Interference Suppression Filter Research Articles

Impact of Liquid Crystal Based Interference Mitigation and Precoding on the Multiuser Performance of VLC Massive MIMO Arrays

In visible light communication systems, the ability to suppress interference caused by other light sources is a major benefit towards performance improvements. Especially for large transmitter arrays or even multi-cell arrangements, the interference problem needs to be handled. In previous work, we have presented a liquid crystal display (LCD) used as an adaptive interference-suppression filter mounted in front of each photodetector. The display elements are switched on and off in such a way that light emitted by unwanted light sources ideally is blocked, but light emitted by desired light sources reaches the detector. The pattern generated by the LC display has strong impact on the system performance. In this paper, we propose combined precoding in conjunction with LCD-based interference suppression in order to increase the signal-to-interference-plus-noise ratio and to ensure user fairness in massive MIMO scenarios. The suggested precoding strategy uses a new heuristic optimization approach based on the Santa Claus problem on unrelated machines known from computer sciences, and employs only binary entries in the weighting matrix. Corresponding results are compared with a genetic evolutionary optimization strategy and with conventional zero-forcing precoding. Regarding performance evaluation, we perform numerical ray-tracing simulations and present a room-scale VLC testbed for experimental verification.

Bayes-Optimal Convolutional AMP

This paper proposes Bayes-optimal convolutional approximate message-passing (CAMP) for signal recovery in compressed sensing. CAMP uses the same low-complexity matched filter (MF) for interference suppression as approximate message-passing (AMP). To improve the convergence property of AMP for ill-conditioned sensing matrices, the so-called Onsager correction term in AMP is replaced by a convolution of all preceding messages. The tap coefficients in the convolution are determined so as to realize asymptotic Gaussianity of estimation errors via state evolution (SE) under the assumption of orthogonally invariant sensing matrices. An SE equation is derived to optimize the sequence of denoisers in CAMP. The optimized CAMP is proved to be Bayes-optimal for all orthogonally invariant sensing matrices if the SE equation converges to a fixed-point and if the fixed-point is unique. For sensing matrices with low-to-moderate condition numbers, CAMP can achieve the same performance as high-complexity orthogonal/vector AMP that requires the linear minimum mean-square error (LMMSE) filter instead of the MF.

Radio frequency interference suppression filters design for HF radar based on SOCP

High-frequency radar is easily affected by radio frequency interference (RFI) since it shares the band with many radio services. To mitigate the RFIs, this study designs receiver for radar's fast-time processing. Two optimisation problems are, respectively, proposed, both involving an objective function accounting for maximising the signal-to-interference plus noise ratio, but are distinguished with different constrains for sidelobes control. Furthermore, the authors show that the two proposed problems both can be reformulated as the second-order cone programming, hence some well-established interior point methods can be introduced to resolve them. Simulation results show that the designed filters can precisely control the sidelobe level from different perspectives, with the RFIs suppressed to achievable greatest extent.

Autoregression filters for interference suppression in atmosphere acoustic sounding systems

The models of autoregression are built and parametric spectra of acoustic noise, which take place during the operation of acoustic sounding systems in conditions of airport operation, are analyzed. Special attention is paid to the synthesis of autoregressive prediction filters for interference suppression. The values of the suppression coefficients are obtained by autoregressive filters for predicting acoustic noise generated by airplanes.

Joint Algorithm Based on Interference Suppression and Kalman Filter for Bearing-Only Weak Target Robust Tracking

Aiming at the problems in the bearing-only tracking (BOT) of underwater weak target in the presence of interferers, such as discontinuity of tracking trajectory and target loss, a novel joint algorithm based on interference suppression (IS) and Kalman filter (ISKF) is proposed in this paper. In the proposed algorithm, in order to smooth the corrupted trajectory of weak target and improve the precision of tracking, a feedback structure which connects IS module and Kalman filter (KF) module is built. Furthermore, the feedback structure renders the measured results of bearing trajectory shareable mutually between IS module and KF module in real-time. In ISKF joint algorithm, IS module is employed as a preprocessing module to eliminate the power of interferers, and KF module is employed as tracker to obtain the bearing trajectory of weak target. In the initial step, the coarse target bearing and interference bearing are estimated using the conventional beamforming (CBF) method. In the updated step, the precise BOT trajectory of weak target is jointly updated using IS and KF. Moreover, when the target intersects with the interference, the ISKF joint algorithm can still track the weak target effectively with the aid of prediction model of KF. Finally, the sea trial results show that the proposed algorithm can achieve more accurate and robust real-time tracking than KF only, which benefits from the feedback between the IS module and the KF module.

