Thereby, it is able to reconstruct each band separately far beyond the Nyquist criterion without aliasing error or degrading the resolution. We experimentally demonstrated the broadband spectrum retrieval results with the overall bandwidth coverage of 400 nm, bridging the wavelengths from 650 to 1050 nm, with a resolution of 2–5 nm. The bandpass sampling SHFTS is designed to have 32 linearly unbalanced MZIs with the maximum optical path length difference of 93 μm within an overall footprint size of 4.7 mm × 0.65 mm, and the coupling angles of SWGC are varied from 0° to 32° to cover the entire tissue transparency window.

Bandpass Crank–Nicolson form with approximation and absorption for nonreciprocal ferrite material

Due to the unique nonreciprocal characteristic, ferrite exhibits anisotropic behaviour in electric performance. Owing to such special phenomenon, it is difficult to efficiently analyse and simulate the ferrite material. Here, an alternative scheme is proposed for the bandpass ferrite finite-difference time-domain simulation. This algorithm is carried out which is based on approximate Crank–Nicolson procedure and incorporated with the complex method and higher-order formulation. The ferrite material can be calculated by the modified auxiliary differential equation approach according to the bandpass sampling theorem. The introduction of numerical example validates the effectiveness. As shown in the results, the proposed scheme can take advantage of these methods which can be demonstrated from the aspect of accuracy, efficiency and absorption. In addition, the proposed scheme can solve the time increment problem caused by the solution of tri-diagonal matrices during the simulation of implicit algorithms.

BPSK Modulation‐Based Local Oscillator‐Free IQ Demodulation for Millimeter Wave Imaging

The precision of local oscillator (LO) signal in in‐phase and quadrature (IQ) demodulation strongly affects the imaging performance of millimeter wave (mmWave) radars. Therefore, to eliminate the requirement for high‐precision LO, a simple yet effective digital IQ demodulation method has been proposed with the aid of a specified sampling scheme in order to eliminate the demand for LO. Based on the bandpass sampling theorem, the characteristic of the intermediate frequency signal of mmWave imaging indicates that the LO is unrequired if the sampling rate is twice of the frequency of the carrier of the intermediate signal. In this way, the in‐phase signal would be directly and accurately obtained by performing the Binary‐Phase‐Shift‐Keying (BPSK) modulation on the samples, based on which the IQ demodulation would be completed by using the Hilbert transform. The proposed method does not employ LO and thus simplifies the demodulation process and is suitable for implementation in a Field‐Programmable Gate Array (FPGA) with fewer hardware resources. To verify the method, a three‐dimensional mmWave radar imaging is carried out at the 30‐34 GHz bandwidth, where the sampling and digital IQ demodulation are realized by an ADC (AD9250) and FPGA (XC7K325T), respectively. The results show a simplified transceiver with lower requirements and the prospect of the proposed method being applied in radar imaging and other related fields.

Determination of the minimum sampling frequency in bandpass sampling by geometric approach and geometric programming

This paper presents a simple and fast approach to find a minimum sampling frequency for multi-band signals. Instead of neighbor and boundary conditions, constraints on the sampling frequency were derived by using the geometric approach to the bandpass sampling theorem. Reformulation of the constraints on the minimum sampling frequency enabled to represent the problem as an optimization problem which was structured by the geometric programming and mixed-integer nonlinear programming methods. The convex optimization problem was then solved by the proposed algorithm applying interior point approach in the line search framework. It was demonstrated that this unified structure directly linked the geometric approach of the bandpass sampling theorem to the optimization problem. The proposed method was verified through numerical simulations in terms of the minimum sampling frequency and the computational efficiency. Results illustrated the feasibility of the geometric approach and the proposed algorithm in the determination of the minimum sampling frequency by providing the savings in the number of iterations and the decrease in the valid minimum sampling frequency.

Classical sampling theorem in digital holography

It is proposed to change the present paradigm of the sampling theorem, accepted in papers on digital holography, from 'when recording digital hologram, Nyquist criterion should be fulfilled' to 'when recording on-axis digital hologram, low-pass sampling theorem should be fulfilled, and when recording off-axis one, band-pass sampling theorem should be fulfilled'. Experimental and theoretical basis for this proposal is presented.

