Robust Noncooperative Spectrum Sharing Game in Underwater Acoustic Interference Channels

Abstract

International audienceThis paper focuses on underwater acoustic (UA) communications and proposes a decentralized spectrum sharing method for noncooperative orthogonal frequency-division multiplexing systems in interference channels. The problem is formulated as a noncooperative game where the players are UA communication systems aiming at finding the power allocation on subcarriers that maximizes a utility function related to their information rate. Realistic assumptions regarding the UA context are formulated. Frequency-selective and randomly time-varying channels are considered. Each system is constrained in average power and adapts its power allocation strategy only with local knowledge of its channel statistics and noise plus interference power spectral density. This knowledge is obtained through a feedback link from the receiver. Estimation errors on the channel statistics are taken into account, thanks to a robust reformulation of the game. We show that an efficient decentralized spectrum sharing can be achieved when all players use a water-filling strategy against each other iteratively. Simulations results are obtained on synthetic but realistic channels. In configurations where the UA communication systems are in close areas, significant increases of spectral efficiencies can be expected compared to the conventional uniform power allocation. Results on channels sounded at sea support our conclusions

Online adaptive power allocation and channel state feedback strategies in underwater acoustic networks

“…The theoretical performance achieved in terms of information rates will be given for the two types of CSI. These comparisons constitutes an extension of the works in [7], [8].…”

“…This BR takes the form of a water-filling (WF) allocation over the noise plus interference PSD weighted by the inverse of the direct channel gains. The BRD consists, for the players, to play their BR one after the other until convergence to a NE of the game (see [7], [12], [13] for details on the technical conditions). In the present context of UWA communication in an interference channel, the players need only to know their direct channel gain and the aggregate PSD of the noise plus interference to update their own power allocation strategy by WF.…”

“…Here, it is assumed that the channel coherence time prohibits feedback of an instantaneous CSI (this is the case when the transmission range is such that the propagation delays is significantly higher than the coherence time). We adopt the robust approach in [7], [9] where the utility functions are defined as the worst ergodic rate relatively to the interference distributions. We have…”

Optimization of Acoustic Communication Links for a Swarm of AUVs: The COMET and NEMOSENS Examples

“…When a feedback link is available, the physical layer adaptation is getting some kind of channel state information from the receiver [6][7][8][9]12,13]. Such an approach can be efficient but is costly in terms of overhead and energy.…”

Q-Learning Based Adaptive Channel Selection for Underwater Sensor Networks

“…In [16] a delay-tolerant handshaking mechanism is implemented, which necessitates some overheads. More recently, [17]- [21] have investigated decentralized spectrum sharing between noncooperative UW communication links. Communications take place outside any network, without protocol, synchronization or information exchanges between different links.…”