Improvement of precision and accuracy of temperature imaging in sooting flames using two-line atomic fluorescence (TLAF)

Severe interference to the fluorescence signal from seeded indium has previously limited the application of current non-linear excitation regime two-line atomic fluorescence (NTLAF) to low sooting flames. The present paper reports new details of these interferences, from spatially- and temporally-resolved spectral measurements in a laminar, non-premixed sooting C2H4 flame burning in air. Three types of interference to the indium LIF signal have been identified: laser-induced fluorescence (LIF) from polycyclic aromatic hydrocarbons (PAH), elastic laser scattering (ELS) and laser-induced incandescence (LII) from soot particles. This knowledge was used to propose new methods to suppress interferences and select customized narrow-band filters for the signal collection, with a narrow bandwidth of ∼1.2 nm (full-width at half-maximum, FWHM) and a high peak transmission of ∼95%. The efficacy of the narrow-band filters for interference suppression in planar NTLAF measurements was assessed by comparing these measurements with those obtained with a set of conventional band-pass filters (FWHM = 10 nm), in both a soot-free flame and a sooting flame. The application of the narrow-band filters was found to increase both the accuracy and the precision of the temperature measurement, so that measurement accuracy that is due to the presence of interferences has been improved from 198 K to 10 K at a location where the soot volume fraction (fv) is 1.2 ppm. An average reduction of 40% in the standard deviation of measured temperature in single-shot measurements has also been achieved with the use of high transmission filters. With the use of narrow-band filters, NTLAF can be reliably applied in laboratory target sooting flames with peak soot volume fraction of several ppm.

Full MIMO Spatial Filtering Approach for Dynamic Range Reduction in Wideband Cognitive Radios

Wideband cognitive radios (CRs) receive signals from multiple transmitters simultaneously to increase spectrum utilization. Processing a wideband spectrum is challenging due to large dynamic range (DR) of the received signal and required high sampling speed of the ADC. The power consumption of high sampling speed/high-resolution ADCs have been prohibitive for handheld radios. However, in CR applications strong inband signals that pose large DR requirements can be filtered out, since CR needs to detect unused spectrum bands where no signal is present. Spatial domain filtering approaches through use of multiple antennas to reduce DR of the wideband signal are proposed. Algorithms and architectures are developed for vector beamforming (multiple antennas and a single ADC) and full multiple-input multiple-output (MIMO) (multiple antennas with an ADC per antenna) analog spatial filters for adaptive interference suppression. Simulation results indicate that for realistic indoor propagation environments the ADC resolution of an analog beamformer can be reduced by 4 bits when the receiver operates at 2 bits/s/Hz, reducing ADC power consumption by approximately 90%. Moreover, simulations indicate that full MIMO analog spatial filter can reduce ADC resolution with over 3 bits per ADC when the receiver operates at 5 bits/s/Hz, reducing ADC power consumption by approximately 85%.

An influence of parasitic parameters on electromagnetic disturbance emission in voltage converters

In this paper it is estimated an influence of parasitic parameters of elements in converters of different topologies on a spectral components of conducted electromagnetic interference. Scalability of obtained results allows to estimate expected levels of electromagnetic interferences (EMI) from considered converters types, and hence, develop more efficient interference-suppression filters (ISF) for switching-type power supplies (STPS) with less development cost. Results are obtained for frequency band of 0–30 MHz.

Low-Complexity Reduced-Rank Linear Interference Suppression Based on Set-Membership Joint Iterative Optimization for DS-CDMA Systems

This paper presents and analyzes a novel low-complexity reduced-rank linear interference suppression technique for direct-sequence code-division multiple access (DS-CDMA) systems based on the set-membership joint iterative optimization of receive parameters. Set-membership filtering is applied to the design and adaptation of the dimensionality-reducing projection matrix and the reduced-rank interference suppression filter. The specification of error bounds on the projection matrix and reduced-rank filter lead to the formation of two constraint sets from which estimates of the adaptive structures are selected at each time instant. The result is a low-complexity sparsely updating reduced-rank technique that does not require eigendecomposition or subspace tracking procedures. We develop least squares and stochastic gradient-type algorithms and a low-complexity rank-selection algorithm and also devise a time-varying adaptive error bound implementation. We present a stability and mean-square-error convergence analysis of the proposed algorithms along with a study of their complexity. The proposed schemes are applied to interference suppression in the uplink of a multiuser spread-spectrum DS-CDMA system, and the results confirm the validity of the analysis and the effective operation of the schemes. Performance comparisons are given against existing reduced-rank and full-rank algorithms, which act to highlight the improvements obtained by the proposed technique and algorithms.

