Approved for public release; distribution is unlimited. / In military operations, covertness of operation is of paramount importance. The transmission power of the data link must be kept to the minimum to maintain a low probability of detection (LPD) from the adversary. However, a reduction in the transmitted power implies a reduction in the operating range, though the detection range by the enemy is also reduced. Therefore, to reduce the enemy’s detection range while maintaining operating distance, this thesis explores strategies to discriminate gain against an adversary’s sensor. The strategies involve using processing gain, directional antennas, polarization and the natural environment as a transmission shield. The processing gain strategy analyzed in this thesis uses a diversity technique called Maximal Ratio Combining (MRC) applied to an IEEE 802.16a link. Sinclair D. Smith carried out a study on the possible processing gain derivable from this technique and this thesis will bring his results to practical applications via link analyses. In the event that the link is detected and the enemy decides to carry out jamming, the thesis explores a possible anti-jamming (AJ) strategy by using MRC and a directional antenna. Daniel P. Zastrow carried out a study on the AJ capability of MRC and this thesis brings his results to practical applications via link analyses. / Major, Republic of Singapore Airforce

The ever-increasing demand for private and sensitive data transmission over wireless networks has made security a crucial concern in the current and future large-scale, dynamic, and heterogeneous wireless communication systems. To address this challenge, wireless researchers have tried hard to continuously analyze the jamming threats and come up with improved countermeausres. In this research, we have analyzed the jamming-vulnerabilities of the leading multi-carrier communication systems, Orthogonal Frequency Division Multiplexing (OFDM) and Single-Carrier Frequency Division Multiple Access (SC-FDMA). In order to lay the necessary theoretical groundwork, first we derived the analytical BER expressions for BPSK/QPSK and analytical upper and lower bounds for 16-QAM for OFDMA and SC-FDMA using Pilot Symbol Assisted Channel Estimation (PSACE) techniques in Rayleigh slow-fading channel that takes into account channel estimation error as well as pilot-jamming effect. From there we advanced to propose more novel attacks on the Cyclic Prefix (CP) of SC-FDMA. The associated countermeasures developed prove to be very effective to restore the system. We are first to consider the effect of frequency-selectivity and fading correlation of channel on the achievable rates of the legitimate system under pilot-spoofing attack. With respect to jamming mitigation techniques, our approaches are more focused on Anti-Jamming (AJ) techniques rather than Low Probability of Intercept (LPI) methods. The Channel State Information (CSI) of the two transceivers and the CSI between the jammer and the target play critical roles in ensuring the effectiveness of jamming and nulling attacks. Although current literature is rich with different channel estimation techniques between two legitimate transceivers, it does not have much to offer in the area of channel estimation from jammer's perspective. In this dissertation, we have proposed novel, computationally simple, deterministic, and optimal blind channel estimation techniques for PSK-OFDM as well as QAM-OFDM that estimate the jammer channel to the target precisely in high Signal-to-Noise (SNR) environment from a single OFDM symbol and thus perform well in mobile radio channel. We have also presented the feasibility analysis of estimating transceiver channel from jammer's perspective at the transmitter as well as receiver side of the underlying OFDM system. / Ph. D. / Susceptibility to interferences is one of the major inherent vulnerabilities of open and pervasive wireless communications systems. The recent trends to more and more decentralized and ad-hoc communication systems that allow various types of network mobile terminals to join and leave simply add to this susceptibility. As these networks continue to flourish worldwide, the issues of privacy and security in wireless communication networks have become a major research problem. The increasingly severe hostile environments with advanced jamming threats has prompted the corresponding advancement in jamming detection and mitigation techniques. This dissertation has analyzed the jamming-vulnerabilities of the leading multi-carrier communication systems of the modern world. We have designed some novel jamming attacks and the corresponding countermeasures. The performance of these novel more-effective techniques are compared with their less-effective conventional counterparts. The information of the channel between the legitimate transmitter-receiver pair and between the jammer and the target play critical roles in ensuring the effectiveness of these smart jamming attacks. Although current literature is rich with different channel estimation techniques between the legitimate pair, it does not have much to offer in the area of channel estimation from jammer’s perspective. In this dissertation, we have proposed novel channel estimation techniques from jammer’s perspective.

