LLM interprets natural-language policies to steer a projected-gradient power allocator in 8 parallel QPSK-AWGN channels, producing policy-dependent allocations and 60% lower mutual-information spread after abrupt channel reversals compared with the optimizer alone.
Adaptive resource allocation optimization using large language models in dynamic wireless environ- ments
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LLM-Steered Power Allocation for Parallel QPSK-AWGN Channels
LLM interprets natural-language policies to steer a projected-gradient power allocator in 8 parallel QPSK-AWGN channels, producing policy-dependent allocations and 60% lower mutual-information spread after abrupt channel reversals compared with the optimizer alone.