Terahertz (THz)-band communication is envisioned as a critical technology that could satisfy the need for much higher data rates in sixth generation wireless communi- cation (6G) systems and beyond. Although THz signal propagation suffers from huge spreading and molecular absorption losses that limit the achievable commu- nication ranges, ultra-massive multiple-input multiple-output (UM-MIMO) antenna arrays can introduce the required beamforming gains to compensate for these losses. The reconfigurable UM-MIMO systems of small footprints motivate the use of spatial modulation techniques. Furthermore, the ultra-wideband fragmented THz spectrum motivates the use of index modulation techniques over multicarrier channels. In this thesis, we consider the problem of efficient index mapping and data detection in THz- band index modulation paradigms. We first propose an accurate frequency-domain statistical UM-MIMO channel model for wideband multicarrier THz-band commu- nications by considering THz-specific features. We then propose several THz-band generalized index modulation schemes that provide various performance and complex- ity tradeoffs. We propose efficient algorithms for mapping information bits to antenna and frequency indices at the transmitter side to enhance the achievable data rates in THz channel uses. We further propose complementary low-complexity parameter estimation and data detection techniques at the receiver side that can scale efficiently with very high rates. We derive theoretical bounds on the achievable performance gains of the proposed solutions and generate extensive numerical results promoting the corresponding future 6G use cases.