Research and Design of Digital down Converter Based on Software Defined Radio

This paper makes a brief introduction on the current development trend of software radio and digital down converter status. The basic theoretical knowledge: Band-pass sampling theorem, digital signal orthogonal transformation theory, multi-rate signal processing theory. Based on these theories, use MATLAB complete the design and verification of mixing module, the extraction module (CIC filter, half-band filter and FIR filters), finally verify the correctness of the design, and implement DDC.

Identification of cubically nonlinear systems excited by bandpass inputs

Identification of cubically nonlinear systems excited by bandpass inputs using discrete-time samples of the input and output signals is investigated. When excited by a bandpass signal, a nonlinear system may generate an output signal which occupies multiple frequency bands. Therefore, although the input signal can be bandpass sampled without causing aliasing by following the well known bandpass sampling theorem, the output signal must obey more sophisticated bandpass sampling criteria to avoid aliasing. Specifically, when a cubically nonlinear system is excited by a bandpass input signal whose highest frequency is larger than three times its bandwidth, a proper bandpass sampling frequency without causing aliasing in the sampled output signal must be at least 18 times the bandwidth of the input signal. First a method for identifying the cubically nonlinear system using properly bandpass sampled data is developed. Then a novel method is proposed, which allows identification of the cubically nonlinear system using data sampled at about twice the bandwidth of the input signal, even though aliasing exists in the sampled output under these circumstances. Compared to conventional methods, the proposed methods have the advantage of requiring a lower sampling rate. This makes the proposed methods highly appreciated in situations where high-speed sampling is unattainable.

Design of near perfect reconstruction oversampled filter banks for subband adaptive filters

In this brief, a design algorithm for real-valued and complex-valued oversampled filter banks which yield a low level of inband alias and enable simple subband adaptive structures is presented. The filter banks are either based on complex modulation of a real-valued low-pass prototype or on the direct or modulated setups of real-valued filter banks. If real-valued filter banks are required, then the different channels will have different subsampling ratios so that the bandpass sampling theorem is not violated. This brief also presents design examples of real-valued and complex-valued filter banks.

Practical consideration for bandpass sampling

The uniform bandpass sampling theorem has been modified to cope with sampling frequency instability and carrier frequency variations. Minimum sampling rates for given sampling and carrier frequency variations are derived. A robust bandpass sampling method is proposed which requires the sampling frequency to be such that the carrier frequency is on the 1/4 or –1/4 sampling frequency grid.

Noise in measurements obtained by sampling

Simple signal processing tools are used to describe noise in sampled measurements. Particular attention is paid to aliasing and the modification of noise spectra by the sampling process. The principles discussed are applied to near-optimal measurements of DC and AC signals in noise, and to the measurement of noise power. Specific problems have been chosen to demonstrate novel approaches and to clarify situations where confusion has arisen. Examples include alternative definitions of equivalent noise bandwidth, the bandpass sampling theorem, quantization and dither, the variance in the mean of correlated measurements, the exploitation of anticorrelation in resonant transducers, the ideal averaging filter, the resolution of synchronous demodulators, and sampling demodulators.

Simulation of nonlinear circuits using modified harmonic balance techniques

AbstractThis paper shows a comparative study for two main different approaches of modified harmonic balance techniques. The first modification is based on a broadband sampling theorem and uses simple modifications to the DFT algorithm (called MDFT). The second method is based on a bandpass sampling theorem and is called the controlled aliasing technique.

On Uniform Sampling of Amplitude Modulated Signals

For a bandpass waveform produced by the amplitude modulation of a low-pass signal, it is shown that the corresponding bandpass signal may be recovered from its samples taken at a uniform rate which is equal to or less than half the sampling rate called for in applying the classical bandpass sampling theorem.

On the error in reconstructing a non-bandlimited function by means of the bandpass sampling theorem

On the error in reconstructing a non-bandlimited function by means of the bandpass sampling theorem