Achieving high throughput and reliability in underwater acoustic networks is a challenging task due to the bandwidth-limited and unpredictable nature of the channel. In a multi-node structure, such as in the Internet of Underwater Things (IoUT), the efficiency of links varies dynamically because of the channel variations. When the channel is not in good condition, e.g., when in deep fade, channel-coding techniques fail to deliver the required information even with multiple rounds of retransmissions. An efficient and agile collaborative strategy among the nodes is required to assign appropriate resources to each link based on their status and capability. Hence, a cross-layer collaborative strategy is introduced to increase the throughput of the network by allocating unequal share of system resources to different nodes/links. The proposed solution adjusts the physical- and link-layer parameters in a collaborative manner for a Code Division Multiple Access (CDMA)-based underwater network. An adaptive Hybrid Automatic Repeat Request (HARQ) solution is employed to guarantee reliable communications against errors in poor communication links. Results are being validated using data collected from the LOON underwater testbed, which is hosted by the NATO STO Centre for Maritime Research and Experimentation (CMRE) in La Spezia, Italy.
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Adaptive Switching for Multimodal Underwater Acoustic Communications Based on Reinforcement Learning
The underwater acoustic (UWA) channel is a complex and stochastic process with large spatial and temporal dynamics. This work studies the adaptation of the communication strategy to the channel dynamics. Specifically, a set of communication strategies are considered, including frequency shift keying (FSK), single-carrier communication, and multicarrier communication. Based on the channel condition, a reinforcement learning (RL) algorithm, the Depth Determined Strategy Gradient (DDPG) method along with a Gumbel-softmax scheme is employed for intelligent and adaptive switching among those communication strategies. The adaptive switching is performed on a transmission block-by-block basis, with the goal of maximizing a long-term system performance. The reward function is defined based on the energy efficiency and the spectral efficiency of the communication strategies. Simulation results reveal that the proposed method outperforms a random selection method in time-varying channels.
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- Award ID(s):
- 1651135
- NSF-PAR ID:
- 10314505
- Date Published:
- Journal Name:
- the 15th International Conference on Underwater Networks & Systems (WUWNet)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3491315.3491354
