SummaryIndoor wireless communication systems are rapidly expanding, creating a growing demand for individual data rates. This paper explores the influence of the indoor source layout on the received signal for future ultrawideband indoor terahertz communication systems. The optimization of the number, distance, and arrangement of sources can improve the indoor signal coverage efficiency and reduce the fluctuation of the signal‐to‐noise ratio (SNR) of each position indoors. The optimization results for the number, distance, and arrangement of sources demonstrate that optimal coverage can be achieved using nine sources with a distance factor of 0.15 in a rectangular arrangement located in the center of the room in an office environment of 15 × 12 × 2.5 m (L × W × H) in size. Increasing the number of sources has little effect on the uniformity of the indoor signal power distribution. Under the optimal coverage, the SNR fluctuation in an empty room can be reduced from 10.77 to 2.5 dB, which guarantees that users can obtain nearly the same communication quality regardless of their location. Moreover, the impact characteristics of two typical wedges fading, namely, fixed shadow objects and moving human bodies, under one or multiple sources are also analyzed. Multisource distribution is found to significantly improve the shadow attenuation effect of wedge fading when there are fixed objects or people walking indoors. In addition, the moving human body attenuation model is extended by combining a Markov process with a ray‐tracing simulation. The results show that the probability of the ideal state under a multisource distribution is significantly higher than that under a single‐source distribution, and it is less influenced by the number of people.

Summary The indoor terahertz sources cause power fluctuation at various locations due to obstacles, which can be avoided by deploying multiple sources, but will lead to high energy consumption. In this paper, the reverse ray‐tracing method is used to establish a terahertz indoor channel. The free path loss, atmospheric absorption, and reflection loss are considered. Adaptive algorithms are adopted to solve the large energy consumption of deploying multiple sources. A weight vector coefficient is used based on the location and received user signal to adjust the transmission power of each terahertz source dynamically. The results show that the adaptive power control of multiple terahertz sources substantially reduces the energy consumption and the signal power fluctuations. For static users, the energy consumption can be reduced by 5 and 9 dB, and the maximum data transmission rate can be increased by one to two times using four and nine sources, respectively. Moreover, energy consumption can be reduced by more than 6 dB for several indoor users. For dynamic users with a changing channel environment, the adaptive algorithm can adjust the source power in real time and improve signal efficiency. However, the efficiency improvement of the algorithm is limited by the distribution of the multiple sources. The energy consumption of four sources with the adaptive algorithm operating in the center of the room is greater than that of nine sources without the adaptive algorithm. Nevertheless, the efficiency of the nine sources with the adaptive algorithm is much higher than that of the four sources.