Robust wireless communications under co-channel interference and jamming

Interference and jamming severely disrupt our ability to communicate by decreasing the effective signal-to-noise ratio and by making parameter estimation difficult at the receiver. The objective of this research work is to design robust wireless systems and algorithms to suppress the adverse effects of non-intentional co-channel interference (CCI) or intentional jamming. In particular, we develop chip-combining schemes with timing, channel, and noise-power estimation techniques, all of which mitigate CCI or jamming. We also exploit the spatial diversity and iterative receiver techniques for this purpose.;Most of the existing timing estimation algorithms are robust against either large frequency offsets or CCI, but not against both at the same time. Hence, we develop a new frame boundary estimation method that is robust in the presence of severe co-channel interference and large carrier-frequency offsets.;To solve the high peak-to-average-power ratio problem of a multicarrier code division multiple access (MC-CDMA) system and enhance its robustness against fading and jamming, we propose a constant-envelope MC-CDMA system employing cyclic delay diversity (CDD) as transmit diversity. We analyze the diversity order, coding gain, and bit-error rate (BER) upper bound for a quasi-static Rayleigh-flat-fading channel. We also propose a blind, accurate, and computationally efficient signal-to-noise ratio (SNR) estimator for the constant-envelope MC-CDMA-CDD system.;A robust anti-jam receiver must be able to suppress partial-band noise jamming and pulse jamming. We propose a configurable receiver that estimates the frequency- or time-domain jammer state information (JSI) and use it for chip combining in the corresponding domain. A soft-JSI-based chip-combining technique is proposed that outperforms conventional hard-JSI-based chip combining. We also derive a chip combiner that provides sufficient statistics to the decoder.;Channel estimation is necessary for coherent signal detection and JSI estimation. Conversely, knowledge of the jamming signal power and JSI of different subcarriers can improve the accuracy of the channel estimates. Hence, we propose joint iterative estimation of the multiple-input multiple-output (MIMO) channel coefficients, jamming power, and JSI for a coded MC-CDMA MIMO system operating under jamming and a time-varying frequency-selective channel. Finally, we reduce the computational complexity of the JSI-based anti-jam receivers by introducing an expectation-maximization (EM)-based joint channel and noise-covariance estimator that does not need either the subcarrier JSI or the individual powers of the AWGN and jamming signal.