A highly reliable resilient coding for wireless communication in extreme environments
Extreme environments (e.g., deep space, deep sea, and deep Earth) are characterized by high uncertainty and abundant resources. Exploring extreme regions not only drives breakthroughs in fundamental science fields such as oceanography and geology but also promotes significant technological and economic progress in areas such as resource discovery and environmental monitoring. As missions continue to scale in depth, duration, and complexity, reliable wireless communication becomes a cornerstone for successful control-command delivery, mission data transmission, and emergency response.1 Therefore, the design of communication systems in extreme environments has become a key capability to support safety, operational efficiency, and continuous exploration.
However, extreme environments impose significant challenges. Mission data exhibit inherently heterogeneous importance levels: control commands and safety telemetry demand stringent reliability and timeliness, whereas general sensing data can tolerate errors or latency. Such heterogeneity necessitates the dynamic adaptation of transmission strategies to ensure the reliable delivery of critical data under varying conditions. Furthermore, extreme environments expose communication systems to unprecedented physical constraints.
Specifically, deep space links suffer severe path loss and long propagation delays, resulting in a persistent ultra-low signal-to-noise ratio (SNR) pattern; deep-sea transmission is impaired by highly non-stationary multipath and Doppler variations, leading to a highly fluctuating, time-varying SNR2; and deep Earth exhibits unpredictable attenuation due to complex and heterogeneous geological structures, causing a severely attenuated SNR.3 The convergence of such adverse conditions renders stable and reliable communication an exceedingly challenging task in extreme environments.
The aforementioned challenges underscore significant performance bottlenecks in existing coding methods. At the source level, existing coding schemes typically treat all mission data uniformly, applying equal-probability compression or identical error protection regardless of priority. Such a uniform approach leads to suboptimal resource utilization and compromises the reliable delivery of critical mission information. At the channel level, various coding schemes, including Reed–Solomon, Bose–Chaudhuri–Hocquenghem, Turbo, low-density parity-check (LDPC) codes, and Polar codes, have been used in extreme environments.4,5 However, existing schemes exhibit obvious limitations under harsh channel conditions. Specifically, the inherent structure constraints of existing codes limit their error-correction ability in low-SNR conditions, leading to unreliable communication. Furthermore, the fixed redundancy and static decoding configuration of existing methods impede effective adaptation to fast time-varying channels, compromising communication reliability.
The resilient coding framework
In this commentary, we propose a highly reliable resilient coding framework that adaptively modifies the coding structure to enable differentiated data compression and error-correction effectiveness improvement. To cope with different SNR conditions, the proposed framework employs a universal resilient parity-check structure to ensure ultra-high reliability. At the same time, the framework incorporates specific mechanisms tailored to different extreme environments. Under sustained low-SNR and degraded-SNR conditions, the proposed framework prioritizes adaptive kernel selection and design to maximize coding gain. Under time-varying SNR conditions, it prioritizes dynamic reorganization of redundancy to cope with burst errors.