Interference Suppression Algorithm for SAR Based on Time–Frequency Transform

The goal of this paper is to suppress the narrowband interference (NBI) and wideband interference (WBI) in synthetic aperture radar (SAR) by using a nonparametric method. The method is based on the analysis of time-frequency characteristic of NBI and WBI from which an interference suppression filter combined with the constant false alarm rate algorithm is designed. In this approach, the short-time Fourier transform (STFT) is used to estimate the instantaneous frequency of the SAR echo data with interference. In the STFT domain, the instantaneous frequency spectrum is represented by wavelet, and then, the designed filter filters the corresponding wavelet coefficients of the interference components. In addition, this algorithm is robust to time-varying NBI and WBI. The performance of the proposed approach is evaluated by the simulated and measured data, and the effectiveness is demonstrated.

Highly selective and tunable microwave photonic filter using parallel Fabry–Pérot filters for universal mobile telecommunications system noise and interference suppression

The authors propose a highly selective and tunable microwave photonic filter based on parallel Fabry–Pérot filters with fibre Bragg gratings for delay. The filter is suitable for noise and interference suppression in universal mobile telecommunications system (UMTS) base stations. Simulation results demonstrate the feasibility of these filters in UMTS applications, and also show flexibility in their frequency response. Tunability of the filter has been employed for UMTS channel selection and grating length has been tuned in order to achieve appropriate delay. The filter provides a very high selective performance (in the frequency range of 1937–1976 MHz and a very high-quality factor of 494) with very high sidelobe suppression (>36 dB) in the stop band with lesser number of components. Tunability and reconfigurability of the proposed filter was obtained by changing the grating length. In this way, easy implementation of simple, compact and cost-effective filter has been demonstrated.

Modeling the Effects of Interference Suppression Filters on Ultra-Wideband Pulses

In this paper, we study the effects of interference suppression filters (multiple stopbands) on ultra-wideband (UWB) short pulses. Multiple stopbands of the filter, which is placed in the receiver, affect the UWB pulse amplitude, pulsewidth, and ringing; resulting in reduced signal-to-noise ratio and degradation in receiver performance. An analytical method is proposed in this paper to model the effect of stopbands on the pulse shape. In this paper, the effects of an interference suppression filter on three different Gaussian pulses are studied. Theoretical and measured pulses are compared and found to be in good agreement. The proposed method enables the UWB radio designer to predict the distortion of the received signals after passing through interference suppression filters.

Blind Multiple Access Interference Suppression Algorithm Based on Relaxed Subgradient Projection for DS/CDMA Systems

A novel blind multiple access interference suppression algorithm based on relaxed parallel subgradient projection is proposed for DS/CDMA systems. The qualification “relaxed” is manifest in two aspects: first, the new expression for updating the interference suppression filter coefficients vector relaxes paralleled projection fields and reduces computation complexity. In addition, the relaxation parameter in the updated process is adaptively determined to guarantee the interference suppression filter coefficients vector falling into fields containing the optimal filter coefficients vector after several iterations. Theoretical analysis and simulation results conclude that this algorithm has a fast convergence speed, steady interference suppression performance, low computation and low bit error rate.

Influence of Channel Estimation Error on MIMO Multiplexing Using Precoding in Downlink OFDM Radio Access

This paper investigates the influence of channel estimation error on the precoding matrix selection and signal detection for MIMO multiplexing using precoding in the downlink OFDM radio access. In a simulation, we assume codebook-based unitary precoding and signal detection that employs a minimum mean squared error (MMSE) based interference suppression filter. The simulation results clarify the effect of the channel estimation error with respect to the precoding matrix selection and signal detection from the viewpoints of the number of streams, i.e., rank order, the number of transmit antennas, the modulation scheme and channel coding rate, and codebook size, i.e., quantization for precoding matrix feedback information.

