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Passive radars based on long-term evolution (LTE) signals suffer from sever interferences. The interferences are not only from the base station used as the illuminator of opportunity (BS-IoO), but also from the other co-channel base stations (CCBS) working at the same frequency with the BS-IoO. Because the reference signals of the co-channel interferences are difficult to obtain, cancellation performance degrades seriously when traditional interference suppression methods are applied in LTE-based passive radar. This paper proposes a cascaded cancellation method based on the spatial spectrum cognition of interference. It consists of several cancellation loops. In each loop, the spatial spectrum of strong interferences is first recognized by using the cyclostationary characteristic of LTE signal and the compressed sensing technique. A clean reference signal of each interference is then reconstructed according to the spatial spectrum previously obtained. With the reference signal, the interferences are cancelled. At the end of each loop, the energy of the interference residual is estimated. If the interference residual is still strong, then the cancellation loop continues; otherwise it terminates. The proposed method can get good cancellation performance with a small-sized antenna array. Theoretical and simulation results demonstrate the effectiveness of the proposed method.

This study presents the space–time snapshot models for the interfering passive signals received by the airborne passive radar which uses a ground-based stationary non-cooperative transmitter. The random range sidelobes couplings of the direct path and of the strong clutter signals into further range cells are major concerns in moving target detection performance. The least squares-based adaptive interference cancellation technique is proposed to efficiently suppress the direct path, strong clutter and Doppler-shifted strong clutter signals present at each antenna element prior to matched filter processing. In mitigating the interfering signals, their corresponding random range sidelobes will also be suppressed by the same amount. Ground-based moving passive radar trials were conducted to validate and ascertain the effectiveness of the proposed adaptive interference cancellation algorithm.

A hybrid space–time adaptive processing (STAP) approach of the direct data domain (DDD) algorithm and adaptive localised domain transformation is proposed for discrete interference suppression in non‐homogeneous clutter which is inevitable in actual airborne radar applications. In the proposed method, the adaptive localised domain transformation matrix is firstly formed by the DDD weighting vectors in angle‐Doppler directions to suppress discrete interference. Afterwards, the adaptive localised domain transformation matrix is applied to the conventional STAP method to suppress the residual clutter. The proposed method is verified based on the actual airborne radar data.

One of the primary technical challenges facing magnetoencephalography (MEG) is that the magnitude of neuromagnetic fields is several orders of magnitude lower than interfering signals. Recently, a new type of sensor has been developed – the optically pumped magnetometer (OPM). These sensors can be placed directly on the scalp and move with the head during participant movement, making them wearable. This opens up a range of exciting experimental and clinical opportunities for OPM-based MEG experiments, including paediatric studies, and the incorporation of naturalistic movements into neuroimaging paradigms. However, OPMs face some unique challenges in terms of interference suppression, especially in situations involving mobile participants, and when OPMs are integrated with electrical equipment required for naturalistic paradigms, such as motion capture systems. Here we briefly review various hardware solutions for OPM interference suppression. We then outline several signal processing strategies aimed at increasing the signal from neuromagnetic sources. These include regression-based strategies, temporal filtering and spatial filtering approaches. The focus is on the practical application of these signal processing algorithms to OPM data. In a similar vein, we include two worked-through experiments using OPM data collected from a whole-head sensor array. These tutorial-style examples illustrate how the steps for suppressing external interference can be implemented, including the associated data and code so that researchers can try the pipelines for themselves. With the popularity of OPM-based MEG rising, there will be an increasing need to deal with interference suppression. We hope this practical paper provides a resource for OPM-based MEG researchers to build upon.

This work considers a code division multiple access (CDMA)-based femtocell system where a fixed set of subscribed users communicate simultaneously to a femtocell access point (FAP) in an asynchronous fashion during the uplink. The main goal of this paper is to present an augmentation protocol for the physical layer of the CDMA2000 femtocell standard with focus on the multiple access interference (MAI) suppression. The above-closed access femtocell uses a unique set of cyclic orthogonal binary codes to eliminate the MAI caused by packet collisions. This property ensures that the time and data rate asynchronicity of active nodes in a femtocell produces a zero MAI situation at the FAP. The work investigates the optimality and the effectiveness of such codes in femtocells from the link bit error rate performance in a practical Rayleigh-fading environment, where Kalman filtering is used at the FAP for the channel estimation. Theoretical findings are verified by simulation evaluations and it is shown numerically a significant improvement in the performance of the proposed scheme when compared with conventional non-cyclic orthogonal codes in a Rayleigh-fading channel in the asynchronous femtocell.

