# Tethered Balloon Cluster Deployments and Optimization for Emergency Communication Networks
###### Abstract  
Natural disasters can severely disrupt conventional communication systems, hampering relief efforts. High-altitude tethered balloon base stations (HATBBSs) are a promising solution to communication disruptions, providing wide communication coverage in disaster-stricken areas. However, a single HATBBS is insufficient for large disaster zones, and limited resources may restrict the number and energy capacity of available base stations. To address these challenges, this study proposes a cluster deployment of tethered balloons to form flying ad hoc networks (FANETs) as a backbone for post-disaster communications. A meta-heuristic-based multi-objective particle swarm optimization (MOPSO) algorithm is employed to optimize the placement of balloons and power control to maximize target coverage and system energy efficiency. Comparative analysis with a stochastic algorithm (SA) demonstrates that MOPSO converges faster, with significant advantages in determining optimal balloon placement. The simulation results show that MOPSO effectively improves network throughput while reducing average delay and packet loss rate.  
emergency communication; multiple tethered balloons; coverage rate; energy efficiency; multi-objective particle swarm optimization (MOPSO); network performance +
Footnote †: journal: _Entropy_  
0000-0001-6600-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-00000-0000-00000  
Wireless communication in complex environments, particularly in distant seas [6] and rural regions, presents significant challenges. Rough terrain and varied atmospheric conditions can lead to multi-path effects, causing signal attenuation, interference, and loss. Optimizing the deployment heights of HATBBSs can effectively reduce these multi-path effects, ensuring more direct and stable signal propagation. Additionally, environmental characteristics, such as humidity, atmospheric absorption, and marine salt spray, will attenuate radio waves, necessitating adjustments to transmit power and frequency band selection to reduce co-channel interference [7; 8] and maximize network coverage and energy efficiency.  
This paper offers an in-depth investigation and optimization of the deployment problem of balloons to ensure sufficient communication. The main contributions of our research are summarized as follows:  
(1) The complex dynamic characteristics of balloons in the air are considered to reflect practical application scenarios more comprehensively, especially the mobility characteristics. To capture and predict the positional changes of balloons accurately, we utilize a Gauss-Markov mobility model, which is well-suited for representing the continuous but partially random movement patterns of high-altitude platforms.  
(2) Based on the constructed system model and the corresponding constraints on distance, coverage, frequency band, and power, the balloon deployment problem is transformed into a multi-objective optimization problem to maximize target coverage and system energy efficiency.  
(3) Multi-objective particle swarm optimization (MOPSO) is applied to address the resulting mixed-integer nonlinear programming problem. Given the higher computational complexity of MOPSO, a low-complexity stochastic algorithm (SA) is also introduced as a benchmark to provide a comprehensive comparative performance analysis.  
The rest of this article is organized as follows. Section 2 briefly reviews related research. Section 3 introduces the system model and formulates the balloon deployment problem. Section 4 details the methodology used to solve the multi-objective optimization problem. Section 5 presents simulation validations and an analysis of the results. Finally, the paper is concluded in Section 6.