An OFDM Signal Identification Method for Wireless Communications Systems

Distinction of OFDM signals from single carrier signals is highly important for adaptive receiver algorithms and signal identification applications. OFDM signals exhibit Gaussian characteristics in time domain and fourth order cumulants of Gaussian distributed signals vanish in contrary to the cumulants of other signals. Thus fourth order cumulants can be utilized for OFDM signal identification. In this paper, first, formulations of the estimates of the fourth order cumulants for OFDM signals are provided. Then it is shown these estimates are affected significantly from the wireless channel impairments, frequency offset, phase offset and sampling mismatch. To overcome these problems, a general chi-square constant false alarm rate Gaussianity test which employs estimates of cumulants and their covariances is adapted to the specific case of wireless OFDM signals. Estimation of the covariance matrix of the fourth order cumulants are greatly simplified peculiar to the OFDM signals. A measurement setup is developed to analyze the performance of the identification method and for comparison purposes. A parametric measurement analysis is provided depending on modulation order, signal to noise ratio, number of symbols, and degree of freedom of the underlying test. The proposed method outperforms statistical tests which are based on fixed thresholds or empirical values, while a priori information requirement and complexity of the proposed method are lower than the coherent identification techniques

On the cyclostationarity of orthogonal frequency division multiplexing and single carrier linear digital modulations: theoretical developments and applications

In recent years, new technologies for wireless communications have emerged. The wireless industry has shown great interest in orthogonal frequency division multiplexing (OFDM) technology, due to the efficiency of OFDM schemes to convey information in a frequency selective fading channel without requiring complex equalizers. On the other hand, the emerging OFDM wireless communication technology raises new challenges for the designers of intelligent radios, such as discriminating between OFDM and single-carrier modulations. To achieve this objective we study the cyclostationarity of OFDM and single carrier linear digital (SCLD) modulated signals. -- In this thesis, we first investigate the nth-order cyclostationarity of OFDM and SCLD modulated signals embedded in additive white Gaussian noise (AWGN) and subject to phase, frequency and timing offsets. We derive the analytical closed-form expressions for the nth-order (q-conjugate) cyclic cumulants (CCs) and cycle frequencies (CFs), and the nth-order (q-conjugate) cyclic cumulant polyspectra (CCPs) of OFDM signal, and obtain a necessary and sufficient condition on the oversampling factor (per subcarrier) to avoid cycle aliasing. An algorithm based on a second-order CC is proposed to recognize OFDM against SCLD modulations in AWGN channel, as an application of signal cyclostationarity to modulation recognition problem. -- We further study the nth-order cyclostationarity of OFDM and SCLD modulated signals, affected by a time dispersive channel, AWGN, carrier phase, and frequency and timing offsets. The analytical closed-form expressions for the nth-order (q-conjugate) CCs and CFs, the nth-order (q-conjugate) CCPs of such signals are derived, and a necessary and sufficient condition on the oversampling factor (per subcarrier) is obtained to eliminate cycle aliasing for both OFDM and SCLD signals. We extend the applicability of the proposed algorithm in AWGN channel to time dispersive channels to recognize OFDM against SCLD modulations. The proposed algorithm obviates the preprocessing tasks; such as symbol timing, carrier and waveform recovery, and signal and noise power estimation. This is of practical significance, as algorithms that rely less on preprocessing are of crucial interest for receivers that operate with no prior information in a non-cooperative environment. It is shown that the recognition performance of the proposed algorithm in time dispersive channel is close to that in AWGN channel. In addition, we have noticed that the performance of recognizing both OFDM and SCLD signals does not depend on the modulation format used on each subcarrier for OFDM and for SCLD signals respectively

Secure OFDM System Design for Wireless Communications

Wireless communications is widely employed in modern society and plays an increasingly important role in people\u27s daily life. The broadcast nature of radio propagation, however, causes wireless communications particularly vulnerable to malicious attacks, and leads to critical challenges in securing the wireless transmission. Motivated by the insufficiency of traditional approaches to secure wireless communications, physical layer security that is emerging as a complement to the traditional upper-layer security mechanisms is investigated in this dissertation. Five novel techniques toward the physical layer security of wireless communications are proposed. The first two techniques focus on the security risk assessment in wireless networks to enable a situation-awareness based transmission protection. The third and fourth techniques utilize wireless medium characteristics to enhance the built-in security of wireless communication systems, so as to prevent passive eavesdropping. The last technique provides an embedded confidential signaling link for secure transmitter-receiver interaction in OFDM systems

Advances in parameter estimation, source enumeration, and signal identification for wireless communications

Parameter estimation and signal identification play an important role in modern wireless communication systems. In this thesis, we address different parameter estimation and signal identification problems in conjunction with the Internet of Things (IoT), cognitive radio systems, and high speed mobile communications. The focus of Chapter 2 of this thesis is to develop a new uplink multiple access (MA) scheme for the IoT in order to support ubiquitous massive uplink connectivity for devices with sporadic traffic pattern and short packet size. The proposed uplink MA scheme removes the Media Access Control (MAC) address through the signal identification algorithms which are employed at the gateway. The focus of Chapter 3 of this thesis is to develop different maximum Doppler spread (MDS) estimators in multiple-input multiple-output (MIMO) frequency-selective fading channel. The main idea behind the proposed estimators is to reduce the computational complexity while increasing system capacity. The focus of Chapter 4 and Chapter 5 of this thesis is to develop different antenna enumeration algorithms and signal-to-noise ratio (SNR) estimators in MIMO timevarying fading channels, respectively. The main idea is to develop low-complexity algorithms and estimators which are robust to channel impairments. The focus of Chapter 6 of this thesis is to develop a low-complexity space-time block codes (STBC)s identification algorithms for cognitive radio systems. The goal is to design an algorithm that is robust to time-frequency transmission impairments