OFDM is a promising technique for high-data-rate wireless communications because it can combat inter-symbol interference (ISI) caused by the dispersive fading of wireless channels. The proposed research focuses on techniques that improve the performance of OFDM-based wireless communications and its commercial and military applications. In particular, we address the following aspects of OFDM: inter-channel interference (ICI) suppression, interference suppression for clustered OFDM, clustered OFDM based anti-jamming modulation, channel estimation for MIMO-OFDM, MIMO transmission with limited feedback. For inter-channel interference suppression, a frequency domain partial response coding (PRC) scheme is proposed to mitigate ICI. We derive the near-optimal weights for PRC that is independent on the channel power spectrum. The error floor resulting from ICI can be reduced significantly using a two-tap or a three-tap PRC. Clustered OFDM is a new technique that has many advantages over traditional OFDM. In clustered OFDM systems, adaptive antenna arrays are used for interference suppression. To calculate weights for interference suppression, we propose a polynomial-based parameter estimator to combat the severe leakage of the DFT based estimator due to the small size of the cluster. An adaptive algorithm is developed to obtain optimal performance. For high data rate military communications, we propose a clustered OFDM base spread spectrum modulation to provide both anti-jamming and fading suppression capability. We analyze the performance of uncoded and coded system. Employing multiple transmit and receive antennas in OFDM systems (MIMO-OFDM) can increase the spectral efficiency and link reliability. We develop a minimum mean-square-error (MMSE) channel estimator that takes advantage of the spatial-frequency correlations in MIMO-OFDM systems to minimize the estimation error. We investigate the training sequence design and two optimal training sequence designs are given for arbitrary spatial correlations. For a MIMO system, the diversity and array gains can be obtained by exploiting channel information at the transmitter. For MIMO-OFDM systems, we propose a subspace tracking based approach that can exploit the frequency correlations of the OFDM system to reduce the feedback rate. The proposed approach does not need recalculate the precoding matrix and is robust to multiple data stream transmission.

Wireless signal transmission underpins crucial aspects of modern communication, but its susceptibility to jamming and spoofing attacks remains a major concern. These attacks have the potential to disrupt vital services, mislead devices, and compromise the integrity of wireless systems. Many researchers have addressed anti-jamming and anti-spoofing techniques. Anti-jamming methods include coding techniques, specialized waveforms (e.g., spreading, beamforming, and modulation), and spatial avoidance using relays or reflectors. Anti-spoofing methods include angle-of-arrival detection with antenna arrays, cross-checking with sensor fusion, and authentication and encryption. In recent decades, artificial intelligence and machine learning have boosted the research in anti-jamming and anti-spoofing, making them more flourish. Despite these advancements, significant challenges persist. For example, while various jamming resistance studies were proposed, their application to vulnerable 5G and narrowband Internet of Things (NB-IoT) communications are unexplored. Additionally, while low-density sparse coding (LDSC) is advantageous for multiplexing and spreading, research into the design of the code itself is lacking. Furthermore, sidelinks, a key component of 5G Advanced and future generation communication, hold the potential to become stealthy, secure channels for countering jamming attacks. As for machine learning based methods, they are limited in theoretical and simulation, instead of applied to commercial ready codebases. In GPS anti-spoofing, existing solutions are often expensive, bulky, or low in accuracy, while authentication and encryption approaches remain restricted to military use. Furthermore, although distributed mobile spoofer analysis has been theoretically explored, it still lacks real-world implementation studies. Recognizing the increasing complexity of the wireless landscape, this thesis addresses these open problems through multiple works targeting anti-jamming and anti-spoofing. The first work develops a standard-compliant spread spectrum waveform for NB-IoT applications under jamming. The next focuses on LDSC design, applying it to spreading, and devising methods to obtain sub-optimal LDSC designs against interference. Another work proposes a secure, stealthy sidelink underlay channel and develops interference cancellation methods for flexibility and resilience. In the last work of anti-jamming, a machine learning based interference mitigation solution was proposed, running on open sourced industrial standard, narrowing the gap between academic and real world implementation. On the GPS anti-spoofing front, the first work presents a low-cost, smartphone-based spoofing detection solution matching the accuracy of antenna-array methods. The next work leverages crowdsourcing and sensor fusion, enabling high-accuracy and low-latency anti-spoofing. Finally, the thesis implements conceptual distributed GPS spoofer using low-cost software-defined radios (SDRs), addressing multi-spoofer challenges. Overall, this work offers vital contributions to the security and resilience of wireless signal transmission. The techniques and solutions presented provide powerful approaches to counteract malicious attacks, fostering reliable communication in an increasingly connected world. Looking ahead, AI and ML hold immense potential for further innovation, bolstering security in 5G and future generation networks. / Doctor of Philosophy / Our phones, cars, navigation systems, and countless other devices rely on invisible wireless signals to work. But what happens when these signals are intentionally disrupted or manipulated? Jamming attacks can cut off vital communication, and spoofing tricks devices into giving false information, leading to mishaps and even security breaches. This research is dedicated to making wireless communication more secure and reliable. We explored ways to design smarter wireless signals that can resist jamming, even in challenging environments. This includes technologies specifically tuned for smart sensors and other devices within the "Internet of Things," which connects everyday objects to the internet. Additionally, we developed techniques to hide important messages within existing wireless transmissions, making them harder for attackers to detect or disrupt. Finally, we created accessible ways to protect navigation systems (like GPS) from spoofing, helping ensure they give accurate information for safer journeys. This work aims to protect the wireless systems we use every day from interference and deception. As smart devices continue to fill our world, research like this will become increasingly important to ensure these technologies work safely and reliably. Looking ahead, the next stages of this work will use powerful artificial intelligence to anticipate and neutralize wireless security threats, safeguarding the connected future.

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