Narrowband Interference Suppression in Wireless OFDM Systems

Signal distortions in communication systems occur between the transmitter and the receiver; these distortions normally cause bit errors at the receiver. In addition interference by other signals may add to the deterioration in performance of the communication link. In order to achieve reliable communication, the effects of the communication channel distortion and interfering signals must be reduced using different techniques. The aim of this paper is to introduce the fundamentals of Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple Access (OFDMA), to review and examine the effects of interference in a digital data communication link and to explore methods for mitigating or compensating for these effects

A new non-linear system for estimating and suppressing narrowband interference in PN spread spectrum modulation

This work develops a novel dynamic fuzzy logic system that, based on a fuzzy basis function expansion, successfully solves the non-linear problem of narrowband interference prediction and rejection in DS-SS. A fuzzy basis function representation provides a natural framework for combining both numerical and linguistic information in a uniform fashion. The result is a low complexity non-linear adaptive line enhancer, which offers a faster convergence rate and an overall better performance over other well-known non-linear line enhancers.Peer ReviewedPostprint (published version

GPS Interference Mitigation Using Derivative-free Kalman Filter-based RNN

The global positioning system (GPS) with accurate positioning and timing properties has become integral part of all applications around the world. Radio frequency interference can significantly decrease the performance of GPS receivers or even completely prohibit the acquisition or tracking of satellites. The approaches of system performances that can be further enhanced by preprocessing to reject the jamming signal will be investigated. A recurrent neural network (RNN) predictor for the GPS anti-jamming applications will be proposed. The adaptive RNN predictor is utilized to accurately predict the narrowband waveform based on an unscented Kalman filter (UKF)-based algorithm. The UKF algorithm as a derivative-free alternative to the extended Kalman filter (EKF) in the framework of state-estimation is adopted to achieve better performance in terms of convergence rate and quality of solution. The adaptive RNN filter can be successfully applied for the suppression of interference with a number of different narrowband formats, i.e. continuous wave interference (CWI), multi-tone CWI, swept CWI and pulsed CWI, to emulate realistic circumstances. Simulation results show that the proposed UKF-based scheme can offer the superior performances to suppress the interference over the conventional methods by computing mean squared prediction error (MSPE) and signal-to-noise ratio (SNR) improvements

Intercarrier Interference Suppression for the OFDM Systems in Time-Varying Multipath Fading Channels

Due to its spectral efficiency and robustness over the multipath channels, orthogonal frequency division multiplexing (OFDM) has served as one of the major modulation schemes for the modern communication systems. In the future, the wireless OFDM systems are expected to operate at high carrier-frequencies, high speed and high throughput mobile reception, where the fasting time-varying fading channels are encountered. The channel variation destroys the orthogonality among the subcarriers and leads to the intercarrier interference (ICI). ICI poses a significant limitation to the wireless OFDM systems. The aim of this dissertation is to find an efficient method of providing reliable communication using OFDM in the fast time-varying fading channel scenarios. First, we investigate the OFDM performance in the situation of time-varying mobile channels in the presence of multiple Doppler frequency shifts. A new mathematical framework of the ICI effect is derived. The simulation results show that ICI induces an irreducible error probability floor, which in proportional to the Doppler frequency shifts. Furthermore, it is observed that ICI power arises from a few adjacent subcarriers. This observation motivates us to design the low-complexity Q-tap equalizers, namely, Minimum Mean Square Error (MMSE) linear equalizer and Decision Feedback (DF) non-linear equalizer to mitigate the ICI. Simulation results show that both Q-tap equalizers can improve the system performance in the sense of symbol error rate (SER). To employ these equalizers, the channel state information is also required. In this dissertation, we also design a pilot-aided channel estimation via Wiener filtering for a time-varying Wide-sense Stationary Uncorrelated Scatterers (WSSUS) channel model. The channel estimator utilizes that channel statistical properties. Our proposed low-complexity ICI suppression scheme, which incorporates the Q-tap equalizer with our proposed channel estimator, can significantly improve the performance of the OFDM systems in a fast time-varying fading channels. At the last part of the dissertation, an alternative ICI mitigation approach, which is based on the ICI self-cancellation coding, is also discussed. The EM-based approach, which solves the phase and amplitude ambiguities associated with this approach, is also introduced

Advanced array processing techniques and systems

Research and development on smart antennas, which are recognized as a promising technique to improve the performance of mobile communications, have been extensive in the recent years. Smart antennas combine multiple antenna elements with a signal processing capability in both space and time to optimize its radiation and reception pattern automatically in response to the signal environment. This paper concentrates on the signal processing aspects of smart antenna systems. Smart antennas are often classified as either switched-beam or adaptive-array systems, for which a variety of algorithms have been developed to enhance the signal of interest and reject the interference. The antenna systems need to differentiate the desired signal from the interference, and normally requires either a priori knowledge or the signal direction to achieve its goal. There exists a variety of methods for direction of arrival (DOA) estimation with conflicting demands of accuracy and computation. Similarly, there are many algorithms to compute array weights to direct the maximum radiation of the array pattern toward the signal and place nulls toward the interference, each with its convergence property and computational complexity. This paper discusses some of the typical algorithms for DOA estimation and beamforming. The concept and details of each algorithm are provided. Smart antennas can significantly help in improving the performance of communication systems by increasing channel capacity and spectrum efficiency, extending range coverage, multiplexing channels with spatial division multiple access (SDMA), and compensating electronically for aperture distortion. They also reduce delay spread, multipath fading, co-channel interference, system complexity, bit error rates, and outage probability. In addition, smart antennas can locate mobile units or assist the location determination through DOA and range estimation. This capability can support and benefit many location-based services including emergency assistance, tracking services, safety services, billing services, and information services such as navigation, weather, traffic, and directory assistance