Band structure of a parallel-plate waveguide filter having phase-shifted square-wave corrugations

In this paper, we study the effect of harmonics of phase-shifted square-wave corrugations on the different stopbands of a corrugated parallel-plate waveguide supporting TM waves. The stopbands are characterized by simultaneous occurrence of first-order and higher-order Bragg interactions. Coupled mode equations of two or four modes are derived via the method of multiple scales. Above cutoff of a higher-order mode, it is found that three resonance conditions must be satisfied: a first-order Bragg condition for the higher-order mode and a higher-order Bragg condition for the dominant TM10 mode, and a third condition coupling the two modes. A design of a multiple stopband filter for interference suppression in UWB applications is given showing all stopbands above cutoff of the TM10 and higher-order modes up to TM50 by including effects of higher harmonics of the structure. The bandwidth of each stopband is controllable by varying the phase shift between corrugations on the two walls of the waveguide. The fundamental matrix method is used to solve the filtering problem numerically.

Block diagonalization for multi-user MIMO with other-cell interference

Block diagonalization is one approach for linear preceding in the multiple-input multiple-output broadcast channel that sends multiple interference free data streams to different users in the same cell. Unfortunately, block diagonalization neglects other-cell interference (OCI), which limits the performance of users at the edge of the cell. This paper presents an OCI-aware enhancement to block diagonalization that uses a whitening filter for interference suppression at the receiver and a novel precoder using the interference-plus-noise covariance matrix for each user at the transmitter. For complex Gaussian matrix channels, the asymptotic sum rate of the proposed system is analyzed under a large antenna assumption for isotropic inputs and compared to conventional block diagonalization. The capacity loss due to OCI is quantified in terms of results from single-user MIMO capacity. Several numerical examples compare achievable sum rates, the proposed asymptotic rates, and the capacity loss, in low and high interference regimes.

Integrated RF Interference Suppression Filter Design Using Bond-Wire Inductors

Design techniques are presented for the realization of high-performance integrated interference suppression filters using bond-wire inductors. A new configuration is proposed for mitigating the impact of mutual coupling between the bond wires. A differential low-noise amplifier with an integrated on-chip passive interference suppression filter is designed at 2.1 GHz in a 0.18-mum CMOS process, and achieves a transmit leakage suppression of 10 dB at 190-MHz offset. The differential filter uses metal-insulator-metal capacitors and bond-wire inductors and occupies only 0.22 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The cascaded system achieves a measured gain of 9.5 dB with a 1.6-dB noise figure and -5 dBm out-of-band IIP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> and consumes 11 mA from a 2-V supply.

New approach for suppression of FM jamming in GPS receivers

A new approach is proposed for the suppression of FM jammers in C/A code GPS receivers. This approach is based on the cascading of the augmented-state approximate conditional mean (ASACM) filter and the discrete wavelet transform (DWT) filter. An ASACM filter for single interference suppression in spread-spectrum systems has been reported in the recent literature. However, the formulation of the ASACM filter and its performance analysis is lacking in the case of suppression of multiple FM interferences. The ASACM filter is formulated here for the suppression of multiple FM jammers. Further, a DWT filter using biorthogonal wavelet is suggested for the suppression of FM jammers. Finally, these two filters are cascaded to get an optimum performance for higher jammer to signal ratio, which is of importance in the GPS, for the case of suppression of multiple FM jammers. The performance of the proposed filters is analyzed through simulation examples for the suppression of single and multiple FM jammers in GPS receivers

Design of multiple-stopband filters for interference suppression in UWB applications

A design of multiple-stopband filters is presented for the suppression of interfering signals in UWB applications. Since possible interferers can be located at fixed frequencies or within a defined frequency band, the design of both fixed and tunable narrow stopband filter sections is addressed. For multiple fixed stopband filters, bent resonators, coupled to the main line, are introduced in order to more effectively suppress harmonics. A new tunable tapped stopband section is proposed, which allows the simultaneous control of stopband frequency and bandwidth. The final multiple-stopband design combines fixed and tunable sections and simultaneously suppresses interferences from global system for mobile communication, wireless local area network, worldwide interoperability for microwave access, and industrial-scientific-medical applications. Measurements verify the design process

Subset Parallel Volterra Filter for narrowband interference suppression in DSSS communications

Subset Parallel Adaptive Volterra Filter (SPAVF) design algorithm is proposed in this letter. Contribution factor is introduced in SPAVF, and it can get rid of redundant elements efficiently in the extended input vector. Computational weight can be reduced largely, and BER performance of SPAVF can be improved by getting rid of the influence of redundant elements in the input vector. Simulation result proves its advantage compared to AVF and PSVF.