In recent years, the wireless data traffic grew exponentially, which was further accompanied by an increasing demand for higher data rates. Towards this aim, Terahertz band (0.1-10 THz) communication is envisioned as one of the key wireless technologies of the next decade. The THz band will help to overcome the spectrum scarcity problems and capacity limitations of current wireless networks, by providing an unprecedentedly large bandwidth. In addition, THz band communication will enable a plethora of long-awaited applications ranging from instantaneous massive data transfer among nearby devices in ultra-high-speed wireless personal and local area networks, to ultra-high-definition content streaming over mobile devices in 5G and beyond small cells. The objective of the thesis is to establish the physical layer foundations of the ultra- broadband communication in the THz band. First, a unified multi-path propagation channel is modeled in the THz band, based on ray-tracing techniques. The wideband characterization are analyzed, which include the distance-varying spectral windows, the delay spread, the wideband capacity and the temporal broadening effects. Second, a multi-wideband waveform design for the THz band is proposed to improve the distance and support ultra- high-speed transmissions. Third, two algorithms for timing acquisition in the pulse-based wireless systems are developed, namely the low-sampling-rate (LSR) algorithm, and the maximum likelihood (ML)-based approach. Fourth, the distance-aware bandwidth resource allocation schemes for the single-user and multi-user THz band networks are developed. Fifth, a three-dimensional (3-D) end-to-end model is developed and characterized, which includes the responses of the graphene-based reflectarray antenna and the 3-D multi-path propagation. The provided physical layer analysis in this thesis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the THz band.

Nanotechnology is providing a new set of tools to the engineering community to design nanoscale components with unprecedented functionalities. The integration of several nano-components into a single entity will enable the development of advanced nanomachines. Nanonetworks, i.e., networks of nanomachines, will enable a plethora of applications in the biomedical, environmental, industrial and military fields. To date, it is still not clear how nanomachines will communicate. The miniaturization of a classical antenna to meet the size requirements of nanomachines would impose the use of very high radiation frequencies. The available transmission bandwidth increases with the antenna resonant frequency, but so does the propagation loss. Due to the expectedly very limited power of nanomachines, the feasibility of nanonetworks would be compromised if this approach were followed. Therefore, a new wireless technology is needed to enable this paradigm. The objective of this thesis is to establish the foundations of graphene-enabled electromagnetic communication in nanonetworks. First, novel graphene-based plasmonic nano-antennas are proposed, modeled and analyzed. The obtained results point to the Terahertz Band (0.1-10 THz) as the frequency range of operation of novel nano-antennas. For this, the second contribution in this thesis is the development of a novel channel model for Terahertz Band communication. In addition, the channel capacity of the Terahertz Band is numerically investigated to highlight the potential of this still-unregulated frequency band. Third, a novel modulation based on the transmission of femtosecond-long pulses is proposed and its performance is analyzed.% in terms of achievable information rates. Fourth, the use of low-weight codes to prevent channel errors in nanonetworks is proposed and investigated. Fifth, a novel symbol detection scheme at the receiver is developed to support the proposed modulation scheme. Sixth, a new energy model for self-powered nanomachines with piezoelectric nano-generators is developed. Moreover, a new Medium Access Control protocol tailored to the Terahertz Band is developed. Finally, a one-to-one nano-link is emulated to validate the proposed solutions.

Nous avons proposé nanocode bloc simple pour assurer la fiabilité des communications nano. Nous proposons également la compression d'image simple, efficace de l'énergie pour les communications nano. Nous étudions les performances des méthodes proposées en termes d'efficacité énergétique, le taux d'erreur binaire et de robustesse contre les erreurs de transmission. Dans la compression d'image pour les communications nano, nous comparons notre méthode proposée SEIC avec compression standart images des méthodes telles que JPEG, JPEG 2000, GIF et PNG. Les résultats montrent que notre méthode proposée surpasse les méthodes de compression d'image standard dans la plupart des indicateurs. Dans la compression d'erreur pour les communications nano, nous proposons nanocode de simple bloc (SBN) et comparer la performance avec le code de correction d'erreur existant pour nanocommunication, tels que Canal Minimum Energy (MEC) et le faible poids de la Manche (LWC) codes. Le résultat montre que notre méthode proposée surpasse MEC et LWC en termes de fiabilité et de la complexité du matériel. / We proposed nanocode single block to ensure the reliability of nano communications. We also offer the simple image compression, power efficient for nano communications. We study the performance of the proposed methods in terms of energy efficiency, bit error rate and robustness against transmission errors. In image compression for nanocommunications, we compare our proposed method SEIC with standart compression image methods such as JPEG, JPEG 2000, GIF and PNG. The results show that our proposed method outperforms standard image compression methods in most metrics. In error compression for nanocommunications, we propose simple block nanocode (SBN) and compare the performance with existing error correction code for nanocommunication, such as Minimum Energy Channel (MEC) and Low weight Channel (LWC) codes. The result show that our proposed method outperforms MEC and LWC in terms of reliability and hardware complexity.