An alternating optimization of beamforming, semantic compression ratio, and fluid-antenna port selection is proposed for near-field rate maximization, with performance evaluated on a Jensen upper bound rather than the true ergodic rate.
Rate Maximization for Fluid Antenna System Assisted Semantic Communication
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abstract
In this paper, we investigate the problem of rate maximization in a fluid antenna system (FAS) assisted semantic communication system. In the considered model, a base station (BS) with multiple static antennas employs semantic extraction techniques to compress the data ready to be sent to a user. The user equipped with a fluid antenna is located in the near field coverage region of the BS. Our aim is to jointly optimize the transmit beamforming and the semantic compression rate at the BS, as well as the selection of activated ports in FAS, to maximize the equivalent transmission ratio under a specific power budget. We design an alternating algorithm to solve the problem, where we obtain the optimal semantic compression ratio is in closed form at each step. Simulation results validate the effectiveness of the proposed algorithm.
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Rate Maximization for Fluid Antenna System Assisted Semantic Communication
An alternating optimization of beamforming, semantic compression ratio, and fluid-antenna port selection is proposed for near-field rate maximization, with performance evaluated on a Jensen upper bound rather than the true ergodic rate.