A novel and simple algorithm capable of extracting and cancelling harmonic disturbance from signals subject to severe power line interference is presented. The key element consists of the adaptation of a filter to a deterministic harmonic reference closely correlated to the interference. The resulting signal is optimal in the mean squared error sense. Simulation results show that this carefully crafted adaptive scheme can improve by up to 30 dB the signal to interference ratio. Minimal remaining interference and fast convergence are obtained by optimisation of the algorithm's parameters.

This study focuses on the design of downlink transmission protocols in multi-cell multi-user mobile networks, where co-channel interference has been recognised as a challenging issue particularly for the users close to the boundary of cells. The key idea of this study is to jointly apply interference alignment (IA) and pre-cancellation to the addressed scenario, where the former technique can effectively increase the overall system throughput and the latter can significantly boost the diversity gains and reception reliability. To ensure the diversity gains can be achieved with zero-forcing IA, a precoder optimisation scheme is proposed based on the well-known iterative interference leakage minimisation scheme. Both analytic and numerical results have been developed to show the capacity and diversity gains obtained by using the proposed scheme. Besides, the computational complexity of the proposed scheme and the effects of imperfect channel state information on the performance are studied as well.

Power amplifiers are one of the costly devices in wireless communication systems and exhibit non-linearity. The problem of non-linearity in the power amplifier categorises in two disturbance impacts, output distortion and in-band distortion which lead to adjacent channel interference and constellation deviation, respectively. In order to gain maximum efficiency of the power amplifier and reduce interference, the authors propose a new digital pre-distortion scheme called complex gain convergence (CGC). The proposed scheme is compared with indirect learning architecture and validated against an laterally diffused metal oxide semiconductor (LDMOS) power amplifier. The outcome of applying CGC scheme shows enhancement in adjacent channel leakage ratio and error vector magnitude performance while the complexity is even lower. An experimental demonstration with the actual power amplifier is also presented.

The wide-scale deployment of radars, distributed across a platform and across multiple platforms for reliable 360° situational awareness (SA), introduces the challenge of radar interference. Interference can broadly be categorised as self-interference (between radars mounted on the same platform) and mutual interference (signals received from radars on other platforms). Both types of interference impede the reliability of SA delivered by such systems, particularly in dense environments where numerous radars operate simultaneously within the same frequency band. This work presents a comprehensive evaluation of a multi-modal beamforming approach that combines unfocused synthetic aperture radar with the traditional Multiple-Input, Multiple-Output beamformer to enhance radar resolution and suppress interference. Additionally, various aspects of sensor configurations defining hardware and software capabilities of state-of-the-art radars are discussed, and a systematic analysis of signal-to-interference-plus-noise ratio at each step of the processing is presented. Extensive simulations and experimental results in both automotive and maritime environments are shown to validate the effectiveness of the proposed approach.

To suppress co-channel interference in polarisation-enabled wireless communication systems, this work aims to provide an interference suppression scheme by exploiting polarisation domain, besides the state-of-the-art temporal, frequency, spatial and code domains. System models, algorithms, characteristics and applications of polarisation filtering (PF) for co-channel interference suppressions for polarisation-enabled (e.g. orthogonal dually polarised antennas) wireless communications are investigated. Specifically, four system models for PF using subspace analysis are established and discussed. The four proposed system models are categorised based on different statistic characteristics of the target signal and that of the interfering signal: both the target signal and interference are temporal deterministic, the target signal is deterministic whereas interference is temporal random, the target signal is random whereas interference is deterministic and both the target signal and interference are random, respectively. Based on the statistic characteristics and subspace theory, the detailed PF implementation for each model is analysed and the closed-form filtering operator is given. It is also shown that the PF implementation for each model can be attained by using one of the zero-forcing matched subspace processing, decorrelating matched subspace processing or Wiener subspace processing. Furthermore, relationship among these four models indicates that, under certain conditions, the implementation of the other three models can be fulfilled by using the implementation of the first model. Numerical and simulation results show the effectiveness of the proposed scheme.