A Dual Decomposition Approach to the Sum Power Gaussian Vector Multiple Access Channel Sum Capacity Problem
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Bibliographic record
Abstract
Abstract — The Gaussian vector multiple access channel with a sum-power constraint across all users, rather than the usual individual power constraint on each user, has recently been shown to be the dual of a Gaussian vector broadcast channel [1] [2]. Further, a numerical algorithm for the sum capacity under the sum power constraint has been proposed in [3]. This paper proposes a different algorithm for this problem based on a dual decomposition approach. The proposed algorithm works in the Lagrangian dual domain; it is based on a modified iterative water-filling algorithm for the multiple access channel; and it is guaranteed to converge to the sum capacity in all cases. This spectrum optimization problem for the sum-power multiple access channel is also applicable to the optimal power allocation problem for an OFDM system with correlated noise. I.
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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