Spectrum Allocation With Adaptive Sub-Band Bandwidth for Terahertz Communication Systems

We study spectrum allocation for terahertz (THz) band communication (THzCom) systems, while considering the frequency and distance-dependent nature of THz channels. Different from existing studies, we explore multi-band-based spectrum allocation with adaptive sub-band bandwidth (ASB) by allowing the spectrum of interest to be divided into sub-bands with unequal bandwidths. Also, we investigate the impact of sub-band assignment on multi-connectivity (MC) enabled THzCom systems, where users associate and communicate with multiple access points simultaneously. We formulate resource allocation problems, with the primary focus on spectrum allocation, to determine sub-band assignment, sub-band bandwidth, and optimal transmit power. Thereafter, we propose reasonable approximations and transformations, and develop iterative algorithms based on the successive convex approximation technique to analytically solve the formulated problems. Aided by numerical results, we show that by enabling and optimizing ASB, significantly higher throughput can be achieved as compared to adopting equal sub-band bandwidth, and this throughput gain is most profound when the power budget constraint is more stringent. We also show that our sub-band assignment strategy in MC-enabled THzCom systems outperforms the state-of-the-art sub-band assignment strategies and the performance gain is most profound when the spectrum with the lowest average molecular absorption coefficient is selected during spectrum allocation.

Automated summary

In this study, spectrum allocation for terahertz band communication systems is explored, taking into account the unique characteristics of THz channels. By dividing the spectrum of interest into sub-bands with unequal bandwidths and investigating the impact of sub-band assignment on multi-connectivity enabled systems, higher throughput can be achieved by enabling and optimizing adaptive sub-band bandwidth. The proposed sub-band assignment strategy outperforms existing strategies, particularly when selecting spectrum with the lowest average molecular absorption